Sample records for latent structure analysis
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James, Richard J.; Dubey, Indu; Smith, Danielle; Ropar, Danielle; Tunney, Richard J.
2016-01-01
Autistic traits are widely thought to operate along a continuum. A taxometric analysis of Adult Autism Spectrum Quotient data was conducted to test this assumption, finding little support but identifying a high severity taxon. To understand this further, latent class and latent profile models were estimated that indicated the presence of six…
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Residual Structures in Latent Growth Curve Modeling
Grimm, Kevin J.; Widaman, Keith F.
2010-01-01
Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…
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Hoyle, R H
1991-02-01
Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.
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The structure of posttraumatic stress disorder: latent class analysis in 2 community samples.
Breslau, Naomi; Reboussin, Beth A; Anthony, James C; Storr, Carla L
2005-12-01
Latent structure analysis of DSM-IV posttraumatic stress disorder (PTSD) can help clarify how persons who experience traumatic events might be sorted into clusters with respect to their symptom profiles. Classification of persons exposed to traumatic events into clinically homogeneous groups would facilitate further etiologic and treatment research, as well as research on the relationship of trauma and PTSD with other disorders. To examine empirically the structure underlying PTSD criterion symptoms and identify discrete classes with similar symptom profiles. Data on PTSD symptoms from trauma-exposed subsets of 2 community samples were subjected to latent class analysis. The resultant classes were studied in associations with trauma type and indicators of impairment. The first sample is from the Detroit Area Survey of Trauma (1899 trauma-exposed respondents with complete data) and the second is from a mid-Atlantic study of young adults conducted by The Johns Hopkins University Prevention Research Center, Baltimore, Md (1377 trauma-exposed respondents with complete data). Respondents in the 2 community samples who experienced 1 or more qualifying PTSD-level traumatic events. Number, size, and symptom profiles of latent classes. In both samples, analysis yielded 3 classes: no disturbance, intermediate disturbance, and pervasive disturbance. The classes also varied qualitatively, with emotional numbing distinguishing the class of pervasive disturbance, a class that approximates the subset with DSM-IV PTSD. Members of the pervasive disturbance class were far more likely to report use of medical care and disruptions in life or activities. The 3-class structure separates trauma-exposed persons with pervasive disturbance (a class that approximates DSM-IV PTSD) from no disturbance and intermediate disturbance, a distinction that also helps identify population subgroups with low risk for any posttrauma disturbance. The results suggest that the structure of PTSD is ordinal
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The latent structure of oppositional defiant disorder in children and adults.
Barry, Tammy D; Marcus, David K; Barry, Christopher T; Coccaro, Emil F
2013-12-01
An understanding of the latent structure of oppositional defiant disorder (ODD) is essential for better developing causal models, improving diagnostic and assessment procedures, and enhancing treatments for the disorder. Although much research has focused on ODD-including recent studies informing the diagnostic criteria for DSM-5-research examining the latent structure of ODD is sparse, and no known study has specifically undertaken a taxometric analysis to address the issue of whether ODD is a categorical or dimensional construct. To address this gap, the authors conducted two separate studies using a set of taxometric analyses with data from the NICHD Study of Early Child Care and Youth Development (child study; n = 969) and with data from a large mixed sample of adults, which included participants reporting psychiatric difficulties as well as healthy controls (adult study; n = 600). The results of a variety of non-redundant analyses across both studies revealed a dimensional latent structure for ODD symptoms among both children and adults. These findings are consistent with previous studies that have examined latent structure of related constructs (e.g., aggression, antisocial behavior) as well as studies that have examined the dimensional versus categorical structure of ODD using methods other than taxometric analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Learning Latent Structure in Complex Networks
DEFF Research Database (Denmark)
Mørup, Morten; Hansen, Lars Kai
such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...
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Marcus, David K.; Barry, Tammy D.
2010-01-01
An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667–1078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators, for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD. PMID:20973595
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Marcus, David K; Barry, Tammy D
2011-05-01
An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.
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Latent factor structure of a behavioral economic marijuana demand curve.
Aston, Elizabeth R; Farris, Samantha G; MacKillop, James; Metrik, Jane
2017-08-01
Drug demand, or relative value, can be assessed via analysis of behavioral economic purchase task performance. Five demand indices are typically obtained from drug purchase tasks. The goal of this research was to determine whether metrics of marijuana reinforcement from a marijuana purchase task (MPT) exhibit a latent factor structure that efficiently characterizes marijuana demand. Participants were regular marijuana users (n = 99; 37.4% female, 71.5% marijuana use days [5 days/week], 15.2% cannabis dependent) who completed study assessments, including the MPT, during a baseline session. Principal component analysis was used to examine the latent structure underlying MPT indices. Concurrent validity was assessed via examination of relationships between latent factors and marijuana use, past quit attempts, and marijuana expectancies. A two-factor solution was confirmed as the best fitting structure, accounting for 88.5% of the overall variance. Factor 1 (65.8% variance) reflected "Persistence," indicating sensitivity to escalating marijuana price, which comprised four MPT indices (elasticity, O max , P max , and breakpoint). Factor 2 (22.7% variance) reflected "Amplitude," indicating the amount consumed at unrestricted price (intensity). Persistence factor scores were associated with fewer past marijuana quit attempts and lower expectancies of negative use outcomes. Amplitude factor scores were associated with more frequent use, dependence symptoms, craving severity, and positive marijuana outcome expectancies. Consistent with research on alcohol and cigarette purchase tasks, the MPT can be characterized with a latent two-factor structure. Thus, demand for marijuana appears to encompass distinct dimensions of price sensitivity and volumetric consumption, with differential relations to other aspects of marijuana motivation.
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Generalized latent variable modeling multilevel, longitudinal, and structural equation models
Skrondal, Anders; Rabe-Hesketh, Sophia
2004-01-01
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.
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Evangelopoulos, Nicholas E
2013-11-01
This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.
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Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters
Hoshino, Takahiro; Shigemasu, Kazuo
2008-01-01
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
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The Latent Structure of Attention Deficit/Hyperactivity Disorder in an Adult Sample
Marcus, David K.; Norris, Alyssa L.; Coccaro, Emil F.
2012-01-01
The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. PMID:22480749
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The latent structure of attention deficit/hyperactivity disorder in an adult sample.
Marcus, David K; Norris, Alyssa L; Coccaro, Emil F
2012-06-01
The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Structural identifiability of cyclic graphical models of biological networks with latent variables.
Wang, Yulin; Lu, Na; Miao, Hongyu
2016-06-13
Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and
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Latent Growth and Dynamic Structural Equation Models.
Grimm, Kevin J; Ram, Nilam
2018-05-07
Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.
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A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.
Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven
2003-01-01
Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)
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Chromatin Structure of Epstein-Barr Virus Latent Episomes.
Lieberman, Paul M
2015-01-01
EBV latent infection is characterized by a highly restricted pattern of viral gene expression. EBV can establish latent infections in multiple different tissue types with remarkable variation and plasticity in viral transcription and replication. During latency, the viral genome persists as a multi-copy episome, a non-integrated-closed circular DNA with nucleosome structure similar to cellular chromosomes. Chromatin assembly and histone modifications contribute to the regulation of viral gene expression, DNA replication, and episome persistence during latency. This review focuses on how EBV latency is regulated by chromatin and its associated processes.
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Do gender and directness of trauma exposure moderate PTSD's latent structure?
Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D
2016-11-30
The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.
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The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai.
Zheng, Yuchen; Kang, Qing; Huang, Jiabin; Jiang, Wenhui; Liu, Qiang; Chen, Han; Fan, Qing; Wang, Zhen; Chen, Jue; Xiao, Zeping
2017-08-25
Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. A total of 379 patients with eating disorders at Shanghai Mental Health Center were evaluated using the EDI questionnaire and a questionnaire developed by researchers from 2010 to 2016. SPSS 20.0 was used to enter data and analyze demographic data, and Latent GOLD was employed to conduct latent profile analysis. According to the results of latent profile analysis, patients with eating disorder were divided into five classes: low-weight fasting class (23.1%), non-fat-phobic binge/purge class (21.54%), low-fat-phobic binge class (19.27%), fat-phobic binge class (19.27%), and non-fat-phobic low-weight class (16.76%). Among the clinical symptoms extracted, there were significant differences in Body Mass Index (BMI), binge eating behavior, self-induced vomiting, laxative use and fat-phobic opinion; while there was no significant difference in restrictive food intake. Based on the clinical symptoms, there are five latent classes in Chinese patients with eating disorder, which is in accordance with the diagnostic categories of feeding and eating disorder in ICD-11. However, further work is needed in improving the fat-phobic opinion of patients with eating disorder and clarifying the BMI standard of thinness in the Chinese population.
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Delucchi, Kevin L; Katerberg, Hilga; Stewart, S Evelyn; Denys, Damiaan A J P; Lochner, Christine; Stack, Denise E; den Boer, Johan A; van Balkom, Anton J L M; Jenike, Michael A; Stein, Dan J; Cath, Danielle C; Mathews, Carol A
2011-01-01
Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous, and findings of underlying structure classification based on symptom grouping have been ambiguous to date. Variable-centered approaches, primarily factor analysis, have been used to identify homogeneous groups of symptoms; but person-centered latent methods have seen little use. This study was designed to uncover sets of homogeneous groupings within 1611 individuals with OCD based on symptoms. Latent class analysis models using 61 obsessive-compulsive symptoms collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, sex, symptom severity, and comorbid tic disorders were tested for relationship to class membership. Latent class analysis models of best fit yielded 3 classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher Yale-Brown Obsessive-Compulsive Scale symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes. These results provide support for the validity of a single underlying latent OCD construct, in addition to the distinct symptom factors identified previously via factor analyses. Copyright © 2011 Elsevier Inc. All rights reserved.
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A quantitative analysis on latent heat of an aqueous binary mixture.
Han, Bumsoo; Choi, Jeung Hwan; Dantzig, Jonathan A; Bischof, John C
2006-02-01
The latent heat during phase change of water-NaCl binary mixture was measured using a differential scanning calorimeter, and the magnitude for two distinct phase change events, water/ice and eutectic phase change, were analyzed considering the phase change characteristics of a binary mixture. During the analysis, the latent heat associated with each event was calculated by normalizing the amount of each endothermic peak with only the amount of sample participating in each event estimated from the lever rule for the phase diagram. The resulting latent heat of each phase change measured is 303.7 +/- 2.5 J/g for water/ice phase change, and 233.0 +/- 1.6 J/g for eutectic phase change, respectively regardless of the initial concentration of mixture. Although the latent heats of water/ice phase change in water-NaCl mixtures are closely correlated, further study is warranted to investigate the reason for smaller latent heat of water/ice phase change than that in pure water (335 J/g). The analysis using the lever rule was extended to estimate the latent heat of dihydrate as 115 J/g with the measured eutectic and water/ice latent heat values. This new analysis based on the lever rule will be useful to estimate the latent heat of water-NaCl mixtures at various concentrations, and may become a framework for more general analysis of latent heat of various biological solutions.
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Latent Transition Analysis with a Mixture Item Response Theory Measurement Model
Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian
2010-01-01
A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…
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The Latent Structure of Secure Base Script Knowledge
Waters, Theodore E. A.; Fraley, R. Chris; Groh, Ashley M.; Steele, Ryan D.; Vaughn, Brian E.; Bost, Kelly K.; Veríssimo, Manuela; Coppola, Gabrielle; Roisman, Glenn I.
2015-01-01
There is increasing evidence that attachment representations abstracted from childhood experiences with primary caregivers are organized as a cognitive script describing secure base use and support (i.e., the "secure base script"). To date, however, the latent structure of secure base script knowledge has gone unexamined--this despite…
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Directory of Open Access Journals (Sweden)
Zhan Gu
2015-01-01
Full Text Available Primary liver cancer (PLC is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.
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Gu, Zhan; Qi, Xiuzhong; Zhai, Xiaofeng; Lang, Qingbo; Lu, Jianying; Ma, Changping; Liu, Long; Yue, Xiaoqiang
2015-01-01
Primary liver cancer (PLC) is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM) plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.
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Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.
Directory of Open Access Journals (Sweden)
Jeban Ganesalingam
2009-09-01
Full Text Available Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001.The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.
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Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting
Directory of Open Access Journals (Sweden)
Wang Zan
2007-03-01
Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency
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Directory of Open Access Journals (Sweden)
Tinaliah Tinaliah
2018-01-01
Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.
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Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia
2013-06-01
We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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STRUCTURE RELATION OF VIOLENCE AND PERSONALITY LATENT DIMENSIONS OF PREADOLESCENT BASKETBALL PLAYERS
Directory of Open Access Journals (Sweden)
Miroljub Ivanović
2012-09-01
Full Text Available The aim of this research was to define structure relations of latent dimension violence among peers structure, characteristics and parent’s educational attitudes. In this research participated 134 basketball players (mini-jam, younger pioneers and pioneers. The research was conducted using the PRONA questionnaire for peers violence evaluation (Maksimovic and collaborators, 2008. Analysing the main components space of peers’ violence, three main components have been determined as dangerous behaviour exposure, announced victim and physiological violence. Mutual relation of these latent personality characteristics examinees dimensions and educational attitudes of their parents has been determined using the Pirson’s correlation coefficien.
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DEFF Research Database (Denmark)
Fenger, Mogens; Linneberg, A.; Werge, Thomas Mears
2008-01-01
and genetic variations of such networks. METHODS: In this study on type 2 diabetes mellitus, heterogeneity was resolved in a latent class framework combined with structural equation modelling using phenotypic indicators of distinct physiological processes. We modelled the clinical condition "the metabolic......BACKGROUND: Biological systems are interacting, molecular networks in which genetic variation contributes to phenotypic heterogeneity. This heterogeneity is traditionally modelled as a dichotomous trait (e.g. affected vs. non-affected). This is far too simplistic considering the complexity...
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Space-time latent component Modeling of Geo-referenced health data
Lawson, Andrew B.; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun
2010-01-01
Latent structure models have been proposed in many applications. For space time health data it is often important to be able to find underlying trends in time which are supported by subsets of small areas. Latent structure modeling is one approach to this analysis. This paper presents a mixture-based approach that can be appied to component selction. The analysis of a Georgia ambulatory asthma county level data set is presented and a simulation-based evaluation is made.
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Improving knowledge management systems with latent semantic analysis
International Nuclear Information System (INIS)
Sebok, A.; Plott, C.; LaVoie, N.
2006-01-01
Latent Semantic Analysis (LSA) offers a technique for improving lessons learned and knowledge management systems. These systems are expected to become more widely used in the nuclear industry, as experienced personnel leave and are replaced by younger, less-experienced workers. LSA is a machine learning technology that allows searching of text based on meaning rather than predefined keywords or categories. Users can enter and retrieve data using their own words, rather than relying on constrained language lists or navigating an artificially structured database. LSA-based tools can greatly enhance the usability and usefulness of knowledge management systems and thus provide a valuable tool to assist nuclear industry personnel in gathering and transferring worker expertise. (authors)
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Changes in latent fingerprint examiners' markup between analysis and comparison.
Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn
2015-02-01
After the initial analysis of a latent print, an examiner will sometimes revise the assessment during comparison with an exemplar. Changes between analysis and comparison may indicate that the initial analysis of the latent was inadequate, or that confirmation bias may have affected the comparison. 170 volunteer latent print examiners, each randomly assigned 22 pairs of prints from a pool of 320 total pairs, provided detailed markup documenting their interpretations of the prints and the bases for their comparison conclusions. We describe changes in value assessments and markup of features and clarity. When examiners individualized, they almost always added or deleted minutiae (90.3% of individualizations); every examiner revised at least some markups. For inconclusive and exclusion determinations, changes were less common, and features were added more frequently when the image pair was mated (same source). Even when individualizations were based on eight or fewer corresponding minutiae, in most cases some of those minutiae had been added during comparison. One erroneous individualization was observed: the markup changes were notably extreme, and almost all of the corresponding minutiae had been added during comparison. Latents assessed to be of value for exclusion only (VEO) during analysis were often individualized when compared to a mated exemplar (26%); in our previous work, where examiners were not required to provide markup of features, VEO individualizations were much less common (1.8%). Published by Elsevier Ireland Ltd.
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Latent-trait latent-class analysis of selfdisclosure in the work environment
Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.
2006-01-01
Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of
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Latent-trait latent-class analysis of selfdisclosure in the work environment
Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.
2005-01-01
Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of
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Latent class models in financial data analysis
Directory of Open Access Journals (Sweden)
Attilio Gardini
2007-10-01
Full Text Available This paper deals with optimal international portfolio choice by developing a latent class approach based on the distinction between international and non-international investors. On the basis of micro data, we analyze the effects of many social, demographic, economic and financial characteristics on the probability to be an international investor. Traditional measures of equity home bias do not allow for the existence of international investment rationing operators. On the contrary, by resorting to latent class analysis it is possible to detect the unobservable distinction between international investors and investors who are precluded from operating into international financial markets and, therefore, to evaluate the role of these unobservable constraints on equity home bias.
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Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P
2016-08-01
The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc
2017-01-01
Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780
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Space-time latent component modeling of geo-referenced health data.
Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun
2010-08-30
Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.
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Latent Class Analysis of Criminal Social Identity in a Prison Sample
Directory of Open Access Journals (Sweden)
Boduszek Daniel
2014-06-01
Full Text Available This study aimed to examine the number of latent classes of criminal social identity that exist among male recidivistic prisoners. Latent class analysis was used to identify homogeneous groups of criminal social identity. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the associationsto number of police arrests, recidivism, and violent offending while controlling for current age. The best fitting latent class model was a five-class solution: ‘High criminal social identity’ (17%, ‘High Centrality, Moderate Affect, Low Ties’ (21.7%, ‘Low Centrality, Moderate Affect, High Ties’ (13.3%,‘Low Cognitive, High Affect, Low Ties’ (24.6%, and ‘Low criminal social identity’ (23.4%. Each of the latent classes was predicted by differing external variables. Criminal social identity is best explained by five homogenous classes that display qualitative and quantitative differences.
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Evaluating the Latent Structure of the MMPI-2 F(p) Scale in a Forensic Sample: A Taxometric Analysis
Strong, David R.; Glassmire, David M.; Frederick, Richard I.; Greene, Roger L.
2006-01-01
P. A. Arbisi and Y. S. Ben-Porath (1995) originally proposed that the Infrequency Psychopathology scale, F(p), be used as the final step in an algorithm to determine the validity of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocol. The current study used taxometric procedures to determine the latent structure of F(p) among…
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Latent structure and construct validity of the reinforcement sensitivity questionnaire
Directory of Open Access Journals (Sweden)
Mitrović Dušanka
2008-01-01
Full Text Available The Revised reinforcement sensitivity theory contains three basic systems: Behavioral inhibition system (BAS, Behavioral activation system (BIS and the Fight/ Flight/ Freeze (FFF system. In this model, BIS is a system for detection of potential conflict or threat, and FFFS differs three basic patterns of reaction to actual or perceived danger. In Study 1, which was aimed at the examination of the latent structure of the RSQ, was conducted on a sample of 472 participants of both genders. The best - fitting model suggests that, at the top level of hierarchy, three dimensions exist, which are analogous to the BIS, BAS and FFF. The last dimension contains three subordinate dimensions, which represent the subsystems of the FFF. Study 2, in which 203 subjects participated, was aimed at examination of the relations between the dimensions of the Revised reinforcement sensitivity theory and dimensions of the PEN model. Confirmatory factor analyses of the RSQ and EPQ-R dimensions revealed that the best-fitting model comprised three latent dimensions, the first one being analogous to the BIS - Neuroticism, the second one to the BAS - Extraversion, and the third to the Aggressiveness- Psychoticism. The structure of the latent dimensions is in accordance with the expectations. The results state that fear and anxiety (which neurophysiological distinction is emphasized by Gray, are substantively similar on the behavioral level. Also, the results suggest that the Freeze dimension is probably closer to the BIS system than to the FFF.
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De Roover, K.; Vermunt, J.K.; Timmerman, Marieke E.; Ceulemans, Eva
2017-01-01
Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (for example, personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that may explain the covariances among variables; for example,
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Liu, R T
2016-04-01
A basic phenomenological question of much theoretical and empirical interest is whether the latent structure of depression is dimensional or categorical in nature. Prior taxometric studies of youth depression have yielded mixed findings. In a step towards resolving these contradictory findings, the current taxometric investigation is the first to utilize a recently developed objective index, the comparison curve fit index, to evaluate the latent structure of major depression in an epidemiological sample of children and adolescents. Data were derived from Mental Health of Children and Young People in Great Britain surveys. Participants were administered a structured diagnostic interview to assess for current depression. Parents (n = 683) were interviewed for children aged 5-16 years, and child interviews (n = 605) were conducted for those aged 11-16 years. MAMBAC (mean above minus below a cut), MAXEIG (maximum eigenvalue) and L-Mode (latent mode) analyses provided convergent support for a dimensional latent structure. The current findings suggest that depression in youth is more accurately conceptualized as a continuous syndrome rather than a discrete diagnostic entity.
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The Latent Structure of Psychopathy in Youth: A Taxometric Investigation
Vasey, Michael W.; Kotov, Roman; Frick, Paul J.; Loney, Bryan R.
2005-01-01
Using taxometric procedures, the latent structure of psychopathy was investigated in two studies of children and adolescents. Prior studies have identified a taxon (i.e., a natural category) associated with antisocial behavior in adults as well as children and adolescents. However, features of this taxon suggest that it is not psychopathy but…
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Latent-Trait Latent-Class Analysis of Self-disclosure in the Work Environment
Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.
2005-01-01
Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of
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Comparing methods of classifying life courses: Sequence analysis and latent class analysis
Elzinga, C.H.; Liefbroer, Aart C.; Han, Sapphire
2017-01-01
We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this
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Comparing methods of classifying life courses: sequence analysis and latent class analysis
Han, Y.; Liefbroer, A.C.; Elzinga, C.
2017-01-01
We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this
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Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask
2013-03-30
The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
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Latent variable models an introduction to factor, path, and structural equation analysis
Loehlin, John C
2004-01-01
This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind
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Mannarini, Stefania; Balottin, Laura; Toldo, Irene; Gatta, Michela
2016-10-01
The study, conducted on Italian preadolscents aged 11 to 13 belonging to the general population, aims to investigate the relationship between the emotional functioning, namely, alexithymia, and the risk of developing behavioral and emotional problems measured using the Strength and Difficulty Questionnaire. The latent class analysis approach allowed to identify two latent variables, accounting for the internalizing (emotional symptoms and difficulties in emotional awareness) and for the externalizing problems (conduct problems and hyperactivity, problematic relationships with peers, poor prosocial behaviors and externally oriented thinking). The two latent variables featured two latent classes: the difficulty in dealing with problems and the strength to face problems that was representative of most of the healthy participants with specific gender differences. Along with the analysis of psychopathological behaviors, the study of resilience and strengths can prove to be a key step in order to develop valuable preventive approaches to tackle psychiatric disorders. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.
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AMATCHMETHOD BASED ON LATENT SEMANTIC ANALYSIS FOR EARTHQUAKEHAZARD EMERGENCY PLAN
Directory of Open Access Journals (Sweden)
D. Sun
2017-09-01
Full Text Available The structure of the emergency plan on earthquake is complex, and it’s difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA. After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.
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Amatchmethod Based on Latent Semantic Analysis for Earthquakehazard Emergency Plan
Sun, D.; Zhao, S.; Zhang, Z.; Shi, X.
2017-09-01
The structure of the emergency plan on earthquake is complex, and it's difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA). After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.
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Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification
Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.
2010-01-01
Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.
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Walters, Glenn D.; Rogers, Richard; Berry, David T. R.; Miller, Holly A.; Duncan, Scott A.; McCusker, Paul J.; Payne, Joshua W.; Granacher, Robert P., Jr.
2008-01-01
The 6 nonoverlapping primary scales of the Structured Interview of Reported Symptoms (SIRS) were subjected to taxometric analysis in a group of 1,211 criminal and civil examinees in order to investigate the latent structure of feigned psychopathology. Both taxometric procedures used in this study, mean above minus below a cut (MAMBAC) and maximum…
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Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment
Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk
2005-01-01
Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data…
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Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane
2015-01-01
Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
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The Latent Factor Structure of Acute Stress Disorder following Bank Robbery
DEFF Research Database (Denmark)
Hansen, M.; Lasgaard, M.; Elklit, A.
2013-01-01
of the latent structure of ASD were specified and estimated. METHOD: The analyses were based on a national study of bank robbery victims (N = 450) using the acute stress disorder scale. RESULTS: The results of the confirmatory factor analyses showed that the DSM-IV model provided the best fit to the data. Thus...
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Longitudinal Physical Activity Patterns Among Older Adults: A Latent Transition Analysis.
Mooney, Stephen J; Joshi, Spruha; Cerdá, Magdalena; Kennedy, Gary J; Beard, John R; Rundle, Andrew G
2018-05-14
Most epidemiologic studies of physical activity measure either total energy expenditure or engagement in a single activity type, such as walking. These approaches may gloss over important nuances in activity patterns. We performed a latent transition analysis to identify patterns of activity types as well as neighborhood and individual determinants of changes in those activity patterns over two years in a cohort of 2,023 older adult residents of New York City, NY, surveyed between 2011 and 2013. We identified seven latent classes: 1) Mostly Inactive, 2) Walking, 3) Exercise, 4) Household Activities and Walking, 5) Household Activities and Exercise, 6) Gardening and Household Activities, and 7) Gardening, Household Activities, and Exercise. The majority of subjects retained the same activity patterns between waves (54% unchanged between waves 1 and 2, 66% unchanged between waves 2 and 3).Most latent class transitions were between classes distinguished only by one form of activity, and only neighborhood unemployment was consistently associated with changing between activity latent classes. Future latent transition analyses of physical activity would benefit from larger cohorts and longer follow-up periods to assess predictors of and long-term impacts of changes in activity patterns.
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Multilevel Latent Class Analysis: Parametric and Nonparametric Models
Finch, W. Holmes; French, Brian F.
2014-01-01
Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…
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Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele
2013-01-01
We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…
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Crawford, John R; Henry, Julie D
2003-06-01
To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS). The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.
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Sullivan, Adam John
In chapter 1, we consider the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and sensitivity analysis techniques to correct for such biases. We give an analysis of which effects in an SEM are and are not biased by an unmeasured confounder. It is shown that a single unmeasured confounder will bias not just one but numerous effects in an SEM. We present sensitivity analysis techniques to correct for biases in total, direct, and indirect effects when using SEM analyses, and illustrate these techniques with a study of aging and cognitive function. In chapter 2, we consider longitudinal mediation with latent growth curves. We define the direct and indirect effects using counterfactuals and consider the assumptions needed for identifiability of those effects. We develop models with a binary treatment/exposure followed by a model where treatment/exposure changes with time allowing for treatment/exposure-mediator interaction. We thus formalize mediation analysis with latent growth curve models using counterfactuals, makes clear the assumptions and extends these methods to allow for exposure mediator interactions. We present and illustrate the techniques with a study on Multiple Sclerosis(MS) and depression. In chapter 3, we report on a pilot study in blended learning that took place during the Fall 2013 and Summer 2014 semesters here at Harvard. We blended the traditional BIO 200: Principles of Biostatistics and created ID 200: Principles of Biostatistics and epidemiology. We used materials from the edX course PH207x: Health in Numbers: Quantitative Methods in Clinical & Public Health Research and used. These materials were used as a video textbook in which students would watch a given number of these videos prior to class. Using surveys as well as exam data we informally assess these blended classes from the student's perspective as well as a comparison of these students with students in another course, BIO 201
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Armour, Cherie; Műllerová, Jana; Elhai, Jon D
2016-03-01
The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.
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A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling
Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang
2017-01-01
It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…
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Gao, Junkai; Lv, Mengjiao; Lu, Jinshu; Chen, Yan; Zhang, Zijun; Zhang, Xiongjie; Zhu, Yingying
2017-12-01
Meso-structured onion-like silica (MOS), which had a highly ordered, onion-like multilayer; large surface area and pore volume; and highly curved mesopores, were synthesized as a support for stearic acid (SA) to develop a novel shape-stabilized phase change material (SA/MOS). The characterizations of SA/MOS were studied by the analysis technique of scanning electron microscope, infrared spectroscopy, x-ray diffraction, differential scanning calorimeter (DSC), and thermal gravimetry analysis (TGA). The results showed that the interaction between the SA and the MOS was physical adsorption and that the MOS had no effect on the crystal structure of the SA. The DSC results suggested that the melting and solidifying temperature of the SA/MOS were 72.7°C and 63.9°C with a melting latent heat of 108.0 J/g and a solidifying latent heat of 126.0 J/g, respectively, and the TGA results indicated that the SA/MOS had a good thermal stability. All of the results demonstrated that the SA/MOS was a promising thermal energy storage material candidate for practical applications.
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Pence, Brian Wells; Miller, William C.; Gaynes, Bradley N.
2009-01-01
Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to…
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Crawford, John R; Henry, Julie D; Ward, Aileen L; Blake, John
2006-03-01
To evaluate the proxy-rating version of the Prospective and Retrospective Memory Questionnaire (PRMQ) and provide norms and methods for score interpretation. Cross-sectional and correlational. The PRMQ was administered to a large sample drawn from the general adult population (N=570). Confirmatory factor analysis (CFA) was used to test competing models of its latent structure. Various psychometric methods were applied to provide clinicians with tools for score interpretation. The CFA model with optimal fit specified a general memory factor together with additional prospective and retrospective factors. The reliabilities of the PRMQ were acceptable (.83 to .92), and demographic variables did not influence ratings. Tables are presented for conversion of raw scores on the Total scale and Prospective and Retrospective scales to T scores. In addition, tables are provided to allow users to assess the reliability and abnormality of differences between proxy ratings on the Prospective and Retrospective scales. Finally, tables are also provided to compare proxy-ratings with self-ratings (using data from the present sample and self-rating data from a previous study). The proxy-rating version of the PRMQ provides a useful measure of everyday memory for use in clinical research and practice.
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Directory of Open Access Journals (Sweden)
Tan N Doan
Full Text Available Accurate diagnosis and subsequent treatment of latent tuberculosis infection (LTBI is essential for TB elimination. However, the absence of a gold standard test for diagnosing LTBI makes assessment of the true prevalence of LTBI and the accuracy of diagnostic tests challenging. Bayesian latent class models can be used to make inferences about disease prevalence and the sensitivity and specificity of diagnostic tests using data on the concordance between tests. We performed the largest meta-analysis to date aiming to evaluate the performance of tuberculin skin test (TST and interferon-gamma release assays (IGRAs for LTBI diagnosis in various patient populations using Bayesian latent class modelling.Systematic search of PubMeb, Embase and African Index Medicus was conducted without date and language restrictions on September 11, 2017 to identify studies that compared the performance of TST and IGRAs for LTBI diagnosis. Two IGRA methods were considered: QuantiFERON-TB Gold In Tube (QFT-GIT and T-SPOT.TB. Studies were included if they reported 2x2 agreement data between TST and QFT-GIT or T-SPOT.TB. A Bayesian latent class model was developed to estimate the sensitivity and specificity of TST and IGRAs in various populations, including immune-competent adults, immune-compromised adults and children. A TST cut-off value of 10 mm was used for immune-competent subjects and 5 mm for immune-compromised individuals.A total of 157 studies were included in the analysis. In immune-competent adults, the sensitivity of TST and QFT-GIT were estimated to be 84% (95% credible interval [CrI] 82-85% and 52% (50-53%, respectively. The specificity of QFT-GIT was 97% (96-97% in non-BCG-vaccinated and 93% (92-94% in BCG-vaccinated immune-competent adults. The estimated figures for TST were 100% (99-100% and 79% (76-82%, respectively. T-SPOT.TB has comparable specificity (97% for both tests and better sensitivity (68% versus 52% than QFT-GIT in immune-competent adults
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Preferences, benefits, and park visits: a latent class segmentation analysis
Kemperman, A.D.A.M.; Timmermans, H.J.P.
2006-01-01
This study describes and predicts segments of urban park visitors to support park planning and policy making. A latent class analysis is used to identify segments of park users who differ regarding their preferences for park characteristics, benefits sought in park visits, and sociodemographics.
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[Latent Class Analysis of Gambling Activities among Korean Adolescents].
Kang, Kyonghwa; Kim, Hyeongsu; Park, Ae Ran; Kim, Hee Young; Lee, Kunsei
2018-04-01
The aim of this study is to identify the types of gambling among adolescents and provide basic prevention information regarding adolescents' gambling problems. Secondary data from representative national survey on 2015 Youth Gambling Problems of Korea Center on Gambling Problems were used. Using latent class analysis (LCA), 13 gambling types such as offline and online games of 14,011 adolescents were classified, and gambling experiences and characteristics were analyzed. The subgroups of adolescent gambling were identified as four latent classes: a rare group (84.5% of the sample), a risk group (1.0%), an offline group (11.9%), and an expanded group (2.6%). The types and characteristics of gambling among the latent classes differed. In the risk group, adolescents participated in online illegal sports betting and internet casino, and gambling time, gambling expenses, and the number of gambling types were higher than other groups. Gambling frequently occur among adolescent, and the subtypes of gambling did not reveal homogeneous characteristics. In order to prevent adolescent gambling problems, it is a necessary to develop tailored prevention intervention in the nursing field, which is appropriate to the characteristics of adolescent gambling group and can help with early identification. © 2018 Korean Society of Nursing Science.
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Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.
Yasmin, Shamsunnahar; Eluru, Naveen
2016-10-01
The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping
2016-09-01
Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.
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Latent semantics as cognitive components
DEFF Research Database (Denmark)
Petersen, Michael Kai; Mørup, Morten; Hansen, Lars Kai
2010-01-01
Cognitive component analysis, defined as an unsupervised learning of features resembling human comprehension, suggests that the sensory structures we perceive might often be modeled by reducing dimensionality and treating objects in space and time as linear mixtures incorporating sparsity...... emotional responses can be encoded in words, we propose a simplified cognitive approach to model how we perceive media. Representing song lyrics in a vector space of reduced dimensionality using LSA, we combine bottom-up defined term distances with affective adjectives, that top-down constrain the latent......, which we suggest might function as cognitive components for perceiving the underlying structure in lyrics....
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Using existing questionnaires in latent class analysis
DEFF Research Database (Denmark)
Nielsen, Anne Molgaard; Vach, Werner; Kent, Peter
2016-01-01
BACKGROUND: Latent class analysis (LCA) is increasingly being used in health research, but optimal approaches to handling complex clinical data are unclear. One issue is that commonly used questionnaires are multidimensional, but expressed as summary scores. Using the example of low back pain (LBP......), the aim of this study was to explore and descriptively compare the application of LCA when using questionnaire summary scores and when using single items to subgrouping of patients based on multidimensional data. MATERIALS AND METHODS: Baseline data from 928 LBP patients in an observational study were...
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A latent transition analysis of bullying and victimization in Chinese primary school students.
Directory of Open Access Journals (Sweden)
Yiqin Pan
Full Text Available Bullying is a social phenomenon that impacts a large number of children and young people, worldwide. This study aimed to longitudinally examine the development of bullying and victimization in Chinese students in grades 4, 5, and 6. We used latent class analysis to empirically identify groups of youth with different bullying and victimization patterns, and then used latent transition analysis to explore the movement of children between these latent classes over time. Results showed that: (1 across the three time points, students could be classified into four classes: bullies, victims, bully-victims, and non-involved children; and (2 students in the non-involved class tended to remain in that class when moving to higher grades, students in the bully and victims classes tended to transition to the non-involved class, while students in the bully-victims class tended to transition to the bullies class. Thus, future intervention should be implemented to prevent bully-victims from bullying behaviors.
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An Evaluation of the Texas Functional Living Scale's Latent Structure and Subscales.
González, David Andrés; Soble, Jason R; Marceaux, Janice C; McCoy, Karin J M
2017-02-01
Performance-based functional assessment is a critical component of neuropsychological practice. The Texas Functional Living Scale (TFLS) has promise given its brevity, nationally representative norms, and co-norming with Wechsler scales. However, its subscale structure has not been evaluated. The purpose of this study was to evaluate the TFLS in a mixed clinical sample (n = 197). Reliability and convergent and discriminant validity coefficients were calculated with neurocognitive testing and collateral reports and factor analysis was performed. The Money and Calculation subscale had the best psychometric properties of the subscales. The evidence did not support solitary interpretation of the Time subscale. A three-factor latent structure emerged representing memory and semantic retrieval, performance and visual scanning, and financial calculation. This study added psychometric support for interpretation of the TFLS total score and some of its subscales. Study limitations included sample characteristics (e.g., gender ratio) and low power for collateral report analyses. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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International Nuclear Information System (INIS)
Lee, Young Eal
1996-02-01
Comparison of the effect of education and public information on the public acceptance of nuclear energy is carried out. For the increase of public acceptance, the correct understanding on the nuclear energy via proper regular school education would be the first basis and the appropriate public information services by utility and unbiased mass media would be the second basis. Subjects that which is more effect in education or information and how much effective quantitatively to improve the public acceptance are derived. Structural Equation Model (SEM) with Latent Variables (LVs) in social science to public attitudes towards nuclear energy is developed. Questionnaire is conducted to respondents who took part in the program of visiting the nuclear power plant opened by OKAEA in 1995. As a result of the analysis, effect of education for correct awareness of nuclear energy is more sensitive to public acceptance than that of information. It is shown that the susceptibility in education factor in influence of radiation on human body and that in information factor persons consider nuclear power plant as an environmental polluter. It is concluded that radiation treatment should be a 'Hand on Experience' and general principle of nuclear power generation should be contained in the educational text book. Education and information should not been independently performed but been carried out simultaneously and mutually aided. It is shown that this modeling approach is useful to make the decision for the long-term nuclear energy policy transparent and successful
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Directory of Open Access Journals (Sweden)
Dimitrios Stamovlasis
2018-04-01
Full Text Available This paper illustrates two psychometric methods, latent class analysis (LCA and taxometric analysis (TA using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.
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Stamovlasis, Dimitrios; Papageorgiou, George; Tsitsipis, Georgios; Tsikalas, Themistoklis; Vaiopoulou, Julie
2018-01-01
This paper illustrates two psychometric methods, latent class analysis (LCA) and taxometric analysis (TA) using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.
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Hankin, Benjamin L.; Snyder, Hannah R.; Gulley, Lauren D.; Schweizer, Tina H.; Bijttebier, Patricia; Nelis, Sabine; Toh, Gim; Vasey, Michael W.
2016-01-01
It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations. PMID:27739389
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Exploratory market structure analysis. Topology-sensitive methodology.
Mazanec, Josef
1999-01-01
Given the recent abundance of brand choice data from scanner panels market researchers have neglected the measurement and analysis of perceptions. Heterogeneity of perceptions is still a largely unexplored issue in market structure and segmentation studies. Over the last decade various parametric approaches toward modelling segmented perception-preference structures such as combined MDS and Latent Class procedures have been introduced. These methods, however, are not taylored for qualitative ...
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BOYSAN, Murat
2014-01-01
Introduction There has been a burgeoning literature considering the significant associations between obsessive-compulsive symptoms and dissociative experiences. In this study, the relationsips between dissociative symtomotology and dimensions of obsessive-compulsive symptoms were examined in homogeneous sub-groups obtained with latent class algorithm in an undergraduate Turkish sample. Method Latent profile analysis, a recently developed classification method based on latent class analysis, was applied to the Dissociative Experiences Scale (DES) item-response data from 2976 undergraduates. Differences in severity of obsessive-compulsive symptoms, anxiety and depression across groups were evaluated by running multinomial logistic regression analyses. Associations between latent class probabilities and psychological variables in terms of obsessive-compulsive sub-types, anxiety, and depression were assessed by computing Pearson’s product-moment correlation coefficients. Results The findings of the latent profile analysis supported further evidence for discontinuity model of dissociative experiences. The analysis empirically justified the distinction among three sub-groups based on the DES items. A marked proportion of the sample (42%) was assigned to the high dissociative class. In the further analyses, all sub-types of obsessive-compulsive symptoms significantly differed across latent classes. Regarding the relationships between obsessive-compulsive symptoms and dissociative symptomatology, low dissociation appeared to be a buffering factor dealing with obsessive-compulsive symptoms; whereas high dissociation appeared to be significantly associated with high levels of obsessive-compulsive symptoms. Conclusion It is concluded that the concept of dissociation can be best understood in a typological approach that dissociative symptomatology not only exacerbates obsessive-compulsive symptoms but also serves as an adaptive coping mechanism. PMID:28360635
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Konold, Timothy; Cornell, Dewey
2015-09-01
Informant-based systems of assessment are common platforms for measuring a variety of educational and psychological constructs where the use of multiple informants is considered best practice. In many instances, structurally different informant types (e.g., students and teachers) are solicited on the basis of their unique roles with the target of measurement. The use of multiple informants provides an opportunity to evaluate the degree to which the obtained ratings are influenced by the trait of focus and extraneous sources that can be attributed to the rater. Data from a multilevel multitrait-multimethod design in which students (N = 35,565) and teachers (N = 9,112), from 340 middle schools, responded to items measuring 3 dimensions of school climate were evaluated through a multilevel correlated trait-correlated method latent variable model. Results indicated that ratings of school climate obtained by students and teachers demonstrated high levels of convergent validity, and that school-level ratings obtained by students and teachers were equitable in the assessment of teasing and bullying. Student ratings of support and structure yielded somewhat stronger evidence of convergent validity than ratings obtained by teachers as revealed by their respective trait factor loadings. This was explained in part by the higher levels of common method effects that were observed for teachers. (c) 2015 APA, all rights reserved.
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Terry-McElrath, Yvonne M; O'Malley, Patrick M; Johnston, Lloyd D
2017-12-13
Effective cigarette smoking prevention and intervention programming is enhanced by accurate understanding of developmental smoking pathways across the life span. This study investigated within-person patterns of cigarette smoking from ages 18 to 50 among a US national sample of high school graduates, focusing on identifying ages of particular importance for smoking involvement change. Using data from approximately 15,000 individuals participating in the longitudinal Monitoring the Future study, trichotomous measures of past 30-day smoking obtained at 11 time points were modeled using repeated-measures latent class analyses. Sex differences in latent class structure and membership were examined. Twelve latent classes were identified: three characterized by consistent smoking patterns across age (no smoking; smoking developing effective smoking prevention and intervention programming. This study examined cigarette smoking among a national longitudinal US sample of high school graduates from ages 18 to 50 and identified distinct latent classes characterized by patterns of movement between no cigarette use, light-to-moderate smoking, and the conventional definition of heavy smoking at 11 time points via repeated-measures latent class analysis. Membership probabilities for each smoking class were estimated, and critical ages of susceptibility to change in smoking behaviors were identified. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Directory of Open Access Journals (Sweden)
Malirat Viviane
2006-10-01
Full Text Available Abstract Background Foot-and-mouth disease (FMD is a highly contagious viral disease of even-toed ungulates. Serological diagnosis/surveillance of FMD presents several problems as there are seven serotypes worldwide and in the event of vaccination it may be necessary to be able to identify FMD infected/exposed animals irrespective of their vaccination status. The recent development of non-structural 3ABC protein (NSP ELISA tests has greatly advanced sero-diagnosis/surveillance as these tests detect exposure to live virus for any of the seven serotypes of FMD, even in vaccinated populations. This paper analyses the performance of three NSP tests using a Bayesian formulation of the Hui-Walter latent class model to estimate test sensitivity and specificity in the absence of a "gold-standard" test, using sera from a well described cattle population in Cameroon with endemic FMD. Results The analysis found a high sensitivity and specificity for both the Danish C-ELISA and the World Organisation for Animal Health (O.I.E. recommended South American I-ELISA. However, the commercial CHEKIT kit, though having high specificity, has very low sensitivity. The results of the study suggests that for NSP ELISAs, latent class models are a useful alternative to the traditional approach of evaluating diagnostic tests against a known "gold-standard" test as imperfections in the "gold-standard" may give biased test characteristics. Conclusion This study demonstrates that when applied to naturally infected zebu cattle managed under extensive rangeland conditions, the FMD ELISAs may not give the same parameter estimates as those generated from experimental studies. The Bayesian approach allows for full posterior probabilities and capture of the uncertainty in the estimates. The implications of an imperfect specificity are important for the design and interpretation of sero-surveillance data and may result in excessive numbers of false positives in low prevalence
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Chiu, Ming-Chuan; Hsieh, Min-Chih
2016-05-01
The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
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Symptom Cluster Research With Biomarkers and Genetics Using Latent Class Analysis.
Conley, Samantha
2017-12-01
The purpose of this article is to provide an overview of latent class analysis (LCA) and examples from symptom cluster research that includes biomarkers and genetics. A review of LCA with genetics and biomarkers was conducted using Medline, Embase, PubMed, and Google Scholar. LCA is a robust latent variable model used to cluster categorical data and allows for the determination of empirically determined symptom clusters. Researchers should consider using LCA to link empirically determined symptom clusters to biomarkers and genetics to better understand the underlying etiology of symptom clusters. The full potential of LCA in symptom cluster research has not yet been realized because it has been used in limited populations, and researchers have explored limited biologic pathways.
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Non-destructive forensic latent fingerprint acquisition with chromatic white light sensors
Leich, Marcus; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus
2011-02-01
Non-destructive latent fingerprint acquisition is an emerging field of research, which, unlike traditional methods, makes latent fingerprints available for additional verification or further analysis like tests for substance abuse or age estimation. In this paper a series of tests is performed to investigate the overall suitability of a high resolution off-the-shelf chromatic white light sensor for the contact-less and non-destructive latent fingerprint acquisition. Our paper focuses on scanning previously determined regions with exemplary acquisition parameter settings. 3D height field and reflection data of five different latent fingerprints on six different types of surfaces (HDD platter, brushed metal, painted car body (metallic and non-metallic finish), blued metal, veneered plywood) are experimentally studied. Pre-processing is performed by removing low-frequency gradients. The quality of the results is assessed subjectively; no automated feature extraction is performed. Additionally, the degradation of the fingerprint during the acquisition period is observed. While the quality of the acquired data is highly dependent on surface structure, the sensor is capable of detecting the fingerprint on all sample surfaces. On blued metal the residual material is detected; however, the ridge line structure dissolves within minutes after fingerprint placement.
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Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests.
Directory of Open Access Journals (Sweden)
Raphaël Mourad
Full Text Available Linkage disequilibrium study represents a major issue in statistical genetics as it plays a fundamental role in gene mapping and helps us to learn more about human history. The linkage disequilibrium complex structure makes its exploratory data analysis essential yet challenging. Visualization methods, such as the triangular heat map implemented in Haploview, provide simple and useful tools to help understand complex genetic patterns, but remain insufficient to fully describe them. Probabilistic graphical models have been widely recognized as a powerful formalism allowing a concise and accurate modeling of dependences between variables. In this paper, we propose a method for short-range, long-range and chromosome-wide linkage disequilibrium visualization using forests of hierarchical latent class models. Thanks to its hierarchical nature, our method is shown to provide a compact view of both pairwise and multilocus linkage disequilibrium spatial structures for the geneticist. Besides, a multilocus linkage disequilibrium measure has been designed to evaluate linkage disequilibrium in hierarchy clusters. To learn the proposed model, a new scalable algorithm is presented. It constrains the dependence scope, relying on physical positions, and is able to deal with more than one hundred thousand single nucleotide polymorphisms. The proposed algorithm is fast and does not require phase genotypic data.
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Bayesian latent feature modeling for modeling bipartite networks with overlapping groups
DEFF Research Database (Denmark)
Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard
2016-01-01
Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....
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Longitudinal Research with Latent Variables
van Montfort, Kees; Satorra, Albert
2010-01-01
This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from some background information about the specific approach, short history and the ma
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Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc
2014-01-01
We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.
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Solidarity and Conflict Between Adult Childrenand Parents : A Latent Class Analysis
Gaalen, Ruben I. van; Dykstra, Pearl A.
2006-01-01
Using multiple dimensions of solidarity and conflict in a latent class analysis, we develop a typology of adult child–parent relationships. The data (N ¼ 4,990) are from the first wave of the Netherlands Kinship Panel Study. In descending order of relationship quality, the 5 types are harmonious
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Latent vs. Observed Variables : Analysis of Irrigation Water Efficiency Using SEM and SUR
Tang, Jianjun; Folmer, Henk
In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equationmodeling (SEM), in the latter
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poLCA: An R Package for Polytomous Variable Latent Class Analysis
Directory of Open Access Journals (Sweden)
Drew A. Linzer
2011-08-01
Full Text Available poLCA is a software package for the estimation of latent class and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment. Both models can be called using a single simple command line. The basic latent class model is a finite mixture model in which the component distributions are assumed to be multi-way cross-classification tables with all variables mutually independent. The latent class regression model further enables the researcher to estimate the effects of covariates on predicting latent class membership. poLCA uses expectation-maximization and Newton-Raphson algorithms to find maximum likelihood estimates of the model parameters.
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Incorporating Measurement Non-Equivalence in a Cross-Study Latent Growth Curve Analysis.
Flora, David B; Curran, Patrick J; Hussong, Andrea M; Edwards, Michael C
2008-10-01
A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement equivalence, or invariance, across the developmental periods. Similarly, when data from more than one study are combined into a single analysis, it is again important to assess measurement equivalence across the data sources. Yet, how to incorporate non-equivalence when it is discovered is not well described for applied researchers. Here, we present an item response theory approach that can be used to create scale scores from measures while explicitly accounting for non-equivalence. We demonstrate these methods in the context of a latent curve analysis in which data from two separate studies are combined to create a single longitudinal model spanning several developmental periods.
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A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.
Mo, Qianxing; Shen, Ronglai; Guo, Cui; Vannucci, Marina; Chan, Keith S; Hilsenbeck, Susan G
2018-01-01
Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Tweets clustering using latent semantic analysis
Rasidi, Norsuhaili Mahamed; Bakar, Sakhinah Abu; Razak, Fatimah Abdul
2017-04-01
Social media are becoming overloaded with information due to the increasing number of information feeds. Unlike other social media, Twitter users are allowed to broadcast a short message called as `tweet". In this study, we extract tweets related to MH370 for certain of time. In this paper, we present overview of our approach for tweets clustering to analyze the users' responses toward tragedy of MH370. The tweets were clustered based on the frequency of terms obtained from the classification process. The method we used for the text classification is Latent Semantic Analysis. As a result, there are two types of tweets that response to MH370 tragedy which is emotional and non-emotional. We show some of our initial results to demonstrate the effectiveness of our approach.
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Latent geometry of bipartite networks
Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri
2017-03-01
Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.
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Jean-Pierre, Pascal; Fundakowski, Christopher; Perez, Enrique; Jean-Pierre, Shadae E; Jean-Pierre, Ashley R; Melillo, Angelica B; Libby, Rachel; Sargi, Zoukaa
2013-02-01
Cancer and its treatments are associated with psychological distress that can negatively impact self-perception, psychosocial functioning, and quality of life. Patients with head and neck cancers (HNC) are particularly susceptible to psychological distress. This study involved a cross-validation of the Measure of Body Apperception (MBA) for HNC patients. One hundred and twenty-two English-fluent HNC patients between 20 and 88 years of age completed the MBA on a Likert scale ranging from "1 = disagree" to "4 = agree." We assessed the latent structure and internal consistency reliability of the MBA using Principal Components Analysis (PCA) and Cronbach's coefficient alpha (α), respectively. We determined convergent and divergent validities of the MBA using correlations with the Hospital Anxiety and Depression Scale (HADS), observer disfigurement rating, and patients' clinical and demographic variables. The PCA revealed a coherent set of items that explained 38 % of the variance. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.73 and the Bartlett's test of sphericity was statistically significant (χ (2) (28) = 253.64; p 0.05). The MBA is a valid and reliable screening measure of body apperception for HNC patients.
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Disintermediation and User-generated Content: A Latent Segmentation Analysis
Del Chiappa, Giacomo; Lorenzo-Romero, Carlota; Constantinides, Efthymios
2014-01-01
This research investigates the perceptions of different groups of consumers for and against the disintermediation of travel agencies also considering the relative power in influencing the tourist's choices exerted by user generated-content (UGC). A web-based survey is carried out in Spain and 961 complete questionnaires was obtained. A latent segmentation was applied on factors identified running an exploratory factor analysis on a list of 16 statements, the use and frequency of use of the In...
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Application of a latent class analysis to empirically define eating disorder phenotypes.
Keel, Pamela K; Fichter, Manfred; Quadflieg, Norbert; Bulik, Cynthia M; Baxter, Mark G; Thornton, Laura; Halmi, Katherine A; Kaplan, Allan S; Strober, Michael; Woodside, D Blake; Crow, Scott J; Mitchell, James E; Rotondo, Alessandro; Mauri, Mauro; Cassano, Giovanni; Treasure, Janet; Goldman, David; Berrettini, Wade H; Kaye, Walter H
2004-02-01
Diagnostic criteria for eating disorders influence how we recognize, research, and treat eating disorders, and empirically valid phenotypes are required for revealing their genetic bases. To empirically define eating disorder phenotypes. Data regarding eating disorder symptoms and features from 1179 individuals with clinically significant eating disorders were submitted to a latent class analysis. The resulting latent classes were compared on non-eating disorder variables in a series of validation analyses. Multinational, collaborative study with cases ascertained through diverse clinical settings (inpatient, outpatient, and community). Members of affected relative pairs recruited for participation in genetic studies of eating disorders in which probands met DSM-IV-TR criteria for anorexia nervosa (AN) or bulimia nervosa and had at least 1 biological relative with a clinically significant eating disorder. Main Outcome Measure Number and clinical characterization of latent classes. A 4-class solution provided the best fit. Latent class 1 (LC1) resembled restricting AN; LC2, AN and bulimia nervosa with the use of multiple methods of purging; LC3, restricting AN without obsessive-compulsive features; and LC4, bulimia nervosa with self-induced vomiting as the sole form of purging. Biological relatives were significantly likely to belong to the same latent class. Across validation analyses, LC2 demonstrated the highest levels of psychological disturbance, and LC3 demonstrated the lowest. The presence of obsessive-compulsive features differentiates among individuals with restricting AN. Similarly, the combination of low weight and multiple methods of purging distinguishes among individuals with binge eating and purging behaviors. These results support some of the distinctions drawn within the DSM-IV-TR among eating disorder subtypes, while introducing new features to define phenotypes.
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Stability of alcohol use and teen dating violence for female youth: A latent transition analysis.
Choi, Hye Jeong; Elmquist, JoAnna; Shorey, Ryan C; Rothman, Emily F; Stuart, Gregory L; Temple, Jeff R
2017-01-01
Alcohol use is one of the most widely accepted and studied risk factors for teen dating violence (TDV). Too little research has explored longitudinally if it is true that an adolescent's alcohol use and TDV involvement simultaneously occur. In the current study, we examined whether there were latent status based on past-year TDV and alcohol use and whether female adolescents changed their statuses of TDV and alcohol use over time. The sample consisted of 583 female youths in seven public high schools in Texas. Three waves of longitudinal data collected from 2011 to 2013 were utilised in this study. Participants completed self-report assessments of alcohol use (past-year alcohol use, number of drinks in the past month and episodic heavy drinking within the past month) and psychological and physical TDV victimisation and perpetration. Latent transition analysis was used to examine if the latent status based on TDV and alcohol use changed over time. Five separate latent statuses were identified: (i) no violence, no alcohol; (ii) alcohol; (iii) psychological violence, no alcohol; (iv) psychological violence, alcohol; and (v) physical and psychological violence, alcohol. Latent transition analysis indicated that adolescents generally remained in the same subgroup across time. This study provides evidence on the co-occurrence of alcohol use and teen dating violence, and whether teens' status based on dating violence and alcohol use are stable over time. Findings from the current study highlight the importance of targeting both TDV and substance use in intervention and prevention programs. [Choi HJ, Elmquist J, Shorey RC, Rothman EF, Stuart GL,Temple JR. Stability of alcohol use and teen dating violence for female youth: Alatent transition analysis. Drug Alcohol Rev 2017;36:80-87]. © 2017 Australasian Professional Society on Alcohol and other Drugs.
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The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai
,; ,; ,; ,; ,; ,; ,; ,; ,; ,
2017-01-01
Background Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. Aims To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. Methods A total of 379 patients with eating disorders at Shanghai Mental Health C...
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UNSOLVED AND LATENT CRIME: DIFFERENCES AND SIMILARITIES
Directory of Open Access Journals (Sweden)
Mikhail Kleymenov
2017-01-01
Full Text Available УДК 343Purpose of the article is to study the specific legal and informational nature of the unsolved crime in comparison with the phenomenon of delinquency, special study and analysis to improve the efficiency of law enforcement.Methods of research are abstract-logical, systematic, statistical, study of documents. The main results of research. Unsolved crime has specific legal, statistical and informational na-ture as the crime phenomenon, which is expressed in cumulative statistical population of unsolved crimes. An array of unsolved crimes is the sum of the number of acts, things of which is suspended and not terminated. The fault of the perpetrator in these cases is not proven, they are not considered by the court, it is not a conviction. Unsolved crime must be registered. Latent crime has a different informational nature. The main symptom of latent crimes is the uncertainty for the subjects of law enforcement, which delegated functions of identification, registration and accounting. Latent crime is not recorded. At the same time, there is a "border" area between the latent and unsolved crimes, which includes covered from the account of the crime. In modern Russia the majority of crimes covered from accounting by passing the decision about refusal in excitation of criminal case. Unsolved crime on their criminogenic consequences represents a significant danger to the public is higher compared to latent crime.It is conducted in the article a special analysis of the differences and similarities in the unsolved latent crime for the first time in criminological literature.The analysis proves the need for radical changes in the current Russian assessment of the state of crime and law enforcement to solve crimes. The article argues that an unsolved crime is a separate and, in contrast to latent crime, poorly understood phenomenon. However unsolved latent crime and have common features and areas of interaction.
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Substance Use Patterns Among Adolescents in Europe: A Latent Class Analysis.
Göbel, Kristin; Scheithauer, Herbert; Bräker, Astrid-Britta; Jonkman, Harrie; Soellner, Renate
2016-07-28
Several researchers have investigated substance use patterns using a latent class analysis; however, hardly no studies exist on substance use patterns across countries. Adolescent substance use patterns, demographic factors, and international differences in the prevalence of substance use patterns were explored. Data from 25 European countries were used to identify patterns of adolescent (12-16 years, 50.6% female) substance use (N = 33,566). Latent class analysis revealed four substance use classes: nonusers (68%), low-alcohol users (recent use of beer, wine, and alcopops; 16.1%), alcohol users (recent use of alcohol and lifetime use of marijuana; 11.2%), and polysubstance users (recent use of alcohol, marijuana, and other illicit drugs; 4.7%). Results support a general pattern of adolescent substance use across all countries; however, the prevalence rates of use patterns vary for each country. The present research provides insight into substance use patterns across Europe by using a large international adolescent sample, multidimensional indicators and a variety of substances. Substance use patterns are helpful when targeting policy and prevention strategies.
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Ullrich-French, Sarah; Cox, Anne E.; Cooper, Brittany Rhoades
2016-01-01
Previous research has used cluster analysis to examine how social physique anxiety (SPA) combines with motivation in physical education. This study utilized a more advanced analytic approach, latent profile analysis (LPA), to identify profiles of SPA and motivation regulations. Students in grades 9-12 (N = 298) completed questionnaires at two time…
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Assessing model fit in latent class analysis when asymptotics do not hold
van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.
2015-01-01
The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values
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Solidarity and conflict between adult children and parents: a latent class analysis
van Gaalen, R.I.A.; Dykstra, P.A.
2006-01-01
Using multiple dimensions of solidarity and conflict in a latent class analysis, we develop a typology of adult child–parent relationships. The data (N= 4,990) are from the first wave of the Netherlands Kinship Panel Study. In descending order of relationship quality, the 5 types are harmonious
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Computer assessment of interview data using latent semantic analysis.
Dam, Gregory; Kaufmann, Stefan
2008-02-01
Clinical interviews are a powerful method for assessing students' knowledge and conceptualdevelopment. However, the analysis of the resulting data is time-consuming and can create a "bottleneck" in large-scale studies. This article demonstrates the utility of computational methods in supporting such an analysis. Thirty-four 7th-grade student explanations of the causes of Earth's seasons were assessed using latent semantic analysis (LSA). Analyses were performed on transcriptions of student responses during interviews administered, prior to (n = 21) and after (n = 13) receiving earth science instruction. An instrument that uses LSA technology was developed to identify misconceptions and assess conceptual change in students' thinking. Its accuracy, as determined by comparing its classifications to the independent coding performed by four human raters, reached 90%. Techniques for adapting LSA technology to support the analysis of interview data, as well as some limitations, are discussed.
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Treatment of Latent Tuberculosis Infection: An Updated Network Meta-analysis
Zenner, D.; Beer, N.; Harris, R. J.; Lipman, M. C.; Stagg, H. R.; van der Werf, M. J.
2017-01-01
Background: Treatment of latent tuberculosis infection (LTBI) is an important component of tuberculosis (TB) control, and this study updates a previous network meta-analysis of the best LTBI treatment options to inform public health action and programmatic management of LTBI. Purpose: To evaluate the comparative efficacy and harms of LTBI treatment regimens aimed at preventing active TB among adults and children. Data Sources: PubMed, Embase, and Web of Science from indexing ...
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Pathways of early fatherhood, marriage, and employment: a latent class growth analysis.
Dariotis, Jacinda K; Pleck, Joseph H; Astone, Nan M; Sonenstein, Freya L
2011-05-01
In the National Longitudinal Survey of Youth 1979 (NLSY79), young fathers include heterogeneous subgroups with varying early life pathways in terms of fatherhood timing, the timing of first marriage, and holding full-time employment. Using latent class growth analysis with 10 observations between ages 18 and 37, we derived five latent classes with median ages of first fatherhood below the cohort median (26.4), constituting distinct early fatherhood pathways representing 32.4% of NLSY men: (A) Young Married Fathers, (B) Teen Married Fathers, (C) Young Underemployed Married Fathers, (D) Young Underemployed Single Fathers, and (E) Young Later-Marrying Fathers. A sixth latent class of men who become fathers around the cohort median, following full-time employment and marriage (On-Time On-Sequence Fathers), is the comparison group. With sociodemographic background controlled, all early fatherhood pathways show disadvantage in at least some later-life circumstances (earnings, educational attainment, marital status, and incarceration). The extent of disadvantage is greater when early fatherhood occurs at relatively younger ages (before age 20), occurs outside marriage, or occurs outside full-time employment. The relative disadvantage associated with early fatherhood, unlike early motherhood, increases over the life course.
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Further Examining Berry's Model: The Applicability of Latent Profile Analysis to Acculturation
Fox, Rina S.; Merz, Erin L.; Solórzano, Martha T.; Roesch, Scott C.
2013-01-01
This study used latent profile analysis (LPA) to identify acculturation profiles. A three-profile solution fit the data best, and comparisons on demographic and psychosocial outcomes as a function of profile yielded expected results. The findings support using LPA as a parsimonious way to model acculturation without anticipating profiles in…
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Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining.
Directory of Open Access Journals (Sweden)
Gabriele Prati
Full Text Available The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type, road user (i.e., opponent vehicle and cyclist's maneuver, type of collision, age and gender of the cyclist, vehicle (type of opponent vehicle, and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather. To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types.
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Zwemmer, J N P; Berkhof, J; Castelijns, J A; Barkhof, F; Polman, C H; Uitdehaag, B M J
2006-10-01
Disease heterogeneity is a major issue in multiple sclerosis (MS). Classification of MS patients is usually based on clinical characteristics. More recently, a pathological classification has been presented. While clinical subtypes differ by magnetic resonance imaging (MRI) signature on a group level, a classification of individual MS patients based purely on MRI characteristics has not been presented so far. To investigate whether a restricted classification of MS patients can be made based on a combination of quantitative and qualitative MRI characteristics and to test whether the resulting subgroups are associated with clinical and laboratory characteristics. MRI examinations of the brain and spinal cord of 50 patients were scored for 21 quantitative and qualitative characteristics. Using latent class analysis, subgroups were identified, for whom disease characteristics and laboratory measures were compared. Latent class analysis revealed two subgroups that mainly differed in the extent of lesion confluency and MRI correlates of neuronal loss in the brain. Demographics and disease characteristics were comparable except for cognitive deficits. No correlations with laboratory measures were found. Latent class analysis offers a feasible approach for classifying subgroups of MS patients based on the presence of MRI characteristics. The reproducibility, longitudinal evolution and further clinical or prognostic relevance of the observed classification will have to be explored in a larger and independent sample of patients.
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Hansen, Maj; Lasgaard, Mathias; Elklit, Ask
2013-03-01
Acute stress disorder (ASD) was introduced into the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) to identify posttraumatic stress reactions occurring within the first month after a trauma and thus help to identify victims at risk of developing posttraumatic stress disorder (PTSD). Since its introduction, research into ASD has focused on the prediction of PTSD, whereas only a few studies have investigated the latent structure of ASD. Results of the latter have been mixed. In light of the current proposal for the ASD diagnosis in the pending DSM-5, there is a profound need for empirical studies that investigate the latent structure of ASD prior to the DSM-5 being finalized. Based on previous factor analytic research, the DSM-IV, and the proposed DSM-5 formulation of ASD, four different models of the latent structure of ASD were specified and estimated. The analyses were based on a national study of bank robbery victims (N = 450) using the acute stress disorder scale. The results of the confirmatory factor analyses showed that the DSM-IV model provided the best fit to the data. Thus, the present study suggests that the latent structure of ASD may best be characterized according to the four-factor DSM-IV model of ASD (i.e., dissociation, re-experiencing, avoidance, and arousal) following exposure to bank robbery. The results are pertinent in light of the pending DSM-5 and add to the debate about the conceptualization of ASD. . © 2012 The British Psychological Society.
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Men and women are from Earth: examining the latent structure of gender.
Carothers, Bobbi J; Reis, Harry T
2013-02-01
Taxometric methods enable determination of whether the latent structure of a construct is dimensional or taxonic (nonarbitrary categories). Although sex as a biological category is taxonic, psychological gender differences have not been examined in this way. The taxometric methods of mean above minus below a cut, maximum eigenvalue, and latent mode were used to investigate whether gender is taxonic or dimensional. Behavioral measures of stereotyped hobbies and physiological characteristics (physical strength, anthropometric measurements) were examined for validation purposes, and were taxonic by sex. Psychological indicators included sexuality and mating (sexual attitudes and behaviors, mate selectivity, sociosexual orientation), interpersonal orientation (empathy, relational-interdependent self-construal), gender-related dispositions (masculinity, femininity, care orientation, unmitigated communion, fear of success, science inclination, Big Five personality), and intimacy (intimacy prototypes and stages, social provisions, intimacy with best friend). Constructs were with few exceptions dimensional, speaking to Spence's (1993) gender identity theory. Average differences between men and women are not under dispute, but the dimensionality of gender indicates that these differences are inappropriate for diagnosing gender-typical psychological variables on the basis of sex. (c) 2013 APA, all rights reserved.
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An examination of generalized anxiety disorder and dysthymic disorder by latent class analysis
Rhebergen, D.; van der Steenstraten, I.M.; Sunderland, M.; de Graaf, R.; ten Have, M.; Lamers, F.; Penninx, B.W.J.H.; Andrews, G.
2014-01-01
Background The nosological status of generalized anxiety disorder (GAD) versus dysthymic disorder (DD) has been questioned. The aim of this study was to examine qualitative differences within (co-morbid) GAD and DD symptomatology. Method Latent class analysis was applied to anxious and depressive
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Carter, Allison; Roth, Eric Abella; Ding, Erin; Milloy, M-J; Kestler, Mary; Jabbari, Shahab; Webster, Kath; de Pokomandy, Alexandra; Loutfy, Mona; Kaida, Angela
2018-03-01
We used latent class analysis to identify substance use patterns for 1363 women living with HIV in Canada and assessed associations with socio-economic marginalization, violence, and sub-optimal adherence to combination antiretroviral therapy (cART). A six-class model was identified consisting of: abstainers (26.3%), Tobacco Users (8.81%), Alcohol Users (31.9%), 'Socially Acceptable' Poly-substance Users (13.9%), Illicit Poly-substance Users (9.81%) and Illicit Poly-substance Users of All Types (9.27%). Multinomial logistic regression showed that women experiencing recent violence had significantly higher odds of membership in all substance use latent classes, relative to Abstainers, while those reporting sub-optimal cART adherence had higher odds of being members of the poly-substance use classes only. Factors significantly associated with Illicit Poly-substance Users of All Types were sexual minority status, lower income, and lower resiliency. Findings underline a need for increased social and structural supports for women who use substances to support them in leading safe and healthy lives with HIV.
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Edens, John F.; Marcus, David K.; Morey, Leslie C.
2009-01-01
Although paranoid personality is one of the most commonly diagnosed personality disorders and is associated with numerous negative life consequences, relatively little is known about the structural properties of this condition. This study examines whether paranoid personality traits represent a latent dimension or a discrete class (i.e., taxon). In study 1, we conducted taxometric analyses of paranoid personality disorder criteria in a sample of 731 patients participating in the Collaborative...
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The Latent Structure of Dictionaries.
Vincent-Lamarre, Philippe; Massé, Alexandre Blondin; Lopes, Marcos; Lord, Mélanie; Marcotte, Odile; Harnad, Stevan
2016-07-01
How many words-and which ones-are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a "Strongly Connected Subset" of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest-the graph's "minimum feedback vertex set" or MinSet-is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. Copyright © 2016 Cognitive Science Society, Inc.
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Bauer, Daniel J.; Curran, Patrick J.
2004-01-01
Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…
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Dissociative features in posttraumatic stress disorder: A latent profile analysis.
Műllerová, Jana; Hansen, Maj; Contractor, Ateka A; Elhai, Jon D; Armour, Cherie
2016-09-01
The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) characterizes the dissociative subtype of posttraumatic stress disorder (PTSD) in terms of the individual meeting the criteria for PTSD and additionally reporting symptoms of depersonalization and/or derealization. The current study aimed to examine whether a dissociative PTSD profile may include alternative features of dissociation and whether it could be differentiated from a nondissociative PTSD profile on certain psychopathologies and demographics. Data from 309 trauma-exposed participants, collected through Amazon Mechanical Turk, were subjected to latent profile analysis. Regression analyses were used to examine the predictors of latent classes. Three discrete profiles named Baseline, PTSD, and Dissociative profile were uncovered. All examined features of dissociation were significantly elevated in the Dissociative profile. Anxiety, male sex, being employed, and having a minority racial background significantly predicted the Dissociative profile relative to the PTSD profile. The study points to the importance of alternative symptoms of dissociation in the dissociative PTSD subtype beyond the symptoms of depersonalization and derealization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Study The role of latent variables in lost working days by Structural Equation Modeling Approach
Directory of Open Access Journals (Sweden)
Meysam Heydari
2016-12-01
Full Text Available Background: Based on estimations, each year about 250 million work-related injuries and many temporary or permanent disabilities occur which most are preventable. Oil and Gas industries are among industries with high incidence of injuries in the world. The aim of this study has investigated the role and effect of different risk management variables on lost working days (LWD in the seismic projects. Methods: This study was a retrospective, cross-sectional and systematic analysis, which was carried out on occupational accidents between 2008-2015(an 8 years period in different seismic projects for oilfield exploration at Dana Energy (Iranian Seismic Company. The preliminary sample size of the study were 487accidents. A systems analysis approach were applied by using root case analysis (RCA and structural equation modeling (SEM. Tools for the data analysis were included, SPSS23 and AMOS23 software. Results: The mean of lost working days (LWD, was calculated 49.57, the final model of structural equation modeling showed that latent variables of, safety and health training factor(-0.33, risk assessment factor(-0.55 and risk control factor (-0.61 as direct causes significantly affected of lost working days (LWD in the seismic industries (p< 0.05. Conclusion: The finding of present study revealed that combination of variables affected in lost working days (LWD. Therefore,the role of these variables in accidents should be investigated and suitable programs should be considered for them.
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Occurence of internet addiction in a general population sample: A latent class analysis
Rumpf, H.J.; Vermulst, A.A.; Bischof, A.; Kastirke, N.; Gürtler, D.; Bischof, G.; Meerkerk, G.J.; John, U.; Meyer, C.
2014-01-01
Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. Methods: A
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Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.
Hayden, Kathleen M; Kuchibhatla, Maragatha; Romero, Heather R; Plassman, Brenda L; Burke, James R; Browndyke, Jeffrey N; Welsh-Bohmer, Kathleen A
2014-11-01
Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline. To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis. The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership. Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment. Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
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Refining the Classification of Children with Selective Mutism: A Latent Profile Analysis
Cohan, Sharon L.; Chavira, Denise A.; Shipon-Blum, Elisa; Hitchcock, Carla; Roesch, Scott C.; Stein, Murray B.
2008-01-01
The goal of this study was to develop an empirically derived classification system for selective mutism (SM) using parent-report measures of social anxiety, behavior problems, and communication delays. The sample consisted of parents of 130 children (ages 5-12) with SM. Results from latent profile analysis supported a 3-class solution made up of…
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Data on the interexaminer variation of minutia markup on latent fingerprints.
Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn
2016-09-01
The data in this article supports the research paper entitled "Interexaminer variation of minutia markup on latent fingerprints" [1]. The data in this article describes the variability in minutia markup during both analysis of the latents and comparison between latents and exemplars. The data was collected in the "White Box Latent Print Examiner Study," in which each of 170 volunteer latent print examiners provided detailed markup documenting their examinations of latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. Each examiner examined 22 latent-exemplar pairs; an average of 12 examiners marked each latent.
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DEFF Research Database (Denmark)
Mølgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner
2017-01-01
. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two...
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Henseler, Jorg; Chin, Wynne W.
2010-01-01
In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…
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Latent variables and route choice behavior
DEFF Research Database (Denmark)
Prato, Carlo Giacomo; Bekhor, Shlomo; Pronello, Cristina
2012-01-01
In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior...... and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation...
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Multilevel structural equation models for assessing moderation within and across levels of analysis.
Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J
2016-06-01
Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Exposing Latent Information in Folksonomies for Reasoning
2010-01-14
1.73 $.") http://www.w3.org/2006/07/SWD/ SKOS /reference/20081001/ Spiteri, L.F. (2007) "The structure and form of folksonomy tags: The road to the...Exposing Latent Information in Folksonomies for Reasoning January 14, 2010 Sponsored by Defense Advanced Research Projects Agency (DOD...DATES COVERED (From - To! 4/14/2009-12/23/2009 4. TITLE AND SUBTITLE Exposing Latent Information in Folksonomies for Reasoning Sa. CONTRACT
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On the explaining-away phenomenon in multivariate latent variable models.
van Rijn, Peter; Rijmen, Frank
2015-02-01
Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.
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Yeung, Wing-Fai; Chung, Ka-Fai; Zhang, Nevin Lian-Wen; Zhang, Shi Ping; Yung, Kam-Ping; Chen, Pei-Xian; Ho, Yan-Yee
2016-01-01
Chinese medicine (CM) syndrome (zheng) differentiation is based on the co-occurrence of CM manifestation profiles, such as signs and symptoms, and pulse and tongue features. Insomnia is a symptom that frequently occurs in major depressive disorder despite adequate antidepressant treatment. This study aims to identify co-occurrence patterns in participants with persistent insomnia and major depressive disorder from clinical feature data using latent tree analysis, and to compare the latent variables with relevant CM syndromes. One hundred and forty-two participants with persistent insomnia and a history of major depressive disorder completed a standardized checklist (the Chinese Medicine Insomnia Symptom Checklist) specially developed for CM syndrome classification of insomnia. The checklist covers symptoms and signs, including tongue and pulse features. The clinical features assessed by the checklist were analyzed using Lantern software. CM practitioners with relevant experience compared the clinical feature variables under each latent variable with reference to relevant CM syndromes, based on a previous review of CM syndromes. The symptom data were analyzed to build the latent tree model and the model with the highest Bayes information criterion score was regarded as the best model. This model contained 18 latent variables, each of which divided participants into two clusters. Six clusters represented more than 50 % of the sample. The clinical feature co-occurrence patterns of these six clusters were interpreted as the CM syndromes Liver qi stagnation transforming into fire, Liver fire flaming upward, Stomach disharmony, Hyperactivity of fire due to yin deficiency, Heart-kidney noninteraction, and Qi deficiency of the heart and gallbladder. The clinical feature variables that contributed significant cumulative information coverage (at least 95 %) were identified. Latent tree model analysis on a sample of depressed participants with insomnia revealed 13 clinical
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Latent transition analysis of pre-service teachers' efficacy in mathematics and science
Ward, Elizabeth Kennedy
This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the STEBI-B, MTEBI-r, and the ABNTMS instruments. The findings suggest that LTA is a viable technique for use in teacher efficacy research. Teacher efficacy is modeled as a construct with two dimensions: personal teaching efficacy (PTE) and outcome expectancy (OE). Findings suggest that the mathematics and science teaching efficacy (PTE) of pre-service teachers is a multi-class phenomena. The analyses revealed a four-class model of PTE at the beginning and end of the final year of teacher training. Results indicate that when pre-service teachers transition between classes, they tend to move from a lower efficacy class into a higher efficacy class. In addition, the findings suggest that time-varying variables (attitudes and beliefs) and time-invariant variables (previous coursework, previous experiences, and teacher perceptions) are statistically significant predictors of efficacy class membership. Further, analyses suggest that the measures used to assess outcome expectancy are not suitable for LCA and LTA procedures.
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Eldridge, Ronald C; Flanders, W Dana; Bostick, Roberd M; Fedirko, Veronika; Gross, Myron; Thyagarajan, Bharat; Goodman, Michael
2017-09-01
Since oxidative stress involves a variety of cellular changes, no single biomarker can serve as a complete measure of this complex biological process. The analytic technique of structural equation modeling (SEM) provides a possible solution to this problem by modelling a latent (unobserved) variable constructed from the covariance of multiple biomarkers. Using three pooled datasets, we modelled a latent oxidative stress variable from five biomarkers related to oxidative stress: F 2 -isoprostanes (FIP), fluorescent oxidation products, mitochondrial DNA copy number, γ-tocopherol (Gtoc) and C-reactive protein (CRP, an inflammation marker closely linked to oxidative stress). We validated the latent variable by assessing its relation to pro- and anti-oxidant exposures. FIP, Gtoc and CRP characterized the latent oxidative stress variable. Obesity, smoking, aspirin use and β-carotene were statistically significantly associated with oxidative stress in the theorized directions; the same exposures were weakly and inconsistently associated with the individual biomarkers. Our results suggest that using SEM with latent variables decreases the biomarker-specific variability, and may produce a better measure of oxidative stress than do single variables. This methodology can be applied to similar areas of research in which a single biomarker is not sufficient to fully describe a complex biological phenomenon.
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BayesLCA: An R Package for Bayesian Latent Class Analysis
Directory of Open Access Journals (Sweden)
Arthur White
2014-11-01
Full Text Available The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian setting. Three methods for fitting the model are provided, incorporating an expectation-maximization algorithm, Gibbs sampling and a variational Bayes approximation. The article briefly outlines the methodology behind each of these techniques and discusses some of the technical difficulties associated with them. Methods to remedy these problems are also described. Visualization methods for each of these techniques are included, as well as criteria to aid model selection.
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A Latent Profile Analysis of Math Achievement, Numerosity, and Math Anxiety in Twins
Hart, Sara A.; Logan, Jessica A. R.; Thompson, Lee; Kovas, Yulia; McLoughlin, Gráinne; Petrill, Stephen A.
2016-01-01
Underperformance in math is a problem with increasing prevalence, complex etiology, and severe repercussions. This study examined the etiological heterogeneity of math performance in a sample of 264 pairs of 12-year-old twins assessed on measures of math achievement, numerosity, and math anxiety. Latent profile analysis indicated 5 groupings of…
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A simple low cost latent fingerprint sensor based on deflectometry and WFT analysis
Dhanotia, Jitendra; Chatterjee, Amit; Bhatia, Vimal; Prakash, Shashi
2018-02-01
In criminal investigations, latent fingerprints are one of the most significant forms of evidence and most commonly used forensic investigation tool worldwide. The existing non-contact latent fingerprint detection systems are bulky, expensive and require environment which is shock and vibration resistant, thereby limiting their usability outside the laboratory. In this article, a compact, full field, low cost technique for profiling of fingerprints using deflectometry is proposed. Using inexpensive mobile phone screen based structured illumination, and windowed Fourier transform (WFT) based phase retrieval mechanism, the 2D and 3D phase plots reconstruct the profile information of the fingerprint. The phase information is also used to confirm a match between two fingerprints in real time. Since the proposed technique is non-interferometric, the measurements are least affected by environmental perturbations. Using the proposed technique, a portable sensor capable of field deployment has been realized.
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Chan, Raymond C K; Qing, Yonghong; Wu, Qiuping; Shum, David
2010-06-01
This study aimed to examine the latent structure of the Chinese version of the Comprehensive Assessment of Prospective Memory (CAPM) using confirmatory factor analysis. A total of 264 healthy Chinese participants (118 men and 146 women) took part in the study and their ages ranged from 17 to 90 years. There was no gender effect upon the frequency of prospective memory (PM) forgetting but age and education were found to be correlated significantly with these frequencies in the current sample. Results of the study also showed that the model with the best fit had a tripartite structure which consisted of a general memory factor (with all items loading on it) plus a basic activities of daily living as well as an instrumental activities of daily living factor. Furthermore, this tripartite model was robust across subgroups with respect to gender, education, and age. These findings provide support for the construct validity of the original CAPM and demonstrate its utility in another culture.
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Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary
2014-11-01
Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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Bayesian Latent Class Analysis Tutorial.
Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca
2018-01-01
This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.
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LATENT STRUCTURE OF MOTOR ABILITIES AND SKILLS OF DEAF CHILDREN
Directory of Open Access Journals (Sweden)
Husnija Hasanbegović
2012-04-01
Full Text Available In this work surveys of latent motility abilities and skills of school children are shown. The sample for this survey was consisted of two subsamples. First one has consisted of deaf children N=29, and the second one has consisted hearing children of same age N=69. Subsamples of deaf is chosen according to model of applied sample, and subsample is chosen randomly, so two stages group sample N=90 has been created. After quantitative differences have been discovered between subsamples, hearing pupils have shown statistically better results at motility skills and techniques than deaf children and cumulative results have been subjected to inter correlation of variables. The target of using this method was determination of saturation of common variability through saturation of variables and their correlation by Ortoblique rotation for determination of latent information that are going to serve as practical guides at education and deaf children treatment, because of improvement of their motility abilities and skills according to hearing children. Three factors have been singled out as main preview of measurement on manifest variables. According to first review of measuring it has been established that at deaf children is needed to work on improving of physical abilities and mobility and then developed motility abilities and skills. Their information has been gained most probably by non system fluctuations as information about ability of balance maintaining which is most probably non dependable of motility abilities and skills as at deaf and hearing children too. According to this survey by entering the structure of measuring instrument it is possible to create programs for improving motility abilities and skills at deaf children.
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Latent heat coldness storage; Stockage du froid par chaleur latente
Energy Technology Data Exchange (ETDEWEB)
Dumas, J.P. [Pau Univ., Lab. de Thermodynamique et Energetique, LTE, 64 (France)
2002-07-01
This article presents the advantages of latent heat storage systems which use the solid-liquid phase transformation of a pure substance or of a solution. The three main methods of latent heat storage of coldness are presented: ice boxes, encapsulated nodules, and ice flows: 1 - definition of the thermal energy storage (sensible heat, latent heat, thermochemical storage); 2 - advantages and drawbacks of latent heat storage; 3 - choice criteria for a phase-change material; 4 - phenomenological aspect of liquid-solid transformations (phase equilibrium, crystallisation and surfusion); 5 - different latent heat storage processes (ice boxes, encapsulated nodules, two-phase refrigerating fluids); 6 - ice boxes (internal and external melting, loop, air injection, measurement of ice thickness); 7 - encapsulated nodules (nodules, tank, drainage, advantage and drawbacks, charge and discharge); 8 - two-phase refrigerating fluids (composition, ice fabrication, flow circulation, flow storage, exchangers). (J.S.)
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Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing
2015-05-01
We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.
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A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.
Brusco, Michael J; Shireman, Emilie; Steinley, Douglas
2017-09-01
The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach
Directory of Open Access Journals (Sweden)
Ranak B Trivedi
2010-07-01
Full Text Available Ranak B Trivedi1, Brian J Ayotte2, Carolyn T Thorpe3, David Edelman4, Hayden B Bosworth51Northwest Health Services Research and Development Service Center of Excellence, VA Puget Sound Health Care System, Seattle, Washington; 2Boston VA Health Care System, Boston, Massachusetts; 3Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin; 4Department of Medicine, Duke University Medical Center, Durham, North Carolina; 5Research Professor, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USAAbstract: To determine subtypes of adherence, 636 hypertensive patients (48% White, 34% male reported adherence to medications, diet, exercise, smoking, and home blood pressure monitoring. A latent class analysis approach was used to identify subgroups that adhere to these five self-management behaviors. Fit statistics suggested two latent classes. The first class (labeled “more adherent” included patients with greater probability of adhering to recommendations compared with the second class (labeled “less adherent” with regard to nonsmoking (97.7% versus 76.3%, medications (75.5% versus 49.5%, diet (70.7% versus 46.9%, exercise (63.4% versus 27.2%, and blood pressure monitoring (32% versus 3.4%. Logistic regression analyses used to characterize the two classes showed that “more adherent” participants were more likely to report full-time employment, adequate income, and better emotional and physical well-being. Results suggest the presence of a less adherent subtype of hypertensive patients. Behavioral interventions designed to improve adherence might best target these at-risk patients for greater treatment efficiency.Keywords: adherence, hypertension, latent class analysis, self-management
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Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items
Lu, Irene R. R.; Thomas, D. Roland
2008-01-01
This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…
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Usage of Latent Class Analysis in Diagnostic Microbiology in the Absence of Gold Standard Test
Directory of Open Access Journals (Sweden)
Gul Bayram Abiha
2016-12-01
Full Text Available The evaluation of performance of various tests diagnostic tests in the absence of gold standard is an important problem. Latent class analysis (LCA is a statistical analysis method known for many years, especially in the absence of a gold standard for evaluation of diagnostic tests so that LCA has found its wide application area. During the last decade, LCA method has widely used in for determining sensivity and specifity of different microbiological tests. It has investigated in the diagnosis of mycobacterium tuberculosis, mycobacterium bovis, human papilloma virus, bordetella pertussis, influenza viruses, hepatitis E virus (HEV, hepatitis C virus (HCV and other various viral infections. Researchers have compared several diagnostic tests for the diagnosis of different pathogens with LCA. We aimed to evaluate performance of latent class analysis method used microbiological diagnosis in various diseases in several researches. When we took into account all of these tests' results, we suppose that LCA is a good statistical analysis method to assess different test performances in the absence of gold standard. [Archives Medical Review Journal 2016; 25(4.000: 467-488
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Directory of Open Access Journals (Sweden)
Kanayama M
2016-06-01
Full Text Available Mieko Kanayama,1 Machiko Suzuki,1 Yoshikazu Yuma2 1Department of Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan; 2Department of Human Development Education, Graduate School of Education, Hyogo University of Teacher Education, Kato, Hyogo, Japan Abstract: The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. Keywords: burnout, collaboration, latent class growth analysis, interprofessional care, special needs schools
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International Nuclear Information System (INIS)
Gao Feng; Han Jiaxing; Lv Caifeng; Wang Qin; Zhang Jun; Li Qun; Bao Liru; Li Xin
2012-01-01
Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core–shell-structured CdTe-SiO 2 quantum dots (QDs) as fluorescent labeling marks. Core–shell-structured CdTe-SiO 2 QDs are prepared via a simple solution-based approach using NH 2 NH 2 ·H 2 O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe-SiO 2 QDs show spherical shapes with well-defined core–shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe-SiO 2 QDs is largely enhanced by surface modification of the SiO 2 shell. The CdTe-SiO 2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe-SiO 2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe-SiO 2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.
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Jain, Anil K; Feng, Jianjiang
2009-06-01
The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.
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Identifying subgroups of patients using latent class analysis
DEFF Research Database (Denmark)
Nielsen, Anne Mølgaard; Kent, Peter; Hestbæk, Lise
2017-01-01
BACKGROUND: Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However......, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. METHODS: From 928 LBP patients consulting...... of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. RESULTS: For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches...
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International Nuclear Information System (INIS)
Min, Qilong; Li, Rui; Wu, Xiaoqing; Fu, Yunfei
2013-01-01
An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages of hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water. Specifically, rain events are segregated into three rain types: warm, convective, and stratiform, based on their dynamical and thermodynamical characteristics. As the first of the series, only the warm rain LH algorithm is presented and evaluated here. The major microphysical processes of condensation and evaporation for warm rain are parameterized through traditional rain growth theory, with the aid of Cloud Resolving Model (CRM) simulations. The evaluation or the self-consistency tests indicate that the physical based retrievals capture the fundamental LH processes associated with the warm rain life cycle. There is no significant systematic bias in terms of convection strength, illustrated by the month-long CRM simulation as the mesoscale convective systems (MCSs) experience from initial, mature, to decay stages. The overall monthly-mean LH comparison showed that the total LH, as well as condensation heating and evaporation cooling components, agree with the CRM simulation. -- Highlights: ► An exploratory study on physics-based warm rain latent heat retrieval algorithm. ► Utilize the full information of the vertical structures of cloud and rainfall. ► Directly link water mass measurements to latent heat at instantaneous pixel level. ► Applicable at various stages of cloud system life cycle
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Discriminative latent models for recognizing contextual group activities.
Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg
2012-08-01
In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.
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Latent-failure risk estimates for computer control
Dunn, William R.; Folsom, Rolfe A.; Green, Owen R.
1991-01-01
It is shown that critical computer controls employing unmonitored safety circuits are unsafe. Analysis supporting this result leads to two additional, important conclusions: (1) annual maintenance checks of safety circuit function do not, as widely believed, eliminate latent failure risk; (2) safety risk remains even if multiple, series-connected protection circuits are employed. Finally, it is shown analytically that latent failure risk is eliminated when continuous monitoring is employed.
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A Multinomial Probit Model with Latent Factors
DEFF Research Database (Denmark)
Piatek, Rémi; Gensowski, Miriam
2017-01-01
be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...
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Park, Jeong Mo; Han, Ae Kyung; Cho, Yoon Hee
2011-12-01
The purpose of this study was to investigate the construct equivalence of the five general factors (subjective health, eating habits, physical activities, sedentary lifestyle, and sleeping behaviors) and to compare the latent means between male and female middle school students in Incheon, Korea. The 2008 Korean Youth Risk Behavior Survey data was used for analysis. Multigroup confirmatory factor analysis was performed to test whether the scale has configural, metric, and scalar invariance across gender. Configural invariance, metric invariance, and factor invariance were satisfied for latent means analysis (LMA) between genders. Male and female students were significantly different in LMA of all factors. Male students reported better subjective health, consumed more fast food and carbonated drinks, participated in more physical activities, showed less sedentary behavior, and enjoyed better quality of sleep than female students. Health providers should consider gender differences when they develop and deliver health promotion programs aimed at adolescents. Copyright © 2011. Published by Elsevier B.V.
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Yang, Jun-Ho; Yoh, Jack J
2018-01-01
A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.
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Lyon, Maureen E; Kimmel, Allison L; Cheng, Yao Iris; Wang, Jichuan
2016-10-01
The purpose of this study was to determine whether distinct latent profiles of religiousness/spirituality exist for ALWH, and if so, are latent profile memberships associated with health-related quality of life (HRQoL). Latent profile analysis of religiosity identified four profiles/groups. Compared to the other three groups, higher levels of emotional well-being were found among young perinatally infected adolescents who attended religious services, but who did not pray privately, feel God's presence or identify as religious or spiritual. Social HRQoL was significantly higher among the highest overall religious/spiritual group. Understanding adolescent profiles of religiousness/spirituality on HRQoL could inform faith-based interventions. Trial registration NCT01289444.
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Population Structure Analysis of Bull Genomes of European and Western Ancestry
DEFF Research Database (Denmark)
Chung, Neo Christopher; Szyda, Joanna; Frąszczak, Magdalena
2017-01-01
Since domestication, population bottlenecks, breed formation, and selective breeding have radically shaped the genealogy and genetics of Bos taurus. In turn, characterization of population structure among diverse bull (males of Bos taurus) genomes enables detailed assessment of genetic resources...... and origins. By analyzing 432 unrelated bull genomes from 13 breeds and 16 countries, we demonstrate genetic diversity and structural complexity among the European/Western cattle population. Importantly, we relaxed a strong assumption of discrete or admixed population, by adapting latent variable models...... harboring largest genetic differentiation suggest positive selection underlying population structure. We carried out gene set analysis using SNP annotations to identify enriched functional categories such as energy-related processes and multiple development stages. Our population structure analysis of bull...
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Solomon, April D; Hytinen, Madison E; McClain, Aryn M; Miller, Marilyn T; Dawson Cruz, Tracey
2018-01-01
DNA profiles have been obtained from fingerprints, but there is limited knowledge regarding DNA analysis from archived latent fingerprints-touch DNA "sandwiched" between adhesive and paper. Thus, this study sought to comparatively analyze a variety of collection and analytical methods in an effort to seek an optimized workflow for this specific sample type. Untreated and treated archived latent fingerprints were utilized to compare different biological sampling techniques, swab diluents, DNA extraction systems, DNA concentration practices, and post-amplification purification methods. Archived latent fingerprints disassembled and sampled via direct cutting, followed by DNA extracted using the QIAamp® DNA Investigator Kit, and concentration with Centri-Sep™ columns increased the odds of obtaining an STR profile. Using the recommended DNA workflow, 9 of the 10 samples provided STR profiles, which included 7-100% of the expected STR alleles and two full profiles. Thus, with carefully selected procedures, archived latent fingerprints can be a viable DNA source for criminal investigations including cold/postconviction cases. © 2017 American Academy of Forensic Sciences.
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Latent variable modeling%建立隐性变量模型
Institute of Scientific and Technical Information of China (English)
蔡力
2012-01-01
@@ A latent variable model, as the name suggests,is a statistical model that contains latent, that is, unobserved, variables.Their roots go back to Spearman's 1904 seminal work[1] on factor analysis,which is arguably the first well-articulated latent variable model to be widely used in psychology, mental health research, and allied disciplines.Because of the association of factor analysis with early studies of human intelligence, the fact that key variables in a statistical model are, on occasion, unobserved has been a point of lingering contention and controversy.The reader is assured, however, that a latent variable,defined in the broadest manner, is no more mysterious than an error term in a normal theory linear regression model or a random effect in a mixed model.
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Multiple Skills Underlie Arithmetic Performance: A Large-Scale Structural Equation Modeling Analysis
Directory of Open Access Journals (Sweden)
Sarit Ashkenazi
2017-12-01
Full Text Available Current theoretical approaches point to the importance of several cognitive skills not specific to mathematics for the etiology of mathematics disorders (MD. In the current study, we examined the role of many of these skills, specifically: rapid automatized naming, attention, reading, and visual perception, on mathematics performance among a large group of college students (N = 1,322 with a wide range of arithmetic proficiency. Using factor analysis, we discovered that our data clustered to four latent variables 1 mathematics, 2 perception speed, 3 attention and 4 reading. In subsequent structural equation modeling, we found that the latent variable perception speed had a strong and meaningful effect on mathematics performance. Moreover, sustained attention, independent from the effect of the latent variable perception speed, had a meaningful, direct effect on arithmetic fact retrieval and procedural knowledge. The latent variable reading had a modest effect on mathematics performance. Specifically, reading comprehension, independent from the effect of the latent variable reading, had a meaningful direct effect on mathematics, and particularly on number line knowledge. Attention, tested by the attention network test, had no effect on mathematics, reading or perception speed. These results indicate that multiple factors can affect mathematics performance supporting a heterogeneous approach to mathematics. These results have meaningful implications for the diagnosis and intervention of pure and comorbid learning disorders.
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Accounting for standard errors of vision-specific latent trait in regression models.
Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L
2014-07-11
To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits
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Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.
2006-01-01
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…
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International Nuclear Information System (INIS)
Utlu, Zafer; Aydın, Devrim; Kıncay, Olcay
2014-01-01
Highlights: • An experimental thermal investigation of hybrid renewable heating system is presented. • Analyses were done by using real data obtained from a prototype structure. • Exergy efficiency of system components investigated during discharging period are close to each other as 32%. • The average input energy and exergy rates to the LHS were 0.770 and 0.027 kW. • Overall total energy and exergy efficiencies of LHS calculated as 72% and 28.4%. - Abstract: In this study an experimental thermal investigation of hybrid renewable heating system is presented. Latent heat storage stores energy, gained by solar collectors and supplies medium temperature heat to heat pump both day time also night time while solar energy is unavailable. In addition to this an accumulation tank exists in the system as sensible heat storage. It provides supply–demand balance with storing excess high temperature heat. Analyses were done according to thermodynamic’s first and second laws by using real data obtained from a prototype structure, built as part of a project. Results show that high percent of heat loses took place in heat pump with 1.83 kW where accumulator-wall heating cycle followed it with 0.42 kW. Contrarily highest break-down of exergy loses occur accumulator-wall heating cycle with 0.28 kW. Averagely 2.42 kW exergy destruction took place in whole system during the experiment. Solar collectors and heat pump are the promising components in terms of exergy destruction with 1.15 kW and 1.09 kW respectively. Exergy efficiency of system components, investigated during discharging period are in a close approximately of 32%. However, efficiency of solar collectors and charging of latent heat storage are 2.3% and 7% which are relatively low. Average overall total energy and exergy efficiencies of latent heat storage calculated as 72% and 28.4% respectively. Discharging energy efficiency of latent heat storage is the highest through all system components. Also heat
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Hu, Hengrui; Allen, Peg; Yan, Yan; Reis, Rodrigo S; Jacob, Rebekah R; Brownson, Ross C
2018-05-30
Use of research evidence in public health decision making can be affected by organizational supports. Study objectives are to identify patterns of organizational supports and explore associations with research evidence use for job tasks among public health practitioners. In this longitudinal study, we used latent class analysis to identify organizational support patterns, followed by mixed logistic regression analysis to quantify associations with research evidence use. The setting included 12 state public health department chronic disease prevention units and their external partnering organizations involved in chronic disease prevention. Chronic disease prevention staff from 12 US state public health departments and partnering organizations completed self-report surveys at 2 time points, in 2014 and 2016 (N = 872). Latent class analysis was employed to identify subgroups of survey participants with distinct patterns of perceived organizational supports. Two classify-analyze approaches (maximum probability assignment and multiple pseudo-class draws) were used in 2017 to investigate the association between latent class membership and research evidence use. The optimal model identified 4 latent classes, labeled as "unsupportive workplace," "low agency leadership support," "high agency leadership support," and "supportive workplace." With maximum probability assignment, participants in "high agency leadership support" (odds ratio = 2.08; 95% CI, 1.35-3.23) and "supportive workplace" (odds ratio = 1.74; 95% CI, 1.10-2.74) were more likely to use research evidence in job tasks than "unsupportive workplace." The multiple pseudo-class draws produced comparable results with odds ratio = 2.09 (95% CI, 1.31-3.30) for "high agency leadership support" and odds ratio = 1.74 (95% CI, 1.07-2.82) for "supportive workplace." Findings suggest that leadership support may be a crucial element of organizational supports to encourage research evidence use. Organizational supports such
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Obesogenic family types identified through latent profile analysis.
Martinson, Brian C; VazquezBenitez, Gabriela; Patnode, Carrie D; Hearst, Mary O; Sherwood, Nancy E; Parker, Emily D; Sirard, John; Pasch, Keryn E; Lytle, Leslie
2011-10-01
Obesity may cluster in families due to shared physical and social environments. This study aims to identify family typologies of obesity risk based on family environments. Using 2007-2008 data from 706 parent/youth dyads in Minnesota, we applied latent profile analysis and general linear models to evaluate associations between family typologies and body mass index (BMI) of youth and parents. Three typologies described most families with 18.8% "Unenriched/Obesogenic," 16.9% "Risky Consumer," and 64.3% "Healthy Consumer/Salutogenic." After adjustment for demographic and socioeconomic factors, parent BMI and youth BMI Z-scores were higher in unenriched/obesogenic families (BMI difference = 2.7, p typology. In contrast, parent BMI and youth BMI Z-scores were similar in the risky consumer families relative to those in healthy consumer/salutogenic type. We can identify family types differing in obesity risks with implications for public health interventions.
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Haipeng Wang; Chengxiang Tang; Shichao Zhao; Qingyue Meng; Xiaoyun Liu
2017-01-01
Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis...
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Latent Factor Structure of DSM-5 Posttraumatic Stress Disorder
Gentes, Emily; Dennis, Paul A.; Kimbrel, Nathan A.; Kirby, Angela C.; Hair, Lauren P.; Beckham, Jean C.; Calhoun, Patrick S.
2015-01-01
The current study examined the latent factor structure of posttraumatic stress disorder (PTSD) based on DSM-5 criteria in a sample of participants (N = 374) recruited for studies on trauma and health. Confirmatory factor analyses (CFA) were used to compare the fit of the previous 3-factor DSM-IV model of PTSD to the 4-factor model specified in DSM-5 as well as to a competing 4-factor “dysphoria” model (Simms, Watson, & Doebbeling, 2002) and a 5-factor (Elhai et al., 2011) model of PTSD. Results indicated that the Elhai 5-factor model (re-experiencing, active avoidance, emotional numbing, dysphoric arousal, anxious arousal) provided the best fit to the data, although substantial support was demonstrated for the DSM-5 4-factor model. Low factor loadings were noted for two of the symptoms in the DSM-5 model (psychogenic amnesia and reckless/self-destructive behavior), which raises questions regarding the adequacy of fit of these symptoms with other core features of the disorder. Overall, the findings from the present research suggest the DSM-5 model of PTSD is a significant improvement over the previous DSM-IV model of PTSD. PMID:26366290
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Latent class factor and cluster models, bi-plots and tri-plots and related graphical displays
Magidson, J.; Vermunt, J.K.
2001-01-01
We propose an alternative method of conducting exploratory latent class analysis that utilizes latent class factor models, and compare it to the more traditional approach based on latent class cluster models. We show that when formulated in terms of R mutually independent, dichotomous latent
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Job satisfaction among Australian doctors: the use of latent class analysis.
Joyce, Catherine; Wang, Wei Chun
2015-10-01
To identify patterns of job satisfaction among Australian doctors using latent class analysis, and to determine the relationships of these patterns to personal and professional characteristics so as to improve satisfaction and minimize medical wastage. MABEL (Medicine in Australia: Balancing Employment and Life) data in 2011 were used. The study collected information on 5764 doctors about their job satisfaction, demographic characteristics, their health, country of medical training, opportunities for professional development and social interaction, taking time off work, views of patients' expectations, unpredictable working hours, hours worked per week, preference to reduce hours and intention to leave the medical workforce. Four latent classes of job satisfaction were identified: 5.8% had high job satisfaction; 19.4% had low satisfaction with working hours; 16.1% had high satisfaction with working hours but felt undervalued; and 6.5% had low job satisfaction. Low job satisfaction was associated with reporting poor health, having trained outside Australia, having poor opportunities for professional development and working longer hours. Low satisfaction was associated with a preference to reduce work hours and an intention to leave the medical workforce. To improve job satisfaction and minimize medical wastage, policies need to address needs of overseas trained doctors, provide continuing professional development and provide good health care for doctors. © The Author(s) 2015.
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Kanayama, Mieko; Suzuki, Machiko; Yuma, Yoshikazu
2016-01-01
The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. PMID:27366107
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Latent factors and route choice behaviour
DEFF Research Database (Denmark)
Prato, Carlo Giacomo
. A reliable dataset was prepared through measures of internal consistency and sampling adequacy, and data were analyzed with a proper application of factor analysis to the route choice context. For the dataset obtained from the survey, six latent constructs affecting driver behaviour were extracted and scores...... on each factor for each survey participant were calculated. Path generation algorithms were examined with respect to observed behaviour, through a measure of reproduction with deterministic techniques of the routes indicated in the answers to the survey. Results presented evidence that the majority...... and Link Nested Logit. Estimates were produced from model specifications that considered level-of-service, label and facility dummy variables. Moreover, a modelling framework was designed to represent drivers’ choices as affected by the latent constructs extracted with factor analysis. Previous experience...
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ltm: An R Package for Latent Variable Modeling and Item Response Analysis
Directory of Open Access Journals (Sweden)
Dimitris Rizopoulos
2006-11-01
Full Text Available The R package ltm has been developed for the analysis of multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach. For dichotomous data the Rasch, the Two-Parameter Logistic, and Birnbaum's Three-Parameter models have been implemented, whereas for polytomous data Semejima's Graded Response model is available. Parameter estimates are obtained under marginal maximum likelihood using the Gauss-Hermite quadrature rule. The capabilities and features of the package are illustrated using two real data examples.
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Latent profile analysis and comorbidity in a sample of individuals with compulsive buying disorder.
Mueller, Astrid; Mitchell, James E; Black, Donald W; Crosby, Ross D; Berg, Kelly; de Zwaan, Martina
2010-07-30
The aims of this study were to perform a latent profile analysis in a sample of individuals with compulsive buying, to explore the psychiatric comorbidity, and to examine whether or not more severe compulsive buying is associated with greater comorbidity. Compulsive buying measures and SCID data obtained from 171 patients with compulsive buying behavior who had participated in treatment trials at different clinical centers in the U.S. and Germany were analyzed. Latent profile analysis produced two clusters. Overall, cluster 2, included subjects with more severe compulsive buying, and was characterized by higher lifetime as well as current prevalence rates for Axis I and impulse control disorders. Nearly 90% of the total sample reported at least one lifetime Axis I diagnosis, particularly mood (74%) and anxiety (57%) disorders. Twenty-one percent had a comorbid impulse control disorder, most commonly intermittent explosive disorder (11%). Half of the sample presented with at least one current Axis I disorder, most commonly anxiety disorders (44%). Given the substantial psychiatric comorbidity, it is reasonable to question whether or not compulsive buying represents a distinct psychiatric entity vs. an epiphenomenon of other psychiatric disorders. Copyright 2010 Elsevier Ltd. All rights reserved.
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Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate
Directory of Open Access Journals (Sweden)
Yu-sheng Cheng
2014-01-01
Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.
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Using structural equation modeling for network meta-analysis.
Tu, Yu-Kang; Wu, Yun-Chun
2017-07-14
Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison
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Oral health status in older adults with social security in Mexico City: Latent class analysis.
Sánchez-García, Sergio; Heredia-Ponce, Erika; Cruz-Hervert, Pablo; Juárez-Cedillo, Teresa; Cárdenas-Bahena, Angel; García-Peña, Carmen
2014-02-01
To explore the oral health status through a latent class analysis in elderly social security beneficiaries from Southwest Mexico City. Cross-sectional study of beneficiaries of the State Employee Social Security and Social Services Institute (ISSSTE, in Spanish) and the Mexican Institute of Social Security (IMSS, in Spanish) aged 60 years or older. Oral health conditions such as edentulism, coronal and root caries (DMFT and DFT ≥ 75 percentile), clinical attachment loss (≥ 4 mm), and healthy teeth (≤ 25 percentile) were determined. A latent class analysis (LCA) was performed to classify the oral health status of dentate patients. In total, 336 patients were included (47.9% from the ISSSTE and 52.1% from the IMSS), with an average age of 74.4 (SD = 7.1) years. The 75th percentile of the DMFT = 23 and of the DFT = 2. Of the patients, 77.9% had periodontal disease. The 25th percentile of healthy teeth = 4. A three class model is adequate, with a high classification quality (Entropy = 0.915). The patients were classified as "Edentulous" (15.2%), "Class 1 = Unfavorable" (13.7%), "Class 2 = Somewhat favorable" (10.4%), and "Class 3 = Favorable" (60.7%). Using "Class 3 = Favorable" as a reference, there was an association (OR = 3.4; 95% CI = 1.8-6.4) between being edentulous and being 75 years of age and over, compared with the 60- to 74-year age group. The oral health in elderly social security beneficiaries is not optimal. The probability of becoming edentulous increases with age. A three-class model appropriately classifies the oral health dimensions in the elderly population. Key words:Elderly, Latent class analysis (LCA), oral health, social security, Mexico.
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A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.
2012-01-01
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
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A Non-Gaussian Spatial Generalized Linear Latent Variable Model
Irincheeva, Irina
2012-08-03
We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.
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Several
2007-01-01
Presentations and recorded keynotes at the 1st European Workshop on Latent Semantic Analysis in Technology-Enhanced Learning, March, 29-30, 2007. Heerlen, The Netherlands: The Open University of the Netherlands. Please see the conference website for more information:
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Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L
2014-06-01
Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.
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Latent profile analysis of neuropsychological measures to determine preschoolers' risk for ADHD.
Rajendran, Khushmand; O'Neill, Sarah; Marks, David J; Halperin, Jeffrey M
2015-09-01
Hyperactive/Inattentive preschool children show clear evidence of neuropsychological dysfunction. We examined whether patterns and severity of test scores could reliably identify subgroups of preschoolers with differential risk for ADHD during school-age. Typically developing (TD: n = 76) and Hyperactive/Inattentive (HI: n = 138) 3-4 year olds were assessed annually for 6 years (T1-T6). Latent profile analysis (LPA) was used to form subgroups among the HI group based on objective/neuropsychological measures (NEPSY, Actigraph and Continuous Performance Test). Logistic regression assessed the predictive validity of empirically formed subgroups at risk for ADHD diagnosis relative to the TD group and to each other from T2 to T6. Latent profile analysis yielded two subgroups of HI preschoolers: (a) selectively weak Attention/Executive functions, and (b) pervasive neuropsychological dysfunction across all measures. Both subgroups were more likely to have ADHD at all follow-up time-points relative to the TD group (OR range: 11.29-86.32), but there were no significant differences between the LPA-formed subgroups of HI children at any time-point. Objective/neuropsychological measures distinguish HI preschoolers from their TD peers, but patterns and severity of neuropsychological dysfunction do not predict risk for ADHD during school-age. We hypothesize that trajectories in at-risk children are influenced by subsequent environmental and neurodevelopmental factors, raising the possibility that they are amenable to early intervention. © 2015 Association for Child and Adolescent Mental Health.
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Tao, Chenyang; Nichols, Thomas E; Hua, Xue; Ching, Christopher R K; Rolls, Edmund T; Thompson, Paul M; Feng, Jianfeng
2017-01-01
We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. Copyright © 2016. Published by Elsevier Inc.
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Calculating latent frequencies of systems with local damping
International Nuclear Information System (INIS)
Kolonits, Ferenc
2005-01-01
Modal analysis of damped systems often cannot proceed with common real-eigenvalue techniques. The system of equilibrium equations leads to a matrix with elements being quadratic functions of a parameter λ. The values of that which make the matrix singular are the latent roots, while the solutions of the associated homogenous equation are the latent vectors. They are the (generally complex) characteristic frequencies and the mode shapes of the system, respectively. Although the theory is well developed, the numerical application is open to refinements yet. A reduction to better-known real-domain subtasks deserves attention. With a theorem of Popper and Gaspar, a n x n λ-matrix problem can be cut in two: into n-size asymmetric real matrices having as eigenvalues the n lower and n upper latent roots, ranked by absolute value. This approach may be of use for systems with high number of degrees of freedom while damped by a relatively few concentrated devices. It might fit also an earthquake analysis, where the lower portion of eigenvalues is customarily what counts. The dampers appear in the splitting algorithm as restricted-size modifications, ready for use by the Sherman-Morrison-Woodbury identity. The task is re-traced this way to a more usual real-asymmetric eigenproblem. A requirement of convergence is that the lower and upper n-set of latent values must be distinct. With odd-number degrees of freedom and neither over-damped, i.e. all latent roots being complex, this condition is surely violated. For such cases, a supplemental algorithm is proposed
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Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H.
2018-01-01
Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…
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Wang, Peng-Wei; Yen, Cheng-Fang
2017-12-08
Adolescent suicidal behavior may consist of different symptoms, including suicidal ideation, suicidal planning and suicidal attempts. Adolescent substance use behavior may contribute to adolescent suicidal behavior. However, research on the relationships between specific substance use and individual suicidal behavior is insufficient, as adolescents may not use only one substance or develop only one facet of suicidal behavior. Latent variables permit us to describe the relationships between clusters of related behaviors more accurately than studying the relationships between specific behaviors. Thus, the aim of this study was to explore how adolescent substance use behavior contributes to suicidal behavior using latent variables representing adolescent suicidal and substance use behaviors. A total of 13,985 adolescents were recruited using a stratified random sampling strategy. The participants indicated whether they had experienced suicidal ideation, planning and attempts and reported their cigarette, alcohol, ketamine and MDMA use during the past year. Latent analysis was used to examine the relationship between substance use and suicidal behavior. Adolescents who used any one of the above substances exhibited more suicidal behavior. The results of latent variables analysis revealed that adolescent substance use contributed to suicidal behavior and that boys exhibited more severe substance use behavior than girls. However, there was no gender difference in the association between substance use and suicidal behavior. Substance use behavior in adolescents is related to more suicidal behavior. In addition, the contribution of substance use to suicidal behavior does not differ between genders.
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Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.
Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip
2015-09-01
A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.
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Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.
2011-01-01
Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…
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Accuracy of latent-variable estimation in Bayesian semi-supervised learning.
Yamazaki, Keisuke
2015-09-01
Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Translating latent trends in food consumer behavior into new products
Gellynck, Xavier; Kühne, Bianka; Van Wezemael, Lynn; Verbeke, Wim
2010-01-01
For successful product development it is important to explore the latent changes in consumer behavior prior to the product development process. The identification of a latent trend before the manifestation moment can be achieved by trend analysis. Trend analysis delivers insights that explore the future in order to identify prospective consumers and new product ideas, but also includes a feeling for the currents in market and technology. Hence, the aim is to identify emerging weak signals in ...
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Litt, Mark D.; Kadden, Ronald M; Tennen, Howard
2012-01-01
The Coping Strategies Scale (CSS) was designed to assess adaptive changes in substance-use specific coping that result from treatment. The present study sought to examine the latent structure of the CSS in the hope that it might shed light on the coping processes of drug users, and guide the development of a brief version of the CSS. Respondents on the CSS were 751 men and women treated in three clinical trials for marijuana dependence. Posttreatment CSS data were analyzed to determine the nature of coping responses in patients who have been trained to use specific strategies to deal with substance use disorders. Exploratory factor analysis yielded two factors, categorized as problem-focused and emotion-focused coping, but confirmatory factor analysis did not support this structure. When infrequently endorsed items were removed, however, confirmatory factor analysis revealed a good fit to the data. Contrary to expectations, practical strategies that often form the basis for coping skills training, such as avoiding those who smoke, were not frequently endorsed. Problem focused items reflected cognitive commitments to change. Emotion-focused items included cognitive reinterpretations of emotions, to help manage emotional reactions. Brief versions of the CSS based on these factors showed good convergent and discriminant validity. The CSS, and the brief versions of the CSS, may prove useful in future treatment trials to evaluate effects of treatment on coping skills acquisition and utilization in substance dependent individuals. PMID:22082345
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Latent semantics of action verbs reflect phonetic parameters of intensity and emotional content
DEFF Research Database (Denmark)
Petersen, Michael Kai
2015-01-01
already in toddlers, this study explores whether articulatory and acoustic parameters may likewise differentiate the latent semantics of action verbs. Selecting 3 X 20 emotion, face, and hand related verbs known to activate premotor areas in the brain, their mutual cosine similarities were computed using...... latent semantic analysis LSA, and the resulting adjacency matrices were compared based on two different large scale text corpora; HAWIK and TASA. Applying hierarchical clustering to identify common structures across the two text corpora, the verbs largely divide into combined mouth and hand movements...... versus emotional expressions. Transforming the verbs into their constituent phonemes, and projecting them into an articulatory space framed by tongue height and formant frequencies, the clustered small and large size movements appear differentiated by front versus back vowels corresponding to increasing...
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Feingold, Alan; Tiberio, Stacey S; Capaldi, Deborah M
2014-03-01
Assessments of substance use behaviors often include categorical variables that are frequently related to other measures using logistic regression or chi-square analysis. When the categorical variable is latent (e.g., extracted from a latent class analysis [LCA]), classification of observations is often used to create an observed nominal variable from the latent one for use in a subsequent analysis. However, recent simulation studies have found that this classical 3-step analysis championed by the pioneers of LCA produces underestimates of the associations of latent classes with other variables. Two preferable but underused alternatives for examining such linkages-each of which is most appropriate under certain conditions-are (a) 3-step analysis, which corrects the underestimation bias of the classical approach, and (b) 1-step analysis. The purpose of this article is to dissuade researchers from conducting classical 3-step analysis and to promote the use of the 2 newer approaches that are described and compared. In addition, the applications of these newer models-for use when the independent, the dependent, or both categorical variables are latent-are illustrated through substantive analyses relating classes of substance abusers to classes of intimate partner aggressors.
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Han, Fang; Liu, Han
2017-02-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
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Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.
Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang
2018-03-12
Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.
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Rosellini, Anthony J.; Brown, Timothy A.
2011-01-01
The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of "DSM-IV" anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder…
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Directory of Open Access Journals (Sweden)
Michael D. Coovert
2017-08-01
Full Text Available Trust plays a central role in the effectiveness of work groups and teams. This is the case for both face-to-face and virtual teams. Yet little is known about the development of trust in virtual teams. We examined cognitive and affective trust and their relationship to team effectiveness as reflected through satisfaction with one’s team and task performance. Latent growth curve analysis reveals both trust types start at a significant level with individual differences in that initial level. Cognitive trust follows a linear growth pattern while affective trust is overall non-linear, but becomes linear once established. Latent change score models are utilized to examine change in trust and also its relationship with satisfaction with the team and team performance. In examining only change in trust and its relationship to satisfaction there appears to be a straightforward influence of trust on satisfaction and satisfaction on trust. However, when incorporated into a bivariate coupling latent change model the dynamics of the relationship are revealed. A similar pattern holds for trust and task performance; however, in the bivariate coupling change model a more parsimonious representation is preferred.
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Xu, Beijie; Recker, Mimi; Qi, Xiaojun; Flann, Nicholas; Ye, Lei
2013-01-01
This article examines clustering as an educational data mining method. In particular, two clustering algorithms, the widely used K-means and the model-based Latent Class Analysis, are compared, using usage data from an educational digital library service, the Instructional Architect (IA.usu.edu). Using a multi-faceted approach and multiple data…
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Temporal analysis of text data using latent variable models
DEFF Research Database (Denmark)
Mølgaard, Lasse Lohilahti; Larsen, Jan; Goutte, Cyril
2009-01-01
Detecting and tracking of temporal data is an important task in multiple applications. In this paper we study temporal text mining methods for Music Information Retrieval. We compare two ways of detecting the temporal latent semantics of a corpus extracted from Wikipedia, using a stepwise...
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Park, Jeong Mo; Han, Ae Kyung; Cho, Yoon Hee
2011-01-01
Purpose: The purpose of this study was to investigate the construct equivalence of the five general factors (subjective health, eating habits, physical activities, sedentary lifestyle, and sleeping behaviors) and to compare the latent means between male and female middle school students in Incheon, Korea. Methods: The 2008 Korean Youth Risk Behavior Survey data was used for analysis. Multigroup confirmatory factor analysis was performed to test whether the scale has configural, metric, and...
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Latent class analysis of diagnostic science assessment data using Bayesian networks
Steedle, Jeffrey Thomas
2008-10-01
Diagnostic science assessments seek to draw inferences about student understanding by eliciting evidence about the mental models that underlie students' reasoning about physical systems. Measurement techniques for analyzing data from such assessments embody one of two contrasting assessment programs: learning progressions and facet-based assessments. Learning progressions assume that students have coherent theories that they apply systematically across different problem contexts. In contrast, the facet approach makes no such assumption, so students should not be expected to reason systematically across different problem contexts. A systematic comparison of these two approaches is of great practical value to assessment programs such as the National Assessment of Educational Progress as they seek to incorporate small clusters of related items in their tests for the purpose of measuring depth of understanding. This dissertation describes an investigation comparing learning progression and facet models. Data comprised student responses to small clusters of multiple-choice diagnostic science items focusing on narrow aspects of understanding of Newtonian mechanics. Latent class analysis was employed using Bayesian networks in order to model the relationship between students' science understanding and item responses. Separate models reflecting the assumptions of the learning progression and facet approaches were fit to the data. The technical qualities of inferences about student understanding resulting from the two models were compared in order to determine if either modeling approach was more appropriate. Specifically, models were compared on model-data fit, diagnostic reliability, diagnostic certainty, and predictive accuracy. In addition, the effects of test length were evaluated for both models in order to inform the number of items required to obtain adequately reliable latent class diagnoses. Lastly, changes in student understanding over time were studied with a
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Öhlén, Joakim; Russell, Lara; Håkanson, Cecilia; Alvariza, Anette; Fürst, Carl Johan; Årestedt, Kristofer; Sawatzky, Richard
2017-01-01
Symptom relief is a key goal of palliative care. There is a need to consider complexities in symptom relief patterns for groups of people to understand and evaluate symptom relief as an indicator of quality of care at end of life. The aims of this study were to distinguish classes of patients who have different symptom relief patterns during the last week of life and to identify predictors of these classes in an adult register population. In a cross-sectional retrospective design, data were used from 87,026 decedents with expected deaths registered in the Swedish Register of Palliative Care in 2011 and 2012. Study variables were structured into patient characteristics, and processes and outcomes of quality of care. A latent class analysis was used to identify symptom relief patterns. Multivariate multinomial regression analyses were used to identify predictors of class membership. Five latent classes were generated: "relieved pain," "relieved pain and rattles," "relieved pain and anxiety," "partly relieved shortness of breath, rattles and anxiety," and "partly relieved pain, anxiety and confusion." Important predictors of class membership were age, sex, cause of death, and having someone present at death, individual prescriptions as needed (PRN) and expert consultations. Interindividual variability and complexity in symptom relief patterns may inform quality of care and its evaluation for dying people across care settings. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
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Havlicek, Judy
2014-01-01
Little is known about maltreatment among foster youth transitioning to adulthood. Multiple entries into out-of-home care and unsuccessful attempts at reunification may nevertheless reflect extended exposure to chronic maltreatment and multiple types of victimization. This study used administrative data from the Illinois Department of Children and Family Services to identify all unduplicated allegations of maltreatment in a cohort of 801 foster youth transitioning to adulthood in the state of Illinois. A latent variable modeling approach generated profiles of maltreatment based on substantiated and unsubstantiated reports of maltreatment taken from state administrative data. Four indicators of maltreatment were included in the latent class analysis: multiple types of maltreatment, predominant type of maltreatment, chronicity, and number of different perpetrators. The analysis identified four subpopulations of foster youth in relation to maltreatment. Study findings highlight the heterogeneity of maltreatment in the lives of foster youth transitioning to adulthood and draw attention to a need to raise awareness among service providers to screen for chronic maltreatment and multiple types of victimization. © The Author(s) 2014.
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Padmadas, SS; Dias, JG; Willekens, FJ
Objective To investigate the degree of individual heterogeneity related to complex dietary behaviour and to further examine the associations of different dietary compositions with selected characteristics. Design Latent class analysis was applied to data from the recent cross-sectional National
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Padmadas, S.; Dias, J.; Willekens, F.J.C.
2006-01-01
Objective To investigate the degree of individual heterogeneity related to complex dietary behaviour and to further examine the associations of different dietary compositions with selected characteristics. Design Latent class analysis was applied to data from the recent cross-sectional National
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Subgrouping of risky behaviors among Iranian college students: a latent class analysis
Directory of Open Access Journals (Sweden)
Safiri S
2016-07-01
Full Text Available Saeid Safiri,1,2 Afarin Rahimi-Movaghar,3 Masud Yunesian,4,5 Homayoun Sadeghi-Bazargani,6 Mansour Shamsipour,5 Mohammad Ali Mansournia,1 Akbar Fotouhi1 1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, 2Department of Public Health, School of Nursing and Midwifery, Maragheh University of Medical Sciences, Maragheh, 3Iranian National Center for Addiction Studies (INCAS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Sciences, Tehran, 4Department of Environmental Health Engineering, School of Public Health, 5Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, 6Road Traffic Injury Research Center, Department of Statistics & Epidemiology, Tabriz University of Medical Sciences, Tabriz, Iran Background: Risky behaviors may interrupt development or cause considerable morbidity or mortality. This study’s purpose was to determine subgroups of students based on risky behaviors and assess the prevalence of risky behaviors in each of the subgroups.Participants and methods: This anonymous cross-sectional study was carried out in October 2015 and November 2015, with 1,777 students from Tabriz University of Medical Sciences, through multistage random sampling method. The data were analyzed by latent class analysis.Results: The prevalence rates of cigarette smoking (more than or equal to ten cigarettes, hookah use (≥1 time/month, and alcohol consumption (≥1 time/month during the last year were 12.4% (95% confidence interval [CI]: 10.9–14.0, 11.6% (95% CI: 10.0–13.1, and 4.9% (95% CI: 3.8–5.9, respectively. The prevalence rates of illicit opioids (1.8%, 95% CI: 1.2–2.5, cannabis (1.2%, 95% CI: 0.7–1.7, methamphetamine (1.1%, 95% CI: 0.6–1.6, methylphenidate (2.5%, 95% CI: 1.7–3.2, and extramarital sex (5.5%, 95% CI: 4.5–6.6 over the last year were
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Influence of WFIKKN1 on BMP1-mediated activation of latent myostatin.
Szláma, György; Vásárhelyi, Viktor; Trexler, Mária; Patthy, László
2016-12-01
The NTR domain of WFIKKN1 protein has been shown to have significant affinity for the prodomain regions of promyostatin and latent myostatin but the biological significance of these interactions remained unclear. In view of its role as a myostatin antagonist, we tested the assumption that WFIKKN1 inhibits the release of myostatin from promyostatin and/or latent myostatin. WFIKKN1 was found to have no effect on processing of promyostatin by furin, the rate of cleavage of latent myostatin by BMP1, however, was significantly enhanced in the presence of WFIKKN1 and this enhancer activity was superstimulated by heparin. Unexpectedly, WFIKKN1 was also cleaved by BMP1 and our studies have shown that the KKN1 fragment generated by BMP1-cleavage of WFIKKN1 contributes most significantly to the observed enhancer activity. Analysis of a pro-TGF-β -based homology model of homodimeric latent myostatin revealed that the BMP1-cleavage sites are buried and not readily accessible to BMP1. In view of this observation, the most plausible explanation for the BMP1-enhancer activity of the KKN1 fragment is that it shifts a conformational equilibrium of latent myostatin from the closed circular structure of the homodimer to a more open form, making the cleavage sites more accessible to BMP1. On the other hand, the observation that the enhancer activity of KKN1 is superstimulated in the presence of heparin is explained by the fact KKN1, latent myostatin, and BMP1 have affinity for heparin and these interactions with heparin increase the local concentrations of the reactants thereby facilitating the action of BMP1. Furin: EC 3.4.21.75; BMP1, bone morphogentic protein 1 or procollagen C-endopeptidase: EC 3.4.24.19. © 2016 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.
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Interexaminer variation of minutia markup on latent fingerprints.
Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn
2016-07-01
Latent print examiners often differ in the number of minutiae they mark during analysis of a latent, and also during comparison of a latent with an exemplar. Differences in minutia counts understate interexaminer variability: examiners' markups may have similar minutia counts but differ greatly in which specific minutiae were marked. We assessed variability in minutia markup among 170 volunteer latent print examiners. Each provided detailed markup documenting their examinations of 22 latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. An average of 12 examiners marked each latent. The primary factors associated with minutia reproducibility were clarity, which regions of the prints examiners chose to mark, and agreement on value or comparison determinations. In clear areas (where the examiner was "certain of the location, presence, and absence of all minutiae"), median reproducibility was 82%; in unclear areas, median reproducibility was 46%. Differing interpretations regarding which regions should be marked (e.g., when there is ambiguity in the continuity of a print) contributed to variability in minutia markup: especially in unclear areas, marked minutiae were often far from the nearest minutia marked by a majority of examiners. Low reproducibility was also associated with differences in value or comparison determinations. Lack of standardization in minutia markup and unfamiliarity with test procedures presumably contribute to the variability we observed. We have identified factors accounting for interexaminer variability; implementing standards for detailed markup as part of documentation and focusing future training efforts on these factors may help to facilitate transparency and reduce subjectivity in the examination process. Published by Elsevier Ireland Ltd.
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Consumption Patterns of Nightlife Attendees in Munich: A Latent-Class Analysis.
Hannemann, Tessa-Virginia; Kraus, Ludwig; Piontek, Daniela
2017-09-19
The affinity for substance use among patrons of nightclubs has been well established. With novel psychoactive substances (NPS) quickly emerging on the European drug market, trends, and patterns of use are potentially changing. (1) The detection of subgroups of consumers in the electronic dance music scene of a major German metropolitan city, (2) describing the consumption patterns of these subgroups, (3) exploring the prevalence and type of NPS consumption in this population at nightlife events in Munich. A total of 1571 patrons answered questions regarding their own substance use and the emergence of NPS as well as their experience with these substances. A latent class analysis was employed to detect consumption patterns within the sample. A four class model was determined reflecting different consumption patterns: the conservative class (34.9%) whose substance was limited to cannabis; the traditional class (36.6%) which especially consumed traditional club drugs; the psychedelic class (17.5%) which, in addition to traditional club drugs also consumed psychedelic drugs; and an unselective class (10.9%) which displayed the greatest likelihood of consumption of all assessed drugs. "Smoking mixtures" and methylone were the new substances mentioned most often, the number of substances mentioned differed between latent classes. Specific strategies are needed to reduce harm in those displaying the riskiest substance use. Although NPS use is still a fringe phenomenon its prevalence is greater in this subpopulation than in the general population, especially among users in the high-risk unselective class.
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DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre
2005-01-01
parametric family ofdistributions. In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....
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Mediation Analysis in a Latent Growth Curve Modeling Framework
von Soest, Tilmann; Hagtvet, Knut A.
2011-01-01
This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…
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A Latent Class Regression Analysis of Men's Conformity to Masculine Norms and Psychological Distress
Wong, Y. Joel; Owen, Jesse; Shea, Munyi
2012-01-01
How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse…
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Lacourse, Eric; Baillargeon, Raymond; Dupere, Veronique; Vitaro, Frank; Romano, Elisa; Tremblay, Richard
2010-01-01
Background: Investigating the latent structure of conduct disorder (CD) can help clarify how symptoms related to aggression, property destruction, theft, and serious violations of rules cluster in individuals with this disorder. Discovering homogeneous subtypes can be useful for etiologic, treatment, and prevention purposes depending on the…
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Directory of Open Access Journals (Sweden)
Youngdeok Kim
2016-04-01
Full Text Available Background: Independent associations of physical activity (PA and sedentary behavior (SB with obesity are well documented. However, little is known about the combined associations of these behaviors with obesity in adolescents. The present study examines the prevalence of concurrent levels of PA and SB, and their associations with obesity among US adolescents. Methods: Data from a total of 12 081 adolescents who participated in the Youth Risk Behaviors Survey during 2012–2013 were analyzed. A latent class analysis was performed to identify latent subgroups with varying combined levels of subjectively measured PA and screen-based SB. Follow-up analysis examined the changes in the likelihood of being obese as determined by the Center for Disease Control and Prevention Growth Chart between latent subgroups. Results: Four latent subgroups with varying combined levels of PA and SB were identified across gender. The likelihood of being obese was significantly greater for the subgroups featuring either or both Low PA or High SB when compared with High PA/Low SB across genders (odds ratio [OR] ranges, 2.1–2.7 for males and 9.6–23.5 for females. Low PA/High SB showed the greater likelihood of being obese compared to subgroups featuring either or both High PA and Low SB (OR ranges, 2.2–23.5 for female adolescents only. Conclusions: The findings imply that promoting sufficient levels of PA while reducing SB should be encouraged in order to reduce obesity risk among adolescents, particularly for males. The risk of obesity for female adolescents can be reduced by engaging in either high levels of PA or low levels of SB.
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Kim, Youngdeok; Barreira, Tiago V; Kang, Minsoo
2016-01-01
Independent associations of physical activity (PA) and sedentary behavior (SB) with obesity are well documented. However, little is known about the combined associations of these behaviors with obesity in adolescents. The present study examines the prevalence of concurrent levels of PA and SB, and their associations with obesity among US adolescents. Data from a total of 12 081 adolescents who participated in the Youth Risk Behaviors Survey during 2012-2013 were analyzed. A latent class analysis was performed to identify latent subgroups with varying combined levels of subjectively measured PA and screen-based SB. Follow-up analysis examined the changes in the likelihood of being obese as determined by the Center for Disease Control and Prevention Growth Chart between latent subgroups. Four latent subgroups with varying combined levels of PA and SB were identified across gender. The likelihood of being obese was significantly greater for the subgroups featuring either or both Low PA or High SB when compared with High PA/Low SB across genders (odds ratio [OR] ranges, 2.1-2.7 for males and 9.6-23.5 for females). Low PA/High SB showed the greater likelihood of being obese compared to subgroups featuring either or both High PA and Low SB (OR ranges, 2.2-23.5) for female adolescents only. The findings imply that promoting sufficient levels of PA while reducing SB should be encouraged in order to reduce obesity risk among adolescents, particularly for males. The risk of obesity for female adolescents can be reduced by engaging in either high levels of PA or low levels of SB.
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Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap
Directory of Open Access Journals (Sweden)
Sukhjit Singh Sehra
2017-07-01
Full Text Available OpenStreetMap (OSM, based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007–2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research.
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Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
Syn, Wendy Tan Wei; How, Bong Chih; Atoum, Issa
2015-01-01
The paper describes a novel approach to categorize users' reviews according to the three Quality in Use (QU) indicators defined in ISO: effectiveness, efficiency and freedom from risk. With the tremendous amount of reviews published each day, there is a need to automatically summarize user reviews to inform us if any of the software able to meet requirement of a company according to the quality requirements. We implemented the method of Latent Semantic Analysis (LSA) and its subspace to predi...
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Phelan, Julia; Ing, Marsha; Nylund-Gibson, Karen; Brown, Richard S.
2017-01-01
This study extends current research by organizing information about students' expectancy-value achievement motivation, in a way that helps parents and teachers identify specific entry points to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task…
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Paas, L.J.; Bijmolt, T.H.A.; Vermunt, J.K.
2004-01-01
A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent
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How to get rid of W: a latent variables approach to modelling spatially lagged variables
Folmer, H.; Oud, J.
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
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How to get rid of W : a latent variables approach to modelling spatially lagged variables
Folmer, Henk; Oud, Johan
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
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Lam, Shui-fong; Law, Wilbert; Chan, Chi-Keung; Wong, Bernard P. H.; Zhang, Xiao
2015-01-01
The contribution of social context to school bullying was examined from the self-determination theory perspective in this longitudinal study of 536 adolescents from 3 secondary schools in Hong Kong. Latent class growth analysis of the student-reported data at 5 time points from grade 7 to grade 9 identified 4 groups of students: bullies (9.8%),…
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Latent Fundamentals Arbitrage with a Mixed Effects Factor Model
Directory of Open Access Journals (Sweden)
Andrei Salem Gonçalves
2012-09-01
Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.
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Toward a quantitative typology of burglars: a latent profile analysis of career offenders.
Vaughn, Michael G; DeLisi, Matt; Beaver, Kevin M; Howard, Matthew O
2008-11-01
Burglary is a serious, costly, and prevalent crime but prior typologies of burglars are mostly speculative and based on qualitative data. Using a sample of 456 adult career criminals, the current study used latent profile analysis to construct a methodologically rigorous quantitative typology. Four classes of burglars emerged: young versatile, vagrant, drug-oriented, and sexual predators. All groups demonstrated significant involvement in varied forms of crime, but the sexual predator group was the most violent and had the most serious criminal careers. Connections to the criminal career literature are offered and suggestions for further empirical study of offender typologies are discussed.
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Primiparous women's preferences for care during a prolonged latent phase of labour.
Ängeby, Karin; Wilde-Larsson, Bodil; Hildingsson, Ingegerd; Sandin-Bojö, Ann-Kristin
2015-10-01
To investigate primiparous women's preferences for care during a prolonged latent phase of labour. A qualitative study based on focus groups and individual interviews and analysed with inductive content analysis. Sixteen primiparous women with a prolonged latent phase of labour >18 hours were interviewed in five focus groups (n = 11) or individually (n = 5). One main category emerged "Beyond normality - a need of individual adapted guidance in order to understand and manage an extended latent phase of labour" which covers the women's preferences during the prolonged latent phase. Five categories were generated from the data: "A welcoming manner and not being rejected", "Individually adapted care", "Important information which prepares for reality and coping", "Participation and need for feedback" and "Staying nearby the labour ward or being admitted for midwifery support". Women with a prolonged latent phase of labour sought to use their own resources, but their needs for professional support increased as time passed. A welcoming attitude from an available midwife during the latent phase created a feeling of security, and personally adapted care was perceived positively. Women with a prolonged latent phase of labour preferred woman-centred care. Midwives play an important role in supporting these women. Women's need for midwifery-support increases as the time spent in latent phase increases. Copyright © 2015 Elsevier B.V. All rights reserved.
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Molgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner; Kent, Peter; Kongsted, Alice
2017-08-09
Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and
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DEFF Research Database (Denmark)
Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena
2014-01-01
-related job advertisements in order to develop a typology of BPM professionals. This empirical analysis reveals distinct ideal types and profiles of BPM professionals on several levels of abstraction. A closer look at these ideal types and profiles confirms that BPM is a boundary-spanning field that requires......While researchers have analysed the organisational competences that are required for successful Business Process Management (BPM) initiatives, individual BPM competences have not yet been studied in detail. In this study, latent semantic analysis is used to examine a collection of 1507 BPM...
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Building latent class trees, with an application to a study of social capital
van den Bergh, M.; Schmittmann, V.D.; Vermunt, J.K.
2017-01-01
Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical variables. However, especially when the number of classes required to obtain a good fit is large, interpretation of the latent classes may not be straightforward. To overcome this problem, we propose an
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A Latent Profile Analysis of Latino Parenting: The Infusion of Cultural Values on Family Conflict
Ayón, Cecilia; Williams, Lela Rankin; Marsiglia, Flavio F.; Ayers, Stephanie; Kiehne, Elizabeth
2015-01-01
The purpose of the present study was to (a) examine how acculturation and social support inform Latinos’ parenting behaviors, controlling for gender and education; (b) describe parenting styles among Latino immigrants while accounting for cultural elements; and (c) test how these parenting styles are associated with family conflict. A 3 step latent profile analysis with the sample (N = 489) revealed best fit with a 4 profile model (n = 410) of parenting: family parenting (n = 268, 65%), child...
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Francese, S; Bradshaw, R; Ferguson, L S; Wolstenholme, R; Clench, M R; Bleay, S
2013-08-07
After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable.
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Mertens, Lieze; Van Cauwenberg, Jelle; Ghekiere, Ariane; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Van de Weghe, Nico; Van Dyck, Delfien
2016-08-12
Increasing cycling for transport can contribute to improve public health among adults. Micro-environmental factors (i.e. small-scaled street-setting features) may play an important role in affecting the street's appeal to cycle for transport. Understanding about the interplay between individuals and their physical environment is important to establish tailored environmental interventions. Therefore, the current study aimed to examine whether specific subgroups exist based on similarities in micro-environmental preferences to cycle for transport. Responses of 1950 middle-aged adults (45-65 years) on a series of choice tasks depicting potential cycling routes with manipulated photographs yielded three subgroups with different micro-environmental preferences using latent class analysis. Although latent class analysis revealed three different subgroups in the middle-aged adult population based on their environmental preferences, results indicated that cycle path type (i.e. a good separated cycle path) is the most important environmental factor for all participants and certainly for individuals who did not cycle for transport. Furthermore, only negligible differences were found between the importances of the other micro-environmental factors (i.e. traffic density, evenness of the cycle path, maintenance, vegetation and speed limits) regarding the two at risk subgroups and that providing a speed bump obviously has the least impact on the street's appeal to cycle for transport. Results from the current study indicate that only negligible differences were found between the three subgroups. Therefore, it might be suggested that tailored environmental interventions are not required in this research context.
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Original article Latent classes of criminal intent associated with criminal behaviour
Directory of Open Access Journals (Sweden)
Daniel Boduszek
2014-07-01
Full Text Available Background This study aimed to examine the number of latent classes of criminal intent that exist among prisoners and to look at the associations with recidivism, number of police arrests, type of offending (robbery, violent offences, murder, and multiple offences, and age. Participants and procedure Latent class analysis was used to identify homogeneous subgroups of prisoners based on their responses to the 10 questions reflecting criminal intent. Participants were 309 male recidivistic prisoners incarcerated in a maximum security prison. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the association between recidivism and latent classes of criminal intent while controlling for offence type (robbery, violent offences, murder, and multiple offences, number of arrests, and age. Results The best fitting latent class model was a three-class solution: ‘High criminal intent’ (49.3%, ‘Intermediate criminal intent’ (41.3%, and ‘Low criminal intent’ (9.4%. The latent classes were differentially related to the external variables (recidivism, violent offences, and age. Conclusions Criminal intent is best explained by three homogeneous classes that appear to represent an underlying continuum. Future work is needed to identify whether these distinct classes of criminal intent may predict engagement in various types of criminal behaviour.
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Māori identity signatures: A latent profile analysis of the types of Māori identity.
Greaves, Lara M; Houkamau, Carla; Sibley, Chris G
2015-10-01
Māori are the indigenous peoples of New Zealand. However, the term 'Māori' can refer to a wide range of people of varying ethnic compositions and cultural identity. We present a statistical model identifying 6 distinct types, or 'Māori Identity Signatures,' and estimate their proportion in the Māori population. The model is tested using a Latent Profile Analysis of a national probability sample of 686 Māori drawn from the New Zealand Attitudes and Values Study. We identify 6 distinct signatures: Traditional Essentialists (22.6%), Traditional Inclusives (16%), High Moderates (31.7%), Low Moderates (18.7%), Spiritually Orientated (4.1%), and Disassociated (6.9%). These distinct Identity Signatures predicted variation in deprivation, age, mixed-ethnic affiliation, and religion. This research presents the first formal statistical model assessing how people's identity as Māori is psychologically structured, documents the relative proportion of these different patterns of structures, and shows that these patterns reliably predict differences in core demographics. We identify a range of patterns of Māori identity far more diverse than has been previously proposed based on qualitative data, and also show that the majority of Māori fit a moderate or traditional identity pattern. The application of our model for studying Māori health and identity development is discussed. (c) 2015 APA, all rights reserved).
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Luciano, Juan V; Forero, Carlos G; Cerdà-Lafont, Marta; Peñarrubia-María, María Teresa; Fernández-Vergel, Rita; Cuesta-Vargas, Antonio I; Ruíz, José M; Rozadilla-Sacanell, Antoni; Sirvent-Alierta, Elena; Santo-Panero, Pilar; García-Campayo, Javier; Serrano-Blanco, Antoni; Pérez-Aranda, Adrián; Rubio-Valera, María
2016-10-01
Although fibromyalgia syndrome (FM) is considered a heterogeneous condition, there is no generally accepted subgroup typology. We used hierarchical cluster analysis and latent profile analysis to replicate Giesecke's classification in Spanish FM patients. The second aim was to examine whether the subgroups differed in sociodemographic characteristics, functional status, quality of life, and in direct and indirect costs. A total of 160 FM patients completed the following measures for cluster derivation: the Center for Epidemiological Studies-Depression Scale, the Trait Anxiety Inventory, the Pain Catastrophizing Scale, and the Control over Pain subscale. Pain threshold was measured with a sphygmomanometer. In addition, the Fibromyalgia Impact Questionnaire-Revised, the EuroQoL-5D-3L, and the Client Service Receipt Inventory were administered for cluster validation. Two distinct clusters were identified using hierarchical cluster analysis ("hypersensitive" group, 69.8% and "functional" group, 30.2%). In contrast, the latent profile analysis goodness-of-fit indices supported the existence of 3 FM patient profiles: (1) a "functional" profile (28.1%) defined as moderate tenderness, distress, and pain catastrophizing; (2) a "dysfunctional" profile (45.6%) defined by elevated tenderness, distress, and pain catastrophizing; and (3) a "highly dysfunctional and distressed" profile (26.3%) characterized by elevated tenderness and extremely high distress and catastrophizing. We did not find significant differences in sociodemographic characteristics between the 2 clusters or among the 3 profiles. The functional profile was associated with less impairment, greater quality of life, and lower health care costs. We identified 3 distinct profiles which accounted for the heterogeneity of FM patients. Our findings might help to design tailored interventions for FM patients.
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Fitzgerald, Joseph M; Broadbridge, Carissa L
2013-01-01
Many researchers employ single-item scales of subjective experiences such as imagery and confidence to assess autobiographical memory. We tested the hypothesis that four latent constructs, recollection, belief, impact, and rehearsal, account for the variance in commonly used scales across four different types of autobiographical memory: earliest childhood memory, cue word memory of personal experience, highly vivid memory, and most stressful memory. Participants rated each memory on scales hypothesised to be indicators of one of four latent constructs. Multi-group confirmatory factor analyses and structural analyses confirmed the similarity of the latent constructs of recollection, belief, impact, and rehearsal, as well as the similarity of the structural relationships among those constructs across memory type. The observed pattern of mean differences between the varieties of autobiographical experiences was consistent with prior research and theory in the study of autobiographical memory.
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Latent class analysis of early developmental trajectory in baby siblings of children with autism.
Landa, Rebecca J; Gross, Alden L; Stuart, Elizabeth A; Bauman, Margaret
2012-09-01
Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Sibs-A (N = 204) were assessed with the Mullen Scales of Early Learning from age 6 to 36 months. Mullen T scores served as dependent variables. Outcome classifications at age 36 months included: ASD (N = 52); non-ASD social/communication delay (broader autism phenotype; BAP; N = 31); and unaffected (N = 121). Child-specific patterns of performance were studied using latent class growth analysis. Latent class membership was then related to diagnostic outcome through estimation of within-class proportions of children assigned to each diagnostic classification. A 4-class model was favored. Class 1 represented accelerated development and consisted of 25.7% of the sample, primarily unaffected children. Class 2 (40.0% of the sample), was characterized by normative development with above-average nonverbal cognitive outcome. Class 3 (22.3% of the sample) was characterized by receptive language, and gross and fine motor delay. Class 4 (12.0% of the sample), was characterized by widespread delayed skill acquisition, reflected by declining trajectories. Children with an outcome diagnosis of ASD were spread across Classes 2, 3, and 4. Results support a category of ASD that involves slowing in early non-social development. Receptive language and motor development is vulnerable to early delay in sibs-A with and without ASD outcomes. Non-ASD sibs-A are largely distributed across classes depicting average or accelerated development. Developmental trajectories of motor, language, and cognition appear independent of communication and social delays in non-ASD sibs-A. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.
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A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis
Directory of Open Access Journals (Sweden)
Fei Chen
2003-01-01
Full Text Available DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT – the bionic wavelet transform (BWT – for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each channel to maximise the useful energy distribution of the whole BWT output. The performance of the proposed BWT was examined by analysing synthetic and real DNA sequences. Results show that BWT performs better than traditional WT in presenting greater energy distribution. This new BWT method should be useful for the detection of the latent structural features in future DNA sequence analysis.
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Directory of Open Access Journals (Sweden)
Hyosun Jang
2018-01-01
Full Text Available Radiation-induced skin injury can take the form of serious cutaneous damage and have specific characteristics. Asymptomatic periods are classified as the latent stage. The skin barrier plays a critical role in the modulation of skin permeability and hydration and protects the body against a harsh external environment. However, an analysis on skin barrier dysfunction against radiation exposure in the latent stage has not been conducted. Thus, we investigated whether the skin barrier is impaired by irradiation in the latent stage and aimed to identify the molecules involved in skin barrier dysfunction. We analyzed skin barrier function and its components in SKH1 mice that received 20 and 40 Gy local irradiation. Increased transepidermal water loss and skin pH were observed in the latent stage of the irradiated skin. Skin barrier components, such as structural proteins and lipid synthesis enzymes in keratinocyte, increased in the irradiated group. Interestingly, we noted sebaceous gland atrophy and increased serine protease and inflammatory cytokines in the irradiated skin during the latent period. This finding indicates that the main factor of skin barrier dysfunction in the latent stage of radiation-induced skin injury is sebaceous gland deficiency, which could be an intervention target for skin barrier impairment.
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Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.
Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E
2018-03-01
Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.
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Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data
Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.
2017-01-01
Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564
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Directory of Open Access Journals (Sweden)
Kobto G Koura
Full Text Available BACKGROUND: Anaemia during pregnancy and at delivery is an important public health problem in low- and middle-income countries. Its association with the children's haemoglobin level over time remains unclear. Our goals were to identify distinct haemoglobin level trajectories using latent class analysis and to assess the association between these trajectories and maternal anaemia and other risk factors. METHOD: A prospective study of children from birth to 18 months of life was conducted in a rural setting in Tori-Bossito, Benin. The main outcome measure was the haemoglobin levels repeatedly measured at 3, 6, 9, 12, 15 and 18 months. Variables were collected from the mothers at delivery and from their children at birth and during the follow-up. The analyses were performed by means of Latent Class Analysis which has never been used for this kind of data. All the analyses were performed with Stata software, version 11.0, using the generalized linear latent and mixed model (GLLAMM framework. RESULTS: We showed that 33.7% of children followed a low haemoglobin trajectory and 66.3% a high trajectory during the first 18 months of life. Newborn anaemia, placental malaria, malaria attack, sickle cell trait and male gender were significantly associated with a lower children's haemoglobin level over time, whereas maternal age, children living in a polygamous family and with good feeding practices had a higher Hb level in the first18 months. We also showed that maternal anaemia was a predictor for 'low haemoglobin level trajectory' group membership but have no significant effect on children haemoglobin level over time. CONCLUSION: Latent Class Analyses framework seems well suited to analyse longitudinal data under the hypothesis that different subpopulations of subjects are present in the data, each with its own set of parameters, with distinctive evolutions that themselves may reflect distinctive aetiologies.
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Stronge, Sam; Cichocka, Aleksandra; Sibley, Chris G.
2016-01-01
Research into the relationship between self-esteem and narcissism has produced conflicting results, potentially caused by hidden subpopulations that exhibit distinct positive or negative associations. This research uses Latent Profile Analysis to identify profiles within a national panel study (N = 6,471) with differing relationships between psychological entitlement and self-esteem. We identified a narcissistic self-esteem profile (9%) characterised by high entitlement and high self-esteem, ...
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Are depression and frailty overlapping syndromes in mid- and late-life? A latent variable analysis.
Mezuk, Briana; Lohman, Matthew; Dumenci, Levent; Lapane, Kate L
2013-06-01
Depression and frailty both predict disability and morbidity in later life. However, it is unclear to what extent these common geriatric syndromes represent overlapping constructs. To examine the joint relationship between the constructs of depression and frailty. Data come from 2004-2005 wave of the Baltimore Epidemiologic Catchment Area Study, and the analysis is limited to participants 40 years and older, with complete data on frailty and depression indicators (N = 683). Depression was measured using the Diagnostic Interview Schedule, and frailty was indexed by modified Fried criteria. A series of confirmatory latent class analyses were used to assess the degree to which depression and frailty syndromes identify the same populations. A latent kappa coefficient (κl) was also estimated between the constructs. Confirmatory latent class analyses indicated that depression and frailty represent distinct syndromes rather than a single construct. The joint modeling of the two constructs supported a three-class solution for depression and two-class solution for frailty, with 2.9% categorized as severely depressed, 19.4% as mildly depressed, and 77.7% as not depressed, and 21.1% categorized as frail and 78.9% as not frail. The chance-corrected agreement statistic indicated moderate correspondence between the depression and frailty constructs (κl: 66, 95% confidence interval: 0.58-0.74). Results suggest that depression and frailty are interrelated concepts, yet their operational criteria identify substantively overlapping subpopulations. These findings have implications for understanding factors that contribute to the etiology and prognosis of depression and frailty in later life. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Lieze Mertens
2016-08-01
Full Text Available Abstract Background Increasing cycling for transport can contribute to improve public health among adults. Micro-environmental factors (i.e. small-scaled street-setting features may play an important role in affecting the street’s appeal to cycle for transport. Understanding about the interplay between individuals and their physical environment is important to establish tailored environmental interventions. Therefore, the current study aimed to examine whether specific subgroups exist based on similarities in micro-environmental preferences to cycle for transport. Methods Responses of 1950 middle-aged adults (45–65 years on a series of choice tasks depicting potential cycling routes with manipulated photographs yielded three subgroups with different micro-environmental preferences using latent class analysis. Results Although latent class analysis revealed three different subgroups in the middle-aged adult population based on their environmental preferences, results indicated that cycle path type (i.e. a good separated cycle path is the most important environmental factor for all participants and certainly for individuals who did not cycle for transport. Furthermore, only negligible differences were found between the importances of the other micro-environmental factors (i.e. traffic density, evenness of the cycle path, maintenance, vegetation and speed limits regarding the two at risk subgroups and that providing a speed bump obviously has the least impact on the street’s appeal to cycle for transport. Conclusions Results from the current study indicate that only negligible differences were found between the three subgroups. Therefore, it might be suggested that tailored environmental interventions are not required in this research context.
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Hole, Arne Risa; Norman, Richard; Viney, Rosalie
2016-02-01
Not accounting for simplifying decision-making heuristics when modelling data from discrete choice experiments has been shown potentially to lead to biased inferences. This study considers two ways of exploring the presence of attribute non-attendance (that is, respondents considering only a subset of the attributes that define the choice options) in a health state valuation discrete choice experiment. The methods used include the latent class (LC) and endogenous attribute attendance (EAA) models, which both required adjustment to reflect the structure of the quality-adjusted life year (QALY) framework for valuing health outcomes. We find that explicit consideration of attendance patterns substantially improves model fit. The impact of allowing for non-attendance on the estimated QALY weights is dependent on the assumed source of non-attendance. If non-attendance is interpreted as a form of preference heterogeneity, then the inferences from the LC and EAA models are similar to those from standard models, while if respondents ignore attributes to simplify the choice task, the QALY weights differ from those using the standard approach. Because the cause of non-attendance is unknown in the absence of additional data, a policymaker may use the range of weights implied by the two approaches to conduct a sensitivity analysis. Copyright © 2014 John Wiley & Sons, Ltd.
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Examining the Latent Structure of the Delis-Kaplan Executive Function System.
Karr, Justin E; Hofer, Scott M; Iverson, Grant L; Garcia-Barrera, Mauricio A
2018-05-04
The current study aimed to determine whether the Delis-Kaplan Executive Function System (D-KEFS) taps into three executive function factors (inhibition, shifting, fluency) and to assess the relationship between these factors and tests of executive-related constructs less often measured in latent variable research: reasoning, abstraction, and problem solving. Participants included 425 adults from the D-KEFS standardization sample (20-49 years old; 50.1% female; 70.1% White). Eight alternative measurement models were compared based on model fit, with test scores assigned a priori to three factors: inhibition (Color-Word Interference, Tower), shifting (Trail Making, Sorting, Design Fluency), and fluency (Verbal/Design Fluency). The Twenty Questions, Word Context, and Proverb Tests were predicted in separate structural models. The three-factor model fit the data well (CFI = 0.938; RMSEA = 0.047), although a two-factor model, with shifting and fluency merged, fit similarly well (CFI = 0.929; RMSEA = 0.048). A bifactor model fit best (CFI = 0.977; RMSEA = 0.032) and explained the most variance in shifting indicators, but rarely converged among 5,000 bootstrapped samples. When the three first-order factors simultaneously predicted the criterion variables, only shifting was uniquely predictive (p measuring executive-related constructs and provide a framework through which clinicians can interpret D-KEFS results.
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International Nuclear Information System (INIS)
Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan
2009-01-01
In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks
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Zhang, Bo; Chen, Zhen; Albert, Paul S
2012-01-01
High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.
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International Nuclear Information System (INIS)
Li, Rui; Min, Qilong; Wu, Xiaoqing; Fu, Yunfei
2013-01-01
An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages between observed cloud and precipitation profiles to the major processes of phase change of atmospheric water. Specifically, rain is segregated into three rain types: warm, convective, and stratiform rain, based on their dynamical and thermodynamical characteristics. As the second of series, both convective and stratiform rain LH algorithms are presented and evaluated here. For convective and stratiform rain, the major LH-related microphysical processes including condensation, deposition, evaporation, sublimation, and freezing–melting are parameterized with the aid of Cloud Resolving Model (CRM) simulations. The condensation and deposition processes are parameterized in terms of rain formation processes through the precipitation formation theory. LH associated with the freezing–melting process is relatively small and is assumed to be a fraction of total condensation and deposition LH. The evaporation and sublimation processes are parameterized for three unsaturated scenarios: rain out of the cloud body, clouds at cloud boundary and clouds and rain in downdraft region. The evaluation or self-consistency test indicates the retrievals capture the major features of LH profiles and reproduce the double peaks at right altitudes. The LH products are applicable at various stages of cloud system life cycle for high-resolution models, as well as for large-scale climate models. -- Highlights: ► An exploratory study on physics-based cold rain latent heat retrieval algorithm. ► Utilize the full information of the vertical structures of cloud and rainfall. ► Include all major LH-related microphysical processes (in ice and liquid phase). ► Directly link water mass measurements to latent heat at instantaneous pixel level. ► Applicable at various stages of cloud system life cycle
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Large-scale weakly supervised object localization via latent category learning.
Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve
2015-04-01
Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.
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Cheng, Qiang; Hsu, Hsien-Yuan
2017-01-01
Using Trends in International Mathematics and Science Study (TIMSS) 2011 eighth-grade international dataset, this study explored the profiles of instructional practices reported by high- and low-performing mathematics teachers across the US, Finland, Korea, and Russia. Concepts of conceptual teaching and procedural teaching were used to frame the design of the current study. Latent cluster analysis was applied in the investigation of the profiles of mathematics teachers’ instructional practic...
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Transcriptional regulation of latent feline immunodeficiency virus in peripheral CD4+ T-lymphocytes.
McDonnel, Samantha J; Sparger, Ellen E; Luciw, Paul A; Murphy, Brian G
2012-05-01
Feline immunodeficiency virus (FIV), the lentivirus of domestic cats responsible for feline AIDS, establishes a latent infection in peripheral blood CD4+ T-cells approximately eight months after experimental inoculation. In this study, cats experimentally infected with the FIV-C strain in the asymptomatic phase demonstrated an estimated viral load of 1 infected cell per approximately 10(3) CD4+ T-cells, with about 1 copy of viral DNA per cell. Approximately 1 in 10 proviral copies was capable of transcription in the asymptomatic phase. The latent FIV proviral promoter was associated with deacetylated, methylated histones, which is consistent with a condensed chromatin structure. In contrast, the transcriptionally active FIV promoter was associated with histone acetylation and demethylation. In addition, RNA polymerase II appeared to be paused on the latent viral promoter, and short promoter-proximal transcripts were detected. Our findings for the FIV promoter in infected cats are similar to results obtained in studies of human immunodeficiency virus (HIV)-1 latent proviruses in cell culture in vitro studies. Thus, the FIV/cat model may offer insights into in vivo mechanisms of HIV latency and provides a unique opportunity to test novel therapeutic interventions aimed at eradicating latent virus.
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Substantiation for Approaches to Treatment of Latent Autoimmune Diabetes in Adults
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T.M. Tykhonova
2014-10-01
Conclusions. Analysis of carbohydrate metabolism on the manifestation stage and over time development of latent autoimmune diabetes in adults as well as reduction of β-cells insulin-producing function associated with autoimmune insulitis and progressing while the development of this form of disease, substantiate the rational for insulin administration as this form of diabetes has been diagnosed. If patients with latent autoimmune diabetes in adults have metabolic syndrome clusters it is quite reasonable to add metformin to insulin.
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Directory of Open Access Journals (Sweden)
Tovilović Snežana
2004-01-01
Full Text Available The research which was realized belongs to one of three research fields within framework of rational-emotional-behavioral therapy (REBT - to the theory of emotional disorders. It was undertaken with the aim to establish presence and nature of relations between social anxiety, treated as dimension and the construct of irrational beliefs from REBT theory. The research was carried out on the sample of 261 students of Novi Sad University, both genders, age 18 to 26. First of all, the latent structure of newly constructed Scale of Social Anxiety (SA of the author Tovilović S. was tested. SA scale was proved to be of satisfying reliability (α =0.92. Principal-component factor analysis was conducted under gathered data. Four factors of social anxiety, which explain 44,09% of total variance of the items of SA scale, were named: social-evaluation anxiety, inhibition in social-uncertain situations, low self-respect and hypersensitivity on rejection. The other test that was used is Scale of General Attitudes and Beliefs of the author Marić Z. Reliability of the sub-scale of irrational beliefs that was got on our sample is α =0.91 yet the subscale of rational beliefs is α =0.70. Canonical correlational analysis was conducted under manifest variables of both scales. Three pairs of statistically significant canonical factors were got, with correlations within the span between Rc=0.78 and Rc=0.64. We discussed nature of correlation between social anxiety and irrational beliefs in the light of REBT model of social phobia, REBT theory of emotional disorder, researches and model of social anxiety in wider, cognitive-behavioral framework.
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Preparation of fine powdered composite for latent heat storage
Energy Technology Data Exchange (ETDEWEB)
Fořt, Jan, E-mail: jan.fort.1@fsv.cvut.cz; Trník, Anton, E-mail: anton.trnik@fsv.cvut.cz; Pavlíková, Milena, E-mail: milena.pavlikova@fsv.cvut.cz; Pavlík, Zbyšek, E-mail: pavlikz@fsv.cvut.cz [Department of Materials Engineering and Chemistry, Faculty of Civil Engineering, Czech Technical University in Prague, Thákurova 7, 166 29 Prague (Czech Republic); Pomaleski, Marina, E-mail: marina-pomaleski@fsv.cvut.cz [Faculty of Civil Engineering, Architecture and Urbanism, University of Campinas, R. Saturnino de Brito 224, 13083-889 Campinas – SP (Brazil)
2016-07-07
Application of latent heat storage building envelope systems using phase-change materials represents an attractive method of storing thermal energy and has the advantages of high-energy storage density and the isothermal nature of the storage process. This study deals with a preparation of a new type of powdered phase change composite material for thermal energy storage. The idea of a composite is based upon the impregnation of a natural silicate material by a reasonably priced commercially produced pure phase change material and forming the homogenous composite powdered structure. For the preparation of the composite, vacuum impregnation method is used. The particle size distribution accessed by the laser diffraction apparatus proves that incorporation of the organic phase change material into the structure of inorganic siliceous pozzolana does not lead to the clustering of the particles. The compatibility of the prepared composite is characterized by the Fourier transformation infrared analysis (FTIR). Performed DSC analysis shows potential of the developed composite for thermal energy storage that can be easily incorporated into the cement-based matrix of building materials. Based on the obtained results, application of the developed phase change composite can be considered with a great promise.
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Directory of Open Access Journals (Sweden)
Dirk Temme
2008-12-01
Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.
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Automatic Evaluation for E-Learning Using Latent Semantic Analysis: A Use Case
Directory of Open Access Journals (Sweden)
Mireia Farrús
2013-03-01
Full Text Available Assessment in education allows for obtaining, organizing, and presenting information about how much and how well the student is learning. The current paper aims at analysing and discussing some of the most state-of-the-art assessment systems in education. Later, this work presents a specific use case developed for the Universitat Oberta de Catalunya, which is an online university. An automatic evaluation tool is proposed that allows the student to evaluate himself anytime and receive instant feedback. This tool is a web-based platform, and it has been designed for engineering subjects (i.e., with math symbols and formulas in Catalan and Spanish. Particularly, the technique used for automatic assessment is latent semantic analysis. Although the experimental framework from the use case is quite challenging, results are promising.
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International Nuclear Information System (INIS)
Sari, Ahmet
2006-01-01
Accelerated thermal cycle tests have been conducted to study the change in melting temperatures and latent heats of fusion of the eutectic mixtures of lauric acid (LA)-myristic acid (MA), lauric acid (LA)-palmitic acid (PA) and myristic acid (MA)-stearic acid (SA) as latent heat storage materials. The thermal properties of these materials were determined by the differential scanning calorimetry (DSC) analysis method. The thermal reliability of the eutectic mixtures after melt/freeze cycles of 720, 1080 and 1460 was also evaluated using the DSC curves. The accelerated thermal cycle tests indicate that the melting temperatures usually tend to decrease, and the variations in the latent heats of fusion are irregular with increasing number of thermal cycles. Moreover, the probable reasons for the change in thermal properties of the eutectic mixtures after repeated thermal cycles were investigated. Fourier Transform Infrared (FT-IR) spectroscopic analysis indicates that the accelerated melt/freeze processes do not cause any degradation in the chemical structure of the mixtures. The change in thermal properties of the eutectic mixtures with increasing number of thermal cycles is only because of the presence of certain amounts of impurities in the fatty acids used in their preparation. It is concluded that the tested eutectic mixtures have reasonable thermal properties and thermal reliability as phase change materials (PCMs) for latent heat storage in any solar heating applications that include a four year utilization period
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Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Vermunt, Jeroen K
2014-10-01
In studies on the development of cognitive processes, children are often grouped based on their ages before analyzing the data. After the analysis, the differences between age groups are interpreted as developmental differences. We argue that this approach is problematic because the variance in cognitive performance within an age group is considered to be measurement error. However, if a part of this variance is systematic, it can provide very useful information about the cognitive processes used by some children of a certain age but not others. In the current study, we presented 210 children aged 5 to 12 years with serial order short-term memory tasks. First we analyze our data according to the approach using age groups, and then we apply latent class analysis to form latent classes of children based on their performance instead of their ages. We display the results of the age groups and the latent classes in terms of serial position curves, and we discuss the differences in results. Our findings show that there are considerable differences in performance between the age groups and the latent classes. We interpret our findings as indicating that the latent class analysis yielded a much more meaningful way of grouping children in terms of cognitive processes than the a priori grouping of children based on their ages. Copyright © 2014 Elsevier Inc. All rights reserved.
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Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry
2013-06-01
The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.
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Latent class analysis on internet and smartphone addiction in college students.
Mok, Jung-Yeon; Choi, Sam-Wook; Kim, Dai-Jin; Choi, Jung-Seok; Lee, Jaewon; Ahn, Heejune; Choi, Eun-Jeung; Song, Won-Young
2014-01-01
This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used. Significant differences between males and females were found for most of the variables (all addicted than females (Psmartphone, this pattern was reversed (Psmartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (Paddiction severity levels (all Paddiction severity levels (all Psmartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field.
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Wang, Haipeng; Tang, Chengxiang; Zhao, Shichao; Meng, Qingyue; Liu, Xiaoyun
2017-09-22
Background : The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff's personal and professional features; Methods : We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results : Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to "satisfied class"; 38.2% had low job satisfaction, named as "unsatisfied class"; 30.5% were categorized into "unsatisfied class with the exception of interpersonal relationships"; 22.4% were identified as "pseudo-satisfied class", only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions : The minority of health-care staff belong to the "satisfied class". Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff's features.
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Stability of latent class segments over time
DEFF Research Database (Denmark)
Mueller, Simone
2011-01-01
Dynamic stability, as the degree to which identified segments at a given time remain unchanged over time in terms of number, size and profile, is a desirable segment property which has received limited attention so far. This study addresses the question to what degree latent classes identified from...... logit model suggests significant changes in the price sensitivity and the utility from environmental claims between both experimental waves. A pooled scale adjusted latent class model is estimated jointly over both waves and the relative size of latent classes is compared across waves, resulting...... in significant differences in the size of two out of seven classes. These differences can largely be accounted for by the changes on the aggregated level. The relative size of latent classes is correlated at 0.52, suggesting a fair robustness. An ex-post characterisation of latent classes by behavioural...
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Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.
2016-01-01
A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…
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Latent Partially Ordered Classification Models and Normal Mixtures
Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith
2013-01-01
Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…
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Mannarini, Stefania; Boffo, Marilisa
2015-01-01
Mental illness stigma is a serious societal problem and a critical impediment to treatment seeking for mentally ill people. To improve the understanding of mental illness stigma, this study focuses on the simultaneous analysis of people's aetiological beliefs, attitudes (i.e. perceived dangerousness and social distance), and recommended treatments related to several mental disorders by devising an over-arching latent structure that could explain the relations among these variables. Three hundred and sixty university students randomly received an unlabelled vignette depicting one of six mental disorders to be evaluated on the four variables on a Likert-type scale. A one-factor Latent Class Analysis (LCA) model was hypothesized, which comprised the four manifest variables as indicators and the mental disorder as external variable. The main findings were the following: (a) a one-factor LCA model was retrieved; (b) alcohol and drug addictions are the most strongly stigmatized; (c) a realistic opinion about the causes and treatment of schizophrenia, anxiety, bulimia, and depression was associated to lower prejudicial attitudes and social rejection. Beyond the general appraisal of mental illness an individual might have, the results generally point to the acknowledgement of the specific features of different diagnostic categories. The implications of the present results are discussed in the framework of a better understanding of mental illness stigma.
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Reliability measures in item response theory: manifest versus latent correlation functions.
Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Verbeke, Geert; De Boeck, Paul
2015-02-01
For item response theory (IRT) models, which belong to the class of generalized linear or non-linear mixed models, reliability at the scale of observed scores (i.e., manifest correlation) is more difficult to calculate than latent correlation based reliability, but usually of greater scientific interest. This is not least because it cannot be calculated explicitly when the logit link is used in conjunction with normal random effects. As such, approximations such as Fisher's information coefficient, Cronbach's α, or the latent correlation are calculated, allegedly because it is easy to do so. Cronbach's α has well-known and serious drawbacks, Fisher's information is not meaningful under certain circumstances, and there is an important but often overlooked difference between latent and manifest correlations. Here, manifest correlation refers to correlation between observed scores, while latent correlation refers to correlation between scores at the latent (e.g., logit or probit) scale. Thus, using one in place of the other can lead to erroneous conclusions. Taylor series based reliability measures, which are based on manifest correlation functions, are derived and a careful comparison of reliability measures based on latent correlations, Fisher's information, and exact reliability is carried out. The latent correlations are virtually always considerably higher than their manifest counterparts, Fisher's information measure shows no coherent behaviour (it is even negative in some cases), while the newly introduced Taylor series based approximations reflect the exact reliability very closely. Comparisons among the various types of correlations, for various IRT models, are made using algebraic expressions, Monte Carlo simulations, and data analysis. Given the light computational burden and the performance of Taylor series based reliability measures, their use is recommended. © 2014 The British Psychological Society.
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Transcriptional Regulation of Latent Feline Immunodeficiency Virus in Peripheral CD4+ T-lymphocytes
Directory of Open Access Journals (Sweden)
Brian G. Murphy
2012-05-01
Full Text Available Feline immunodeficiency virus (FIV, the lentivirus of domestic cats responsible for feline AIDS, establishes a latent infection in peripheral blood CD4+ T-cells approximately eight months after experimental inoculation. In this study, cats experimentally infected with the FIV-C strain in the asymptomatic phase demonstrated an estimated viral load of 1 infected cell per approximately 103 CD4+ T-cells, with about 1 copy of viral DNA per cell. Approximately 1 in 10 proviral copies was capable of transcription in the asymptomatic phase. The latent FIV proviral promoter was associated with deacetylated, methylated histones, which is consistent with a condensed chromatin structure. In contrast, the transcriptionally active FIV promoter was associated with histone acetylation and demethylation. In addition, RNA polymerase II appeared to be paused on the latent viral promoter, and short promoter-proximal transcripts were detected. Our findings for the FIV promoter in infected cats are similar to results obtained in studies of human immunodeficiency virus (HIV-1 latent proviruses in cell culture in vitro studies. Thus, the FIV/cat model may offer insights into in vivo mechanisms of HIV latency and provides a unique opportunity to test novel therapeutic interventions aimed at eradicating latent virus.
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Biomarkers of latent TB infection
DEFF Research Database (Denmark)
Ruhwald, Morten; Ravn, Pernille
2009-01-01
For the last 100 years, the tuberculin skin test (TST) has been the only diagnostic tool available for latent TB infection (LTBI) and no biomarker per se is available to diagnose the presence of LTBI. With the introduction of M. tuberculosis-specific IFN-gamma release assays (IGRAs), a new area...... of in vitro immunodiagnostic tests for LTBI based on biomarker readout has become a reality. In this review, we discuss existing evidence on the clinical usefulness of IGRAs and the indefinite number of potential new biomarkers that can be used to improve diagnosis of latent TB infection. We also present...... early data suggesting that the monocyte-derived chemokine inducible protein-10 may be useful as a novel biomarker for the immunodiagnosis of latent TB infection....
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Valente, Juliana Y; Cogo-Moreira, Hugo; Sanchez, Zila M
2017-11-01
To identify different patterns of drug use in adolescence and determine if these are associated with parenting styles and other sociodemographic factors. A latent class analysis was conducted using baseline data collected in a sample (n=6381) from a randomized controlled trial conducted to evaluate the effectiveness of the #Tamojunto drug-use prevention program, carried out with 7th- and 8th-grade public school students in six Brazilian cities. Three latent classes were identified among the students: 1) abstainers/low users (81.54%), 2) alcohol users/binge drinkers (16.65%), and 3) polydrug users (1.80%). A gradient of inverse association was found between parenting styles (authoritative, authoritarian, and indulgent, with the neglectful style as a reference point) and the classes "alcohol users/binge drinkers" (aOR=0.36, 95%CI=0.27-0.47; aOR=0.56, 95%CI=0.43-0.72; and aOR=0.64, 95%CI=0.51-0.80, respectively) and "polydrug users" (aOR=0.09, 95%CI=0.03-0.24; aOR=0.23, 95%CI=0.11-0.52; and aOR=0.24, 95%CI=0.08-0.74, respectively). Associations were also revealed between the latent classes and the adolescent's age and socioeconomic status. The results suggest that activities to develop parenting skills should be included in school programs aimed at the prevention of drug use among adolescents in order to reduce neglectful practices and thereby possibly reduce drug use among the children. Copyright © 2017. Published by Elsevier B.V.
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Meacham, Meredith C; Rudolph, Abby E; Strathdee, Steffanie A; Rusch, Melanie L; Brouwer, Kimberly C; Patterson, Thomas L; Vera, Alicia; Rangel, Gudelia; Roesch, Scott C
2015-01-01
Although most people who inject drugs (PWID) in Tijuana, Mexico, primarily inject heroin, injection and non-injection use of methamphetamine and cocaine is common. We examined patterns of polydrug use among heroin injectors to inform prevention and treatment of drug use and its health and social consequences. Participants were PWID residing in Tijuana, aged ≥18 years who reported heroin injection in the past six months and were recruited through respondent-driven sampling (n = 1,025). Latent class analysis was conducted to assign individuals to classes on a probabilistic basis, using four indicators of past six-month polydrug and polyroute use: cocaine injecting, cocaine smoking or snorting, methamphetamine injecting, and methamphetamine smoking or snorting. Latent class membership was regressed onto covariates in a multinomial logistic regression. Latent class analyses testing 1, 2, 3, and 4 classes were fit, with the 3-class solution fitting best. Class 1 was defined by predominantly heroin use (50.2%, n = 515); class 2 by methamphetamine and heroin use (43.7%, n = 448), and class 3 by methamphetamine, cocaine, and heroin use (6.0%, n = 62). Bivariate and multivariate analyses indicated a group of methamphetamine and cocaine users that exhibited higher-risk sexual practices and lower heroin injecting frequency, and a group of methamphetamine users who were younger and more likely to be female. Discrete subtypes of heroin PWID were identified based on methamphetamine and cocaine use patterns. These findings have identified subtypes of heroin injectors who require more tailored interventions to reduce the health and social harms of injecting drug use.
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Olaya, Beatriz; Moneta, Maria Victoria; Caballero, Francisco Félix; Tyrovolas, Stefanos; Bayes, Ivet; Ayuso-Mateos, José Luis; Haro, Josep Maria
2017-08-18
This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up. We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes. 63.8% of participants were assigned to the "healthy" class, with minimum disease, 30% were classified under the "metabolic/stroke" class and 6% were assigned to the "cardiorespiratory/mental/arthritis" class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the "metabolic/stroke" class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services. Common chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.
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A Latent Class Analysis of Heterosexual Young Men's Masculinities.
Casey, Erin A; Masters, N Tatiana; Beadnell, Blair; Wells, Elizabeth A; Morrison, Diane M; Hoppe, Marilyn J
2016-07-01
Parallel bodies of research have described the diverse and complex ways that men understand and construct their masculine identities (often termed "masculinities") and, separately, how adherence to traditional notions of masculinity places men at risk for negative sexual and health outcomes. The goal of this analysis was to bring together these two streams of inquiry. Using data from a national, online sample of 555 heterosexually active young men, we employed latent class analysis (LCA) to detect patterns of masculine identities based on men's endorsement of behavioral and attitudinal indicators of "dominant" masculinity, including sexual attitudes and behaviors. LCA identified four conceptually distinct masculine identity profiles. Two groups, termed the Normative and Normative/Male Activities groups, respectively, constituted 88 % of the sample and were characterized by low levels of adherence to attitudes, sexual scripts, and behaviors consistent with "dominant" masculinity, but differed in their levels of engagement in male-oriented activities (e.g., sports teams). Only eight percent of the sample comprised a masculinity profile consistent with "traditional" ideas about masculinity; this group was labeled Misogynistic because of high levels of sexual assault and violence toward female partners. The remaining four percent constituted a Sex-Focused group, characterized by high numbers of sexual partners, but relatively low endorsement of other indicators of traditional masculinity. Follow-up analyses showed a small number of differences across groups on sexual and substance use health indicators. Findings have implications for sexual and behavioral health interventions and suggest that very few young men embody or endorse rigidly traditional forms of masculinity.
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Prevalence of latent alpha-herpesviruses in Thoroughbred racing horses.
Pusterla, Nicola; Mapes, Samantha; David Wilson, W
2012-08-01
The objective of this study was to detect and characterize latent equine herpes virus (EHV)-1 and -4 from the submandibular (SMLN) and bronchial lymph (BLN) nodes, as well as from the trigeminal ganglia (TG) of 70 racing Thoroughbred horses submitted for necropsy following sustaining serious musculoskeletal injuries while racing. A combination of nucleic acid precipitation and pre-amplification steps was used to increase analytical sensitivity. Tissues were deemed positive for latent EHV-1 and/or -4 infection when found PCR positive for the corresponding glycoprotein B (gB) gene in the absence of detectable late structural protein gene (gB gene) mRNA. The EHV-1 genotype was also determined using a discriminatory real-time PCR assay targeting the DNA polymerase gene (ORF 30). Eighteen (25.7%) and 58 (82.8%) horses were PCR positive for the gB gene of EHV-1 and -4, respectively, in at least one of the three tissues sampled. Twelve horses were dually infected with EHV-1 and -4, two carried a latent neurotropic strain of EHV-1, six carried a non-neurotropic genotype of EHV-1 and 10 were dually infected with neurotropic and non-neurotropic EHV-1. The distribution of latent EHV-1 and -4 infection varied in the samples, with the TG found to be most commonly infected. Overall, non-neurotropic strains were more frequently detected than neurotropic strains, supporting the general consensus that non-neurotropic strains are more prevalent in horse populations, and hence the uncommon occurrence of equine herpes myeloencephalopathy. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Heterogeneity of postpartum depression: a latent class analysis
2016-01-01
Summary Background Maternal depression in the postpartum period confers substantial morbidity and mortality, but the definition of postpartum depression remains controversial. We investigated the heterogeneity of symptoms with the aim of identifying clinical subtypes of postpartum depression. Methods Data were aggregated from the international perinatal psychiatry consortium Postpartum Depression: Action Towards Causes and Treatment, which represents 19 institutions in seven countries. 17 912 unique subject records with phenotypic data were submitted. We applied latent class analyses in a two-tiered approach to assess the validity of empirically defined subtypes of postpartum depression. Tier one assessed heterogeneity in women with complete data on the Edinburgh postnatal depression scale (EPDS) and tier two in those with postpartum depression case status. Findings 6556 individuals were assessed in tier one and 4245 in tier two. A final model with three latent classes was optimum for both tiers. The most striking characteristics associated with postpartum depression were severity, timing of onset, comorbid anxiety, and suicidal ideation. Women in class 1 had the least severe symptoms (mean EPDS score 10·5), followed by those in class 2 (mean EPDS score 14·8) and those in class 3 (mean EPDS score 20·1). The most severe symptoms of postpartum depression were significantly associated with poor mood (mean EPDS score 20·1), increased anxiety, onset of symptoms during pregnancy, obstetric complications, and suicidal ideation. In class 2, most women (62%) reported symptom onset within 4 weeks postpartum and had more pregnancy complications than in other two classes (69% vs 67% in class 1 and 29% in class 3). Interpretation PPD seems to have several distinct phenotypes. Further assessment of PPD heterogeneity to identify more precise phenotypes will be important for future biological and genetic investigations. Funding Sources of funding are listed at the end of the
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Offringa, Reid; Tsai, Laura Cordisco; Aira, Toivgoo; Riedel, Marion; Witte, Susan S
2017-08-01
Women engaged in sex work bear a disproportionate burden of HIV infection worldwide, particularly in low- to middle-income countries. Stakeholders interested in promoting prevention and treatment programs are challenged to efficiently and effectively target heterogeneous groups of women. This problem is particularly difficult because it is nearly impossible to know how those groups are composed a priori. Although grouping based on individual variables (e.g., age or place of solicitation) can describe a sample of women engaged in sex work, selecting these variables requires a strong intuitive understanding of the population. Furthermore, this approach is difficult to quantify and has the potential to reinforce preconceived notions, rather than generate new information. We aimed to investigate groupings of women engaged in sex work. The data were collected from a sample of 204 women who were referred to an HIV prevention intervention in Ulaanbaatar, Mongolia. Latent class analysis was used to create subgroups of women engaged in sex work, based on personal and financial risk factors. This analysis found three latent classes, representing unique response pattern profiles of personal and financial risk. The current study approached typology research in a novel, more empirical way and provided a description of different subgroups, which may respond differently to HIV risk interventions.
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Directory of Open Access Journals (Sweden)
Haipeng Wang
2017-09-01
Full Text Available Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results: Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to “satisfied class”; 38.2% had low job satisfaction, named as “unsatisfied class”; 30.5% were categorized into “unsatisfied class with the exception of interpersonal relationships”; 22.4% were identified as “pseudo-satisfied class”, only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions: The minority of health-care staff belong to the “satisfied class”. Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff’s features.
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Latent class analysis on internet and smartphone addiction in college students
Directory of Open Access Journals (Sweden)
Mok JY
2014-05-01
Full Text Available Jung-Yeon Mok,1 Sam-Wook Choi,1,2 Dai-Jin Kim,3 Jung-Seok Choi,4 Jaewon Lee,2 Heejune Ahn,5 Eun-Jeung Choi,6 Won-Young Song7 1Eulji Addiction Institute, Eulji University, Seoul, South Korea; 2Department of Psychiatry, Gangnam Eulji Hospital, Eulji University, Seoul, South Korea; 3Department of Psychiatry, Seoul St Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, South Korea; 4Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea; 5Department of Electrical and Information Engineering, SeoulTech, Seoul, South Korea; 6Department of Social Welfare, Dongshin University, Naju, South Korea; 7Department of Counseling and Psychotherapy, Konyang University, Nonsan, South Korea Purpose: This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. Methods: A total of 448 university students (178 males and 270 females in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance were the statistical methods used. Results: Significant differences between males and females were found for most of the variables (all P<0.05. Specifically, in terms of internet usage, males were more addicted than females (P<0.05; however, regarding smartphone, this pattern was reversed (P<0.001. Due to these observed differences, classifications of the subjects into subgroups based on internet and smartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (P<0.001. A common trend for psychosocial trait factors was found for both sexes: anxiety levels and
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Systematic identification of latent disease-gene associations from PubMed articles.
Zhang, Yuji; Shen, Feichen; Mojarad, Majid Rastegar; Li, Dingcheng; Liu, Sijia; Tao, Cui; Yu, Yue; Liu, Hongfang
2018-01-01
Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.
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A Framework for Reproducible Latent Fingerprint Enhancements.
Carasso, Alfred S
2014-01-01
Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.
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Subgrouping of risky behaviors among Iranian college students: a latent class analysis
Safiri, Saeid; Rahimi-Movaghar, Afarin; Yunesian, Masud; Sadeghi-Bazargani, Homayoun; Shamsipour, Mansour; Mansournia, Mohammad Ali; Fotouhi, Akbar
2016-01-01
Background Risky behaviors may interrupt development or cause considerable morbidity or mortality. This study’s purpose was to determine subgroups of students based on risky behaviors and assess the prevalence of risky behaviors in each of the subgroups. Participants and methods This anonymous cross-sectional study was carried out in October 2015 and November 2015, with 1,777 students from Tabriz University of Medical Sciences, through multistage random sampling method. The data were analyzed by latent class analysis. Results The prevalence rates of cigarette smoking (more than or equal to ten cigarettes), hookah use (≥1 time/month), and alcohol consumption (≥1 time/month) during the last year were 12.4% (95% confidence interval [CI]: 10.9–14.0), 11.6% (95% CI: 10.0–13.1), and 4.9% (95% CI: 3.8–5.9), respectively. The prevalence rates of illicit opioids (1.8%, 95% CI: 1.2–2.5), cannabis (1.2%, 95% CI: 0.7–1.7), methamphetamine (1.1%, 95% CI: 0.6–1.6), methylphenidate (2.5%, 95% CI: 1.7–3.2), and extramarital sex (5.5%, 95% CI: 4.5–6.6) over the last year were also estimated. Three latent classes were determined: 1) low risk; 2) cigarette and hookah smoker; and 3) high risk. It is worth mentioning that 3.7% of males and 0.4% of females were in the high risk group. Conclusion Subgrouping of college students showed that a considerable percentage of them, especially males, were classified into the high risk and cigarette and hookah smoker groups. Appropriate preventive measures that consider multiple different risky behaviors simultaneously are needed for this part of the population. PMID:27524898
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Latent class analysis on internet and smartphone addiction in college students
Mok, Jung-Yeon; Choi, Sam-Wook; Kim, Dai-Jin; Choi, Jung-Seok; Lee, Jaewon; Ahn, Heejune; Choi, Eun-Jeung; Song, Won-Young
2014-01-01
Purpose This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. Methods A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used. Results Significant differences between males and females were found for most of the variables (all addicted than females (Psmartphone, this pattern was reversed (Psmartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (Paddiction severity levels (all Paddiction severity levels (all Pprocess, this study identified three distinct internet and smartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field. PMID:24899806
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Linear latent variable models: the lava-package
DEFF Research Database (Denmark)
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...
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Estimators for longitudinal latent exposure models: examining measurement model assumptions.
Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D
2017-06-15
Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
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Perceptions of care in women sent home in latent labor.
Hosek, Claire; Faucher, Mary Ann; Lankford, Janice; Alexander, James
2014-01-01
To assess perceptions of care from woman discharged from an obstetrical (OB) triage unit or a labor and delivery unit with a diagnosis of false or latent labor in order to determine factors that may increase or decrease the woman's satisfaction with care. Descriptive, convenience sample. One hundred low-income pregnant women at term presenting for care in latent labor consented to participate in a telephone survey. The survey was based on the relevant research about care of women in early labor and the Donabedian quality improvement framework assessing structure, process, and outcomes of care. Forty-one percent of women did not want to be discharged home in latent labor. Common reasons included women stating they were in too much pain or they were living too far from the birth setting. Eating, drinking, and comfort measures were the most common measures women cited that would have made them feel better when in the hospital. A reoccurring response from women was their desire for very clear and specific written instructions about how to stay comfortable at home and when to return to the hospital. Comfort measures in the birth setting, including in triage, should include a variety of options including ambulation and oral nutrition. Detailed and specific written instructions about early labor and staying comfortable while at home have value for women in this survey regarding their perceptions of care. Results from this survey of low-income women suggest that a subset of women in latent labor just do not want to go home and this may be related to having too much pain and/or travel distance to the hospital. Hospital birth settings also have an opportunity to create a care environment that provides services and embodies attributes that women report as important for their satisfaction with care in latent labor.
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Takayabu, Yukari N.; Shige, Shoichi; Tao, Wei-Kuo; Hirota, Nagio
2010-01-01
The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large
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Using standard serology blood tests to diagnose latent syphilis
Directory of Open Access Journals (Sweden)
G. L. Katunin
2016-01-01
Full Text Available Goal. To conduct a comparative assessment of the results of regulated serological tests obtained as a result of blood tests in patients suffering from latent syphilis. Materials and methods. The authors examined 187 patient medical records with newly diagnosed latent syphilis in FGBU GNTsDK (State Research Center for Dermatology, Venereology and Cosmetology, Health Ministry of the Russian Federation, in 2006-2015. The results of patient blood tests were analyzed with the use of non-treponemal (microprecipitation test/RPR and treponemal (passive hemagglutination test, immune-enzyme assay (IgA, IgM, IgG, IFabs, immunofluorescence test and Treponema pallidum immobilization test serology tests. Results. According to the results of blood tests of latent syphilis patients, the largest number of positive results was obtained as a result of treponemal serology tests such as immune-enzyme assay (100%, passive hemagglutination test (100% and IFabs (100%. The greatest number of negative results was observed in non-treponemal (microprecipitation test/RPR serology tests: in 136 (72.7% patients; evidently positive results (4+ test results were obtained in 8 (4.3% patients only. According to the results of a comparative analysis of blood tests in patients suffering from latent syphilis obtained with the use of treponemal serology tests, the greatest number of evidently positive results (4+ was noted for the passive hemagglutination test (67.9%. Negative treponemal test results were obtained with the use of the immunofluorescence test and Treponema pallidum immobilization test (21.9% and 11.8% of cases, respectively. Moreover, weakly positive results prevailed for the immunofluorescence test: in 65 (34.7% patients. Conclusion. These data confirm that the following treponemal tests belong to the most reliable ones for revealing patients suffering from latent syphilis: immune-enzyme assay, passive hemagglutination test and IFabs.
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The Multi-state Latent Factor Intensity Model for Credit Rating Transitions
Koopman, S.J.; Lucas, A.; Monteiro, A.
2008-01-01
A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the
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Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula
2014-08-01
Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.
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A flexible latent class approach to estimating test-score reliability
van der Palm, D.W.; van der Ark, L.A.; Sijtsma, K.
2014-01-01
The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution
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Joint Textual And Visual Cues For Retrieving Images Using Latent Semantic Indexing
Pecenovic, Zoran; Ayer, Serge; Vetterli, Martin
2001-01-01
In this article we present a novel approach of integrating textual and visual descriptors of images in a unified retrieval structure. The methodology, inspired from text retrieval and information filtering is based on Latent Semantic Indexing (LS1).
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Mathur, Charu; Stigler, Melissa; Lust, Katherine; Laska, Melissa
2014-01-01
Little is known about the complex patterning of weight-related health behaviors in 2-and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health…
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Directory of Open Access Journals (Sweden)
Manuel Fernández-Arata
2015-06-01
Full Text Available Resumen La medición del burnout ha evolucionado con la creación de varios instrumentos y modelos. El Maslach Burnout Inventory - General Survey (MBI-GS es uno de estos instrumentos para medir tres constructos definicionales del burnout: (1 agotamiento emocional, (2 eficacia profesional y (3 indiferencia. Fue creado para un amplio rango de ocupaciones, pero pocas veces se ha verificado su estructura latente e invarianza de medición en Latinoamérica. El presente estudio analiza esta estructura latente y la invarianza de medición del MBI-GS en una muestra de 940 trabajadores peruanos de varias ocupaciones. Se aplicó la metodología de ecuaciones estructurales mediante el análisis factorial confirmatorio, así como la invarianza de medición entre varones y mujeres, imponiendo restricciones sucesivamente más estrictas. Los resultados verificaron satisfactoriamente la estructura de tres dimensiones latentes del MBI-GS, y la invarianza de sus parámetros entre hombres y mujeres. Se discute las implicaciones de los resultados. Abstract The measurement of burnout has evolved into the creation of various tools and models. The Maslach Burnout Inventory - General Survey (MBI-GS is one of these instruments used to measure three definitional constructs of burnout: (1 emotional exhaustion, (2 professional efficiency, and (3 indifference. It was created for a wide range of occupations, but its latent structure and invariance of measurement in Latin America has rarely been verified. The present study analyzes the latent structure and the invariance of measurement of MBI-GS in a sample of 940 Peruvian workers in various occupations. The methodology of structural equations was applied through the confirmatory factor analysis, as well as the invariance of measurement between men and women, imposing restrictions successively more strict. The results satisfactorily verified the structure of three-dimensional latent MBI-GS, and the invariance of its
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Chamberlain, Samuel R; Stochl, Jan; Redden, Sarah A; Odlaug, Brian L; Grant, Jon E
2017-09-01
Gambling disorder has been associated with cognitive dysfunction and impaired quality of life. The current definition of non-pathological, problem, and pathological types of gambling is based on total symptom scores, which may overlook nuanced underlying presentations of gambling symptoms. The aims of the current study were (i) to identify subtypes of gambling in young adults, using latent class analysis, based on individual responses from the Structured Clinical Interview for Gambling Disorder (SCI-GD); and (ii) to explore relationships between these gambling subtypes, and clinical/cognitive measures. Total 582 non-treatment seeking young adults were recruited from two US cities, on the basis of gambling five or more times per year. Participants undertook clinical and neurocognitive assessment, including stop-signal, decision-making, and set-shifting tasks. Data from individual items of the Structured Clinical Interview for Gambling Disorder (SCI-GD) were entered into latent class analysis. Optimal number of classes representing gambling subtypes was identified using Bayesian Information Criterion and differences between them were explored using multivariate analysis of variance. Three subtypes of gambling were identified, termed recreational gamblers (60.2% of the sample; reference group), problem gamblers (29.2%), and pathological gamblers (10.5%). Common quality of life impairment, elevated Barratt Impulsivity scores, occurrence of mainstream mental disorders, having a first degree relative with an addiction, and impaired decision-making were evident in both problem and pathological gambling groups. The diagnostic item 'chasing losses' most discriminated recreational from problem gamblers, while endorsement of 'social, financial, or occupational losses due to gambling' most discriminated pathological gambling from both other groups. Significantly higher rates of impulse control disorders occurred in the pathological group, versus the problem group, who in turn
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Hyppolite, Judex; Trivedi, Pravin
2012-06-01
Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel. Copyright © 2012 John Wiley & Sons, Ltd.
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Directory of Open Access Journals (Sweden)
Nobuhiro Sanko
2013-03-01
Full Text Available Disaggregate behaviour choice models have been improved in many aspects, but they are rarely evaluated from the viewpoint of their ability to express intention to change travel behaviour. This study compared various models, including objective and latent models and compensatory and non-compensatory decision-making models. Latent models contain latent factors calculated using the LISREL (linear structural relations model. Non-compensatory models are based on a lexicographic-semiorder heuristic. This paper proposes ‘probability increment’ and ‘joint probability increment’ as indicators for evaluating the ability of these models to express intention to change travel behaviour. The application to commuting travel data in the Chukyo metropolitan area in Japan showed that the appropriate non-compensatory and latent models outperform other models.
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Latent Dirichlet Allocation (LDA) for Sentiment Analysis Toward Tourism Review in Indonesia
Putri, IR; Kusumaningrum, R.
2017-01-01
The tourism industry is one of foreign exchange sector, which has considerable potential development in Indonesia. Compared to other Southeast Asia countries such as Malaysia with 18 million tourists and Singapore 20 million tourists, Indonesia which is the largest Southeast Asia’s country have failed to attract higher tourist numbers compared to its regional peers. Indonesia only managed to attract 8,8 million foreign tourists in 2013, with the value of foreign tourists each year which is likely to decrease. Apart from the infrastructure problems, marketing and managing also form of obstacles for tourism growth. An evaluation and self-analysis should be done by the stakeholder to respond toward this problem and capture opportunities that related to tourism satisfaction from tourists review. Recently, one of technology to answer this problem only relying on the subjective of statistical data which collected by voting or grading from user randomly. So the result is still not to be accountable. Thus, we proposed sentiment analysis with probabilistic topic model using Latent Dirichlet Allocation (LDA) method to be applied for reading general tendency from tourist review into certain topics that can be classified toward positive and negative sentiment.
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Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A
2010-03-01
Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.
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A model for the latent heat of melting in free standing metal nanoparticles
International Nuclear Information System (INIS)
Shin, Jeong-Heon; Deinert, Mark R.
2014-01-01
Nanoparticles of many metals are known to exhibit scale dependent latent heats of melting. Analytical models for this phenomenon have so far failed to completely capture the observed phenomena. Here we present a thermodynamic analysis for the melting of metal nanoparticles in terms of their internal energy and a scale dependent surface tension proposed by Tolman. The resulting model predicts the scale dependence of the latent heat of melting and is confirmed using published data for tin and aluminum
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Willie, Tiara C; Chakrapani, Venkatesan; White Hughto, Jaclyn M; Kershaw, Trace S
2017-12-01
Globally, transgender women (TGW) experience multiple forms of victimization such as violence and discrimination that can place them at risk for poor sexual health. To date, research overlooks the heterogeneity in experiences of victimization among TGW. Furthermore, few studies have examined the association between victimization and sexual risk among TGW in India, despite the high burden of HIV and victimization in this community. Latent profile analysis was performed to identify patterns of victimization in a convenience sample of 299 TGW recruited from nongovernmental organizations across four states in India. Analysis of covariance was performed to examine differences in sexual risk (i.e., alcohol use before sex; inconsistent condom use with a male regular partner, a male causal partner, and a male paying partner; and having multiple sexual partners) between latent profiles. Five distinct profiles of Indian TGW were identified based on the type and severity of victimization: (1) Low victimization, (2) High verbal police victimization, (3) High verbal and physical police victimization, (4) Moderate victimization, and (5) High victimization. While controlling for age, education, income, HIV status, and marital status, results revealed that TGW in the moderate victimization and high victimization profiles had higher sexual risk than TGW in the low victimization and high verbal police victimization profiles. In addition, TGW in high verbal and physical police victimization profile had higher sexual risk than TGW in low victimization profile. These findings underscore the importance of tailoring sexual risk reduction interventions to the specific needs of TGW based on patterns of victimization.
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Extraction of latent images from printed media
Sergeyev, Vladislav; Fedoseev, Victor
2015-12-01
In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.
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Examination of the change in latent statuses in bullying behaviors across time.
Ryoo, Ji Hoon; Wang, Cixin; Swearer, Susan M
2015-03-01
Involvement in bullying and victimization has been mostly studied using cross-sectional data from 1 time point. As such, much of our understanding of bullying and victimization has not captured the dynamic experiences of youth over time. To examine the change of latent statuses in bullying and victimization, we applied latent transition analysis examining self-reported bullying involvement from 1,180 students in 5th through 9th grades across 3 time points. We identified unobserved heterogeneous subgroups (i.e., latent statuses) and investigated how students transition between the unobserved subgroups over time. For victimization, 4 latent statuses were identified: frequent victim (11.23%), occasional traditional victim (28.86%), occasional cyber and traditional victim (10.34%), and infrequent victim (49.57%). For bullying behavior, 3 latent statuses were identified: frequent perpetrator (5.12%), occasional verbal/relational perpetrator (26.04%), and infrequent perpetrator (68.84%). The characteristics of the transitions were examined. The multiple-group effects of gender, grade, and first language learned on transitions across statuses were also investigated. The infrequent victim and infrequent perpetrator groups were the most stable, and the frequent victim and frequent perpetrator groups were the least stable. These findings suggest instability in perpetration and victimization over time, as well as significant changes, especially during school transition years. Findings suggest that school-based interventions need to address the heterogeneity in perpetrator and victim experiences in adolescence.
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Fitting Latent Cluster Models for Networks with latentnet
Directory of Open Access Journals (Sweden)
Pavel N. Krivitsky
2007-12-01
Full Text Available latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002 suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a function of distances between these characteristics as well as functions of observed dyadic level covariates. In latentnet social distances are represented in a Euclidean space. It also includes a variant of the extension of the latent position model to allow for clustering of the positions developed in Handcock, Raftery, and Tantrum (2007.The package implements Bayesian inference for the models based on an Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent position model and a two-stage maximum likelihood method for the latent position cluster model. For latent position cluster models, the package provides a Bayesian way of assessing how many groups there are, and thus whether or not there is any clustering (since if the preferred number of groups is 1, there is little evidence for clustering. It also estimates which cluster each actor belongs to. These estimates are probabilistic, and provide the probability of each actor belonging to each cluster. It computes four types of point estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode and the estimator which minimizes Kullback-Leibler divergence from the posterior. You can assess the goodness-of-fit of the model via posterior predictive checks. It has a function to simulate networks from a latent position or latent position cluster model.
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Enhancing multilingual latent semantic analysis with term alignment information.
Energy Technology Data Exchange (ETDEWEB)
Chew, Peter A.; Bader, Brett William
2008-08-01
Latent Semantic Analysis (LSA) is based on the Singular Value Decomposition (SVD) of a term-by-document matrix for identifying relationships among terms and documents from co-occurrence patterns. Among the multiple ways of computing the SVD of a rectangular matrix X, one approach is to compute the eigenvalue decomposition (EVD) of a square 2 x 2 composite matrix consisting of four blocks with X and XT in the off-diagonal blocks and zero matrices in the diagonal blocks. We point out that significant value can be added to LSA by filling in some of the values in the diagonal blocks (corresponding to explicit term-to-term or document-to-document associations) and computing a term-by-concept matrix from the EVD. For the case of multilingual LSA, we incorporate information on cross-language term alignments of the same sort used in Statistical Machine Translation (SMT). Since all elements of the proposed EVD-based approach can rely entirely on lexical statistics, hardly any price is paid for the improved empirical results. In particular, the approach, like LSA or SMT, can still be generalized to virtually any language(s); computation of the EVD takes similar resources to that of the SVD since all the blocks are sparse; and the results of EVD are just as economical as those of SVD.
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Besstremyannaya, Galina
2011-09-01
The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management. Copyright © 2011 John Wiley & Sons, Ltd.
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The epigenetic landscape of latent Kaposi sarcoma-associated herpesvirus genomes.
Directory of Open Access Journals (Sweden)
Thomas Günther
Full Text Available Herpesvirus latency is generally thought to be governed by epigenetic modifications, but the dynamics of viral chromatin at early timepoints of latent infection are poorly understood. Here, we report a comprehensive spatial and temporal analysis of DNA methylation and histone modifications during latent infection with Kaposi Sarcoma-associated herpesvirus (KSHV, the etiologic agent of Kaposi Sarcoma and primary effusion lymphoma (PEL. By use of high resolution tiling microarrays in conjunction with immunoprecipitation of methylated DNA (MeDIP or modified histones (chromatin IP, ChIP, our study revealed highly distinct landscapes of epigenetic modifications associated with latent KSHV infection in several tumor-derived cell lines as well as de novo infected endothelial cells. We find that KSHV genomes are subject to profound methylation at CpG dinucleotides, leading to the establishment of characteristic global DNA methylation patterns. However, such patterns evolve slowly and thus are unlikely to control early latency. In contrast, we observed that latency-specific histone modification patterns were rapidly established upon a de novo infection. Our analysis furthermore demonstrates that such patterns are not characterized by the absence of activating histone modifications, as H3K9/K14-ac and H3K4-me3 marks were prominently detected at several loci, including the promoter of the lytic cycle transactivator Rta. While these regions were furthermore largely devoid of the constitutive heterochromatin marker H3K9-me3, we observed rapid and widespread deposition of H3K27-me3 across latent KSHV genomes, a bivalent modification which is able to repress transcription in spite of the simultaneous presence of activating marks. Our findings suggest that the modification patterns identified here induce a poised state of repression during viral latency, which can be rapidly reversed once the lytic cycle is induced.
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Latent variable models are network models.
Molenaar, Peter C M
2010-06-01
Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.
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Heteroscedastic Latent Trait Models for Dichotomous Data.
Molenaar, Dylan
2015-09-01
Effort has been devoted to account for heteroscedasticity with respect to observed or latent moderator variables in item or test scores. For instance, in the multi-group generalized linear latent trait model, it could be tested whether the observed (polychoric) covariance matrix differs across the levels of an observed moderator variable. In the case that heteroscedasticity arises across the latent trait itself, existing models commonly distinguish between heteroscedastic residuals and a skewed trait distribution. These models have valuable applications in intelligence, personality and psychopathology research. However, existing approaches are only limited to continuous and polytomous data, while dichotomous data are common in intelligence and psychopathology research. Therefore, in present paper, a heteroscedastic latent trait model is presented for dichotomous data. The model is studied in a simulation study, and applied to data pertaining alcohol use and cognitive ability.
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Haltigan, John D; Vaillancourt, Tracy
2018-01-01
Using 6 cycles (grade 5 through grade 10) of data obtained from a large prospective sample of Canadian school children (N = 700; 52.6% girls), we replicated previous findings concerning the empirical definition of peer victimization (i.e., being bullied) and examined static and dynamic intrapersonal factors associated with its emergence and experiential continuity through mid-adolescence. Latent class analyses consistently revealed a low victimization and an elevated victimization class across time, supporting previous work suggesting peer victimization was defined by degree rather than by type (e.g., physical). Using latent transition analyses (LTA), we found that child sex, parent-perceived pubertal development, and internalizing symptoms influenced the probability of transitioning from the low to the elevated victimization class across time. Higher-order extensions within the LTA modeling framework revealed a lasting effect of grade 5 victimization status on grade 10 victimization status and a large effect of chronic victimization on later parent-reported youth internalizing symptoms (net of prior parent-reported internalizing symptoms) in later adolescence (grade 11). Implications of the current findings for the experience of peer victimization, as well as the application of latent transition analysis as a useful approach for peer victimization research, are discussed.
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Directory of Open Access Journals (Sweden)
Sofia von Humboldt
Full Text Available Objective: To analyze the determinants of adjustment to aging (AtA and subjective age (SA identified by older adults and to investigate the differences of latent constructs that can work as major determinants in AtA and SA in an older Portuguese and Romanian population. Method: Measures were completed, including demographics and interviews. Complete data were available for 38 older adults aged between 74-90 years (M=80.6; SD = 5.4, from Portugal and Romenia. Data was subjected to content analysis. Representation of the associations and latent constructs were analyzed by a Multiple Correspondence Analysis (MCA. Results: The most prevalent response of the interviewed participants for determinants to AtA was ‘health status, physical and intellectual functioning’ (18.1%. ‘With apprehension’ and ‘good enough’ (both 27.0% were identified as the most frequent SA responses. Findings showed a model for each nationality. AtA and SA for Portuguese elderly were explained by a three-factor model: ‘regardful’, ‘engaged’ and ‘conciliated’. A three-dimension model formed by ‘perseverant’, ‘congruent’ and ‘enjoyers’ was indicated as a best-fit solution for Romanian elderly. Conclusion: AtA and SA are strongly explained by increased likelihood of specific constructs in its definition. AtA is related to SA in older adults in both countries, although in different degree.
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Energy Technology Data Exchange (ETDEWEB)
Rea, Jonathan E.; Oshman, Christopher J.; Olsen, Michele L.; Hardin, Corey L.; Glatzmaier, Greg C.; Siegel, Nathan P.; Parilla, Philip A.; Ginley, David S.; Toberer, Eric S.
2018-05-01
In this paper, we present performance simulations and techno-economic analysis of a modular dispatchable solar power tower. Using a heliostat field and power block three orders of magnitude smaller than conventional solar power towers, our unique configuration locates thermal storage and a power block directly on a tower receiver. To make the system dispatchable, a valved thermosyphon controls heat flow from a latent heat thermal storage tank to a Stirling engine. The modular design results in minimal balance of system costs and enables high deployment rates with a rapid realization of economies of scale. In this new analysis, we combine performance simulations with techno-economic analysis to evaluate levelized cost of electricity, and find that the system has potential for cost-competitiveness with natural gas peaking plants and alternative dispatchable renewables.
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Basic design of parallel computational program for probabilistic structural analysis
International Nuclear Information System (INIS)
Kaji, Yoshiyuki; Arai, Taketoshi; Gu, Wenwei; Nakamura, Hitoshi
1999-06-01
In our laboratory, for 'development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory' (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)
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Basic design of parallel computational program for probabilistic structural analysis
Energy Technology Data Exchange (ETDEWEB)
Kaji, Yoshiyuki; Arai, Taketoshi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Gu, Wenwei; Nakamura, Hitoshi
1999-06-01
In our laboratory, for `development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory` (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)
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Progression to dementia in memory clinic patients without dementia: a latent profile analysis
Kohler, S.; Hamel, R.; Sistermans, N.; Koene, T.; Pijnenburg, Y.A.L.; van der Flier, W.M.; Scheltens, P.; Visser, P.J.; Aalten, P.; Verhey, F. R. J.; Ramakers, I.
2013-01-01
Objective: To identify the existence of discrete cognitive subtypes among memory clinic patients without dementia and test their prognostic values. Methods: In a retrospective cohort study of 635 patients without dementia visiting the Alzheimer centers in Maastricht or Amsterdam, latent profile
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Recovery of latent fingerprints and DNA on human skin.
Färber, Doris; Seul, Andrea; Weisser, Hans-Joachim; Bohnert, Michael
2010-11-01
The project "Latent Fingerprints and DNA on Human Skin" was the first systematic research in Europe dealing with detection of fingerprints and DNA left by offenders on the skin of corpses. One thousand samples gave results that allow general statements on the materials and methods used. The tests were carried out according to a uniform trial structure. Fingerprints were deposited by natural donors on corpses. The latent fingerprints were treated with magnetic powder or black fingerprint powder. Afterward, they were lifted with silicone casting material (Isomark(®)) or gelatine foil. All lifts were swabbed to recover DNA. It was possible to visualize comparable and identifiable fingerprints on the skin of corpses (16%). In the same categories, magnetic powder (18.4%) yielded better results than black fingerprint powder (13.6%). The number of comparable and identifiable fingerprints decreased on the lifts (12.7%). Isomark(®) (14.9%) was the better lifting material in comparison with gelatine foil (10.1%). In one-third of the samples, DNA could be extracted from the powdered and lifted latents. Black fingerprint powder delivered the better result with a rate of 2.2% for full DNA profiles and profiles useful for exclusion in comparison with 1.8% for the magnetic powder traces. Isomark(®) (3.1%) yielded better results than gelatine foil (0.6%). © 2010 American Academy of Forensic Sciences.
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Weiss, Carine; Schröpfer, Daniel; Merten, Sonja
2016-08-11
Despite the successes of routine national childhood vaccination programmes, measles remains a public health concern. The purpose of this paper is to investigate how patterns of parental attitudes are linked to the decision-making process for or against MMR vaccination. This exploratory study was designed to identify distinct patterns of attitudes towards or against measles vaccination through Latent Class Analysis (LCA) in a sub-sample of mothers living in the canton of Aargau in Switzerland. Parents of young children below 36 months of age were randomly selected through parents' counsellors' registries. Among other questions, respondents were asked to state their agreement in response to 14 belief statements regarding measles vaccination on a 5-point Likert scale. To identify groups of parents showing distinct patterns of attitudes and beliefs regarding measles vaccination, we used Latent Class Analysis (LCA). The LCA showed three classes of parents with different attitudes and believes towards measles vaccination: The biggest group (class 1) are those having positive attitudes towards immunisation, followed by the second biggest group (class 2) which is characterised by having fearful attitudes and by showing uncertainty about immunisation. The third group (class 3) shows distinct patterns of critical attitudes against immunisation. Within this group over 90 % agree or totally agree that immunisation is an artificial intrusion into the natural immune system and therefore want to vaccinate their children only if necessary. We find that parents in the Canton Aargau who hesitate to vaccinate their children against measles, mumps and rubella show distinct opinions and attitudes. Health professionals should be aware of these perceptions to tailor their messages accordingly and positively influence these parents to vaccinate their children. Special attention needs to be given to those parents who are planning to vaccinate their children but are not following the
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Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2013-01-01
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
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Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena; vom Brocke, Jan
2016-01-01
While researchers have analysed the organisational competences that are required for successful Business Process Management (BPM) initiatives, individual BPM competences have not yet been studied in detail. In this study, latent semantic analysis is used to examine a collection of 1507 BPM-related job advertisements in order to develop a typology of BPM professionals. This empirical analysis reveals distinct ideal types and profiles of BPM professionals on several levels of abstraction. A closer look at these ideal types and profiles confirms that BPM is a boundary-spanning field that requires interdisciplinary sets of competence that range from technical competences to business and systems competences. Based on the study's findings, it is posited that individual and organisational alignment with the identified ideal types and profiles is likely to result in high employability and organisational BPM success.
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Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling
Raykov, Tenko; Marcoulides, George A.
2012-01-01
A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…
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Directory of Open Access Journals (Sweden)
Alison P. Lenton
2014-07-01
Full Text Available Generally, psychologists consider state authenticity– that is, the subjective sense of being one’s true self – to be a unitary and unidimensional construct, such that (a the phenomenological experience of authenticity is thought to be similar no matter its trigger, and (b inauthenticity is thought to be simply the opposing pole (on the same underlying construct of authenticity. Using latent class analysis, we put this conceptualization to a test. In order to avoid over-reliance on a Western conceptualization of authenticity, we used a cross-cultural sample (N = 543, comprising participants from Western, South-Asian, East-Asian, and South-East Asian cultures. Participants provided either a narrative in which the described when they felt most like being themselves or one in which they described when they felt least like being themselves. The analysis identified six distinct classes of experiences: two authenticity classes ('everyday' and 'extraordinary', three inauthenticity classes ('self-conscious,' 'deflated,' and 'extraordinary', and a class representing convergence between authenticity and inauthenticity. The classes were phenomenologically distinct, especially with respect to negative affect, private and public self-consciousness, and self-esteem. Furthermore, relatively more interdependent cultures were less likely to report experiences of extraordinary (inauthenticity than relatively more independent cultures. Understanding the many facets of (inauthenticity may enable researchers to connect different findings and explain why the attainment of authenticity can be difficult.
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Energy Technology Data Exchange (ETDEWEB)
Molitor, Christian; Mauracher, Stephan Gerhard; Rompel, Annette, E-mail: annette.rompel@univie.ac.at [Universität Wien, Althanstrasse 14, 1090 Wien (Austria)
2015-05-22
Latent and active aurone synthase purified from petals of C. grandiflora (cgAUS1) were crystallized. The crystal quality of recombinantly expressed latent cgAUS1 was significantly improved by co-crystallization with the polyoxotungstate Na{sub 6}[TeW{sub 6}O{sub 24}] within the liquid–liquid phase-separation zone. Aurone synthase (AUS), a member of a novel group of plant polyphenol oxidases (PPOs), catalyzes the oxidative conversion of chalcones to aurones. Two active cgAUS1 (41.6 kDa) forms that differed in the level of phosphorylation or sulfation as well as the latent precursor form (58.9 kDa) were purified from the petals of Coreopsis grandiflora. The differing active cgAUS1 forms and the latent cgAUS1 as well as recombinantly expressed latent cgAUS1 were crystallized, resulting in six different crystal forms. The active forms crystallized in space groups P2{sub 1}2{sub 1}2{sub 1} and P12{sub 1}1 and diffracted to ∼1.65 Å resolution. Co-crystallization of active cgAUS1 with 1,4-resorcinol led to crystals belonging to space group P3{sub 1}21. The crystals of latent cgAUS1 belonged to space group P12{sub 1}1 and diffracted to 2.50 Å resolution. Co-crystallization of recombinantly expressed pro-AUS with the hexatungstotellurate(VI) salt Na{sub 6}[TeW{sub 6}O{sub 24}] within the liquid–liquid phase separation zone significantly improved the quality of the crystals compared with crystals obtained without hexatungstotellurate(VI)
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International Nuclear Information System (INIS)
Yamaki, Tetsuya; Nuryanthi, Nuryanthi; Koshikawa, Hiroshi; Sawada, Shinichi; Hakoda, Teruyuki; Hasegawa, Shin; Asano, Masaharu; Maekawa, Yasunari
2012-01-01
High-energy heavy-ion induced damage, called latent tracks m organic polymers can sometimes be etched out chemically to give submicro- and nano-sized pores. Our focus is placed on ion-track membranes of poly(vinylidene fluoride) (PVDF), a type of fluoropolymer, which were previously considered as a matrix of polymer electrolyte fuel-cell membranes. There have been no optimized methods of preparing the PVDF-based ion-track membranes. We thus examined chemical structures of the defects created in the track, and accordingly, presented a pretreatment technique for achieving more efficient track etching. A 25 μm-thick PVDF film was bombarded with 1.1 GeV 238 U or 450 MeV 129 Xe ions. In the multi-purpose chamber, degradation processes were monitored in-situ by FT-IR spectroscopy and residual gas analysis as a function of the fluence up to 6.0 x 10 11 ions/cm 2 . The films irradiated at 8 ions/cm 2 were etched in a 9 M KOH aqueous solution at 80degC. We also performed the conductometric etching, which allows monitoring of pore evolution versus etching time by recording the electrical conductance through the membrane. At fluences above 1 x 10 10 ions/cm 2 , the film showed two new absorption bands identified as double-bond stretching vibrations of in-chain unsaturations -CH=CF- and fluorinated vinyl groups -CF 2 CH=CF 2 . These defects would result from the evolution of HF. The knowledge of the solubility in a permanganate alkaline solution and our preliminary experiment suggested the importance of oxidized tracks for the easy introduction of the etching agent. We finally found that the pretreatment with ozone could oxidize the double bonds in the tracks, thereby vigorously promoting track etching before breakthrough. (author)
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Latent lifestyle preferences and household location decisions
Walker, Joan L.; Li, Jieping
2007-04-01
Lifestyle, indicating preferences towards a particular way of living, is a key driver of the decision of where to live. We employ latent class choice models to represent this behavior, where the latent classes are the lifestyles and the choice model is the choice of residential location. Thus, we simultaneously estimate lifestyle groups and how lifestyle impacts location decisions. Empirical results indicate three latent lifestyle segments: suburban dwellers, urban dwellers, and transit-riders. The suggested lifestyle segments have intriguing policy implications. Lifecycle characteristics are used to predict lifestyle preferences, although there remain significant aspects that cannot be explained by observable variables.
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A Latent Class Analysis of Heterosexual Young Men’s Masculinities
Masters, N. Tatiana; Beadnell, Blair; Wells, Elizabeth A.; Morrison, Diane M.; Hoppe, Marilyn J.
2015-01-01
Parallel bodies of research have described the diverse and complex ways that men understand and construct their masculine identities (often termed“masculinities”) and, separately, how adherence to traditional notions of masculinity places men at risk for negative sexual and health outcomes. The goal of this analysis was to bring together these two streams of inquiry. Using data from a national, online sample of 555 hetero-sexually active young men, we employed latent class analysis (LCA) to detect patterns of masculine identities based on men’s endorsement of behavioral and attitudinal indicators of“dominant” masculinity, including sexual attitudes and behaviors. LCA identified four conceptually distinct masculine identity profiles. Twogroups, termed the Normative and Normative/Male Activities groups, respectively, constituted 88 % of the sample and were characterized by low levels of adherence to attitudes, sexual scripts, and behaviors consistent with“dominant”masculinity, but differed in their levels of engagement in male-oriented activities (e.g., sports teams). Only eight percent of the sample comprised a masculinity profile consistent with “traditional” ideas about masculinity; this group was labeled Misogynistic because of high levels of sexual assault and violence toward female partners. The remaining four percent constituted a Sex-Focused group, characterized by high numbers of sexual partners, but relatively low endorsement of other indicators of traditional masculinity. Follow-up analyses showed a small number of differences across groups on sexual and substance use health indicators. Findings have implications for sexual and behavioral health interventions and suggest that very few young men embody or endorse rigidly traditional forms of masculinity. PMID:26496914
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Tropical Gravity Wave Momentum Fluxes and Latent Heating Distributions
Geller, Marvin A.; Zhou, Tiehan; Love, Peter T.
2015-01-01
Recent satellite determinations of global distributions of absolute gravity wave (GW) momentum fluxes in the lower stratosphere show maxima over the summer subtropical continents and little evidence of GW momentum fluxes associated with the intertropical convergence zone (ITCZ). This seems to be at odds with parameterizations forGWmomentum fluxes, where the source is a function of latent heating rates, which are largest in the region of the ITCZ in terms of monthly averages. The authors have examined global distributions of atmospheric latent heating, cloud-top-pressure altitudes, and lower-stratosphere absolute GW momentum fluxes and have found that monthly averages of the lower-stratosphere GW momentum fluxes more closely resemble the monthly mean cloud-top altitudes rather than the monthly mean rates of latent heating. These regions of highest cloud-top altitudes occur when rates of latent heating are largest on the time scale of cloud growth. This, plus previously published studies, suggests that convective sources for stratospheric GW momentum fluxes, being a function of the rate of latent heating, will require either a climate model to correctly model this rate of latent heating or some ad hoc adjustments to account for shortcomings in a climate model's land-sea differences in convective latent heating.
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Institute of Scientific and Technical Information of China (English)
辛欣; 林钦佑; 魏骁驰; 黄河燕
2015-01-01
Data sparsity is a well-known challenge in recommender systems. Previous studies alleviate this problem by incorporating the information within the corresponding social media site. In this paper, we solve this challenge by exploring cross-site information. Specifically, we examine: 1) how to effectively and efficiently utilize cross-site ratings and content features to improve recommendation performance and 2) how to make the recommendation interpretable by utilizing content features. We propose a joint model of matrix factorization and latent topic analysis. Heterogeneous content features are modeled by multiple kinds of latent topics. In addition, the combination of matrix factorization and latent topics makes the recommendation result interpretable. Therefore, the above two issues are simultaneously solved. Through a real-world dataset, where user behaviors in three social media sites are collected, we demonstrate that the proposed model is effective in improving recommendation performance and interpreting the rationale of ratings.
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Latent period and temporal aspects of lung cancer among miners
International Nuclear Information System (INIS)
Sun Shiquan; Yang Xiaoou; Yang Lan; Meng Xianyu; Liu Shengen; You Zhanyun
1984-01-01
Data of lung cancer happened in the miners of this reported mine area is of great value to investigate the temporal aspects of miner's lung cancer, owing to its plenty of cases, longterm follow up and mining as child miners in early years before liberation of China. This preliminary analysis showed that the induction-latent period increased with the decrease of age at the year-of-first-employment in this mine and the protraction of follow up. In other words, even they were exposed since childhood, the excess of lung cancer never appeared until certain age for carcinogenesis. Therefore, the long-term follow up and comprehensive analysis of induction-latent period, underground duration-of-employment, time and age at start of mining would be helpful to properly estimating risk level, discovering the cause and predicting the trend of lung cancer incidence. There is no evidence to show whether child miners are more sensitive than adult miners working at the same exposure conditions
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Directory of Open Access Journals (Sweden)
Andrew Denovan
2018-01-01
Full Text Available This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief, belief in the paranormal (Revised Paranormal Belief Scale; RPBS and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy. Latent profile analysis (LPA identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample; class 2, moderate schizotypy and moderate paranormal belief (18.2%; class 3, moderate schizotypy (high cognitive disorganization and low paranormal belief (29%; and class 4, moderate schizotypy and high paranormal belief (8.9%. Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3 performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.
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Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew
2018-01-01
This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.
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Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.
2003-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs. S. America ) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model. Review of other latent heating algorithms will be discussed in the workshop.
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Learning Latent Vector Spaces for Product Search
Van Gysel, C.; de Rijke, M.; Kanoulas, E.
2016-01-01
We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations. The power of the model lies in its ability to directly model the discriminative relation between
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Ciampi, Antonio; Dyachenko, Alina; Cole, Martin; McCusker, Jane
2011-12-01
The study of mental disorders in the elderly presents substantial challenges due to population heterogeneity, coexistence of different mental disorders, and diagnostic uncertainty. While reliable tools have been developed to collect relevant data, new approaches to study design and analysis are needed. We focus on a new analytic approach. Our framework is based on latent class analysis and hidden Markov chains. From repeated measurements of a multivariate disease index, we extract the notion of underlying state of a patient at a time point. The course of the disorder is then a sequence of transitions among states. States and transitions are not observable; however, the probability of being in a state at a time point, and the transition probabilities from one state to another over time can be estimated. Data from 444 patients with and without diagnosis of delirium and dementia were available from a previous study. The Delirium Index was measured at diagnosis, and at 2 and 6 months from diagnosis. Four latent classes were identified: fairly healthy, moderately ill, clearly sick, and very sick. Dementia and delirium could not be separated on the basis of these data alone. Indeed, as the probability of delirium increased, so did the probability of decline of mental functions. Eight most probable courses were identified, including good and poor stable courses, and courses exhibiting various patterns of improvement. Latent class analysis and hidden Markov chains offer a promising tool for studying mental disorders in the elderly. Its use may show its full potential as new data become available.
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DEFF Research Database (Denmark)
Mahmmod, Yasser; Toft, Nils; Katholm, Jørgen
2013-01-01
threshold (Ct) values against bacterial culture (BC) for diagnosis of S. agalactiae IMI using latent class analysis to avoid the assumption of a perfect reference test. A total of 614 dairy cows were randomly selected from 6 herds with bulk tank PCR Ct value ≤ 39 for S. agalactiae and S. aureus. At milk...... cut-offs, indicating under estimation of S. agalactiae IMI in the examined dairy cows. In conclusion, Se of PCR is always higher than Se of BC at all tested cut-offs. The lower cut-off, the more comparable becomes Se of PCR and Se of BC. The changes in Se in both PCR and BC at different Ct-value cut...... definition of infection may reflect a more general condition of cows being positive for S. agalactiae. Our findings indicate that PCR Ct-value cut-offs should be chosen according to the underlying latent infection definition of interest. Latent class analysis proposes a useful alternative to classic test...
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Computerized summary scoring: crowdsourcing-based latent semantic analysis.
Li, Haiying; Cai, Zhiqiang; Graesser, Arthur C
2017-11-03
In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries. Researchers have proposed different formulations of the model summary in previous studies, such as pregraded summaries, expert-generated summaries, or source texts. The former two methods, however, require substantial human time, effort, and costs in order to either grade or generate summaries. Using source texts does not require human effort, but it also does not predict human summary scores well. With human summary scores as the gold standard, in this study we evaluated the crowdsourcing LSA method by comparing it with seven other LSA methods that used sets of summaries from different sources (either experts or crowdsourced) of differing quality, along with source texts. Results showed that crowdsourcing LSA predicted human summary scores as well as expert-good and crowdsourcing-good summaries, and better than the other methods. A series of analyses with different numbers of crowdsourcing summaries demonstrated that the number (from 10 to 100) did not significantly affect performance. These findings imply that crowdsourcing LSA is a promising approach to CSS, because it saves human effort in generating the model summary while still yielding comparable performance. This approach to small-scale CSS provides a practical solution for instructors in courses, and also advances research on automated assessments in which student responses are expected to semantically converge on subject matter content.
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Predominant typologies of psychopathology in the United States: a latent class analysis.
El-Gabalawy, Renée; Tsai, Jack; Harpaz-Rotem, Ilan; Hoff, Rani; Sareen, Jitender; Pietrzak, Robert H
2013-11-01
Latent class analysis (LCA) offers a parsimonious way of classifying common typologies of psychiatric comorbidity. We used LCA to identify the nature and correlates of predominant typologies of Axis I and II disorders in a large and comprehensive population-based sample of U.S. adults. We analyzed data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (2004-2005; n = 34,653), a population-based sample of U.S. adults. We derived latent classes based on all assessed Axis I and II disorders and examined the relationship between the identified Axis I classes and lifetime psychiatric disorders and suicide attempts, and physical and mental health-related quality of life. A four-class solution was optimal in characterizing predominant typologies of both Axis I and II disorders. For Axis I disorders, these included low psychopathology (n = 28,935, 84.0%), internalizing (n = 3693, 9.9%), externalizing (n = 1426, 4.5%), and high psychopathology (n = 599, 1.6%) classes. For Axis II disorders, these included no/low personality disorders (n = 31,265, 90.9%), obsessive/paranoid (n = 1635, 4.6%), borderline/dysregulated (n = 1319, 3.4%), and highly comorbid (n = 434, 1.1%) classes. Compared to the low psychopathology class, all other Axis I classes had significantly increased odds of mental disorders, elevated Axis II classes, suicide attempts and poorer quality of life, with the high psychopathology class having the overall highest rates of these correlates, with the exception of substance use disorders. Compared to the low psychopathology class, the internalizing and externalizing classes had increased rates of mood and anxiety disorders, and substance use disorders, respectively. Axis I and II psychopathology among U.S. adults may be best represented by four predominant typologies. Characterizing co-occurring patterns of psychopathology using person-based typologies represents a higher-order classification system that may be useful in clinical
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Sensible and latent heat forced divergent circulations in the West African Monsoon System
Hagos, S.; Zhang, C.
2008-12-01
Field properties of divergent circulation are utilized to identify the roles of various diabatic processes in forcing moisture transport in the dynamics of the West African Monsoon and its seasonal cycle. In this analysis, the divergence field is treated as a set of point sources and is partitioned into two sub-sets corresponding to latent heat release and surface sensible heat flux at each respective point. The divergent circulation associated with each set is then calculated from the Poisson's equation using Gauss-Seidel iteration. Moisture transport by each set of divergent circulation is subsequently estimated. The results show different roles of the divergent circulations forced by surface sensible and latent heating in the monsoon dynamics. Surface sensible heating drives a shallow meridional circulation, which transports moisture deep into the continent at the polar side of the monsoon rain band and thereby promotes the seasonal northward migration of monsoon precipitation during the monsoon onset season. In contrast, the circulation directly associated with latent heating is deep and the corresponding moisture convergence is within the region of precipitation. Latent heating also induces dry air advection from the north. Neither effect promotes the seasonal northward migration of precipitation. The relative contributions of the processes associated with latent and sensible heating to the net moisture convergence, and hence the seasonal evolution of monsoon precipitation, depend on the background moisture.
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Cytokine profile in patients with early latent syphilis
Directory of Open Access Journals (Sweden)
Zakharov S.V.
2018-03-01
Full Text Available The purpose of this study was to study the change in the content of the most active cytokines (interleukins 6 and 10 during the formation of the immune response in patients with latent early syphilis, as well as to study the possible relationship between the concentrations of these cytokines and the duration of the disease. In 50 patients with early latent syphilis, the concentration of interleukins 6 and 10 in serum was studied. The serum level of interleukins was studied by the enzyme immunoassay. A statistically significant increase in the concentration of interleukin 6 in the blood of patients with latent syphilis and decrease in the interleukin 10 concentration in comparison with healthy people was established. At the same time, in patients with latent syphilis with term of infection for more than 1 year, interleukin 10 has been expressed, as compared with healthy people and, especially, with patients with syphilis with a duration of infection of up to 1 year. Along with this, a lower degree of increase in the concentration of interleukin 6 in patients with latent syphilis with a duration of infection over 1 year has been established, as compared with patients with latent syphilis with a term of infection up to 1 year, against the background of its increased concentration as compared with a group of healthy individuals.
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Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M
2017-05-01
Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.
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Rinker, Dipali Venkataraman; Diamond, Pamela M; Walters, Scott T; Wyatt, Todd M; DeJong, William
2016-09-01
: First-year college students are at particular risk for experiencing negative alcohol-related consequences that may set the stage for experiencing such consequences in later life. Latent class analysis is a person-centered approach that, based on observable indicator variables, divides a population into mutually exclusive and exhaustive groups ('classes'). To date, no studies have examined the latent class structure of negative alcohol-related consequences experienced by first-year college students just before entering college. The aims of this study were to (a) identify classes of first-year college students based on the patterns of negative alcohol-related consequences they experienced just before entering college, and (b) determine whether specific covariates were associated with class membership. Incoming freshmen from 148 colleges and universities (N = 54,435) completed a baseline questionnaire as part of an alcohol education program they completed just prior to their first year of college. Participants answered questions regarding demographics and other personal characteristics, their alcohol use in the past 2 weeks, and the negative alcohol-related consequences they had experienced during that time. Four distinct classes of students emerged: (a) No Problems, (b) Academic Problems, (c) Injured Self and (d) Severe Problems. Average number of drinks per drinking day, total number of drinking days, age of drinking initiation, intention to join a fraternity or sorority and family history of alcohol problems were associated with membership in all of the problem classes relative to the No Problems class. These results can inform future campus-based prevention efforts. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.
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Energy Technology Data Exchange (ETDEWEB)
Theissen, P. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Kaldewey, S. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Moka, D. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Bunke, J. (Philips Medizin Systeme, Hamburg (Germany)); Voth, E. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Schicha, H. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany))
1993-06-01
[sup 31]Phosphorous magnetic resonance spectroscopy allows an in vivo examination of energy metabolism. The present study was designed to evaluate whether in patients with latent hyperthyroidism alterations of muscle energy metabolism could be found similar to those observed in patients with overt hyperthyroidism. In 10 patients with overt hyperthyroidism before therapy and 20 with latent hyperthyroidism (also without therapy) and in 24 healthy volunteers magnetic resonance spectroscopy of the calf muscle was performed within a 1.5-Tesla magnet. Muscle concentrations of phosphocreatine, inorganic phosphate, and ATP were quantified compared to an external standard solution of K[sub 2]HPO[sub 4]. In the patients with overt hyperthyroidism and with latent hyperthyroidism a significant decrease of phosphocreatine was found. Further, the ATP concentration in patients with latent and manifest hyperthyroidism tended towards lower values. There were no significant differences in the decrease of phosphocreatine and ATP between both patient groups. Therefore, this study for the first time shows that alterations of energy metabolism in latent hyperthyroidism can be measured and that they are similar to those observed in overt hyperthyroidism. (orig.)
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Choi, Wan-Suk; Moon, Ok-Kon; Yeum, Dong-Moon
2017-10-07
This study investigated the characteristics and health behavior profiles of 1,803 workers who had experienced industrial accidents. Average weekly exercise days, average number of cigarettes smoked per day, average daily sleep duration, and number of days of alcohol consumption were selected to investigate health behavior profiles. Specifically, latent profile analysis was applied to identify the health behavior profiles of people who had completed industrial accident care; the latent classes were the health-conscious type (n=240), the potential-risk type (n=850), and the high-risk type (n=713). Comparison of the health-conscious and potential-risk types indicated that younger subjects, the employed, and those with lower social status and life satisfaction were more likely to be the potential-risk type. Comparison of the health-conscious and high-risk types revealed that males, younger subjects, the employed, those without chronic illnesses, and those with lower social status and life satisfaction were more likely to be the high-risk type. The results suggest that industrial accident victims who have completed accident care have different health behaviors and it is necessary to improve health promotion based on health type characteristics.
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Hajebi, Ahmad; Abbasi-Ghahramanloo, Abbas; Hashemian, Seyed Sepehr; Khatibi, Seyed Reza; Ghasemzade, Masomeh; Khodadost, Mahmoud
2017-09-01
Suicide is one the most important public health problem which is rapidly growing concerns. The aim of this study was to subgroup suicide using LCA method. This cross-sectional study was conducted in Iran based on 66990 records registered in Ministry of Health in 2014. A case report questionnaire in the form of software was used for case registries. Latent class analysis was used to achieve the research objectives. Four latent classes were identified; (a) Non-lethal attempters without a history of psychiatric disorders, (b) Non-lethal attempters with a history of psychiatric disorders, (c) Lethal attempters without a history of psychiatric disorders, (d) Lethal attempters with a history of psychiatric disorders. The probability of completed/an achieved suicide is high in lethal attempter classes. Being male increases the risk of inclusion in lethal attempters' classes (OR = 4.93). Also, being single (OR = 1.16), having an age lower than 25 years (OR = 1.14) and being a rural citizen (OR = 2.36) associate with lethal attempters classes. The males tend to use more violent methods and have more completed suicide. Majority of the individuals are non-lethal attempters who need to be addressed by implementing preventive interventions and mental support provision. Copyright © 2017. Published by Elsevier B.V.
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Hosmane, Nina N.; Kwon, Kyungyoon J.; Bruner, Katherine M.; Capoferri, Adam A.; Rosenbloom, Daniel I.S.; Keele, Brandon F.; Ho, Ya-Chi
2017-01-01
A latent reservoir for HIV-1 in resting CD4+ T lymphocytes precludes cure. Mechanisms underlying reservoir stability are unclear. Recent studies suggest an unexpected degree of infected cell proliferation in vivo. T cell activation drives proliferation but also reverses latency, resulting in productive infection that generally leads to cell death. In this study, we show that latently infected cells can proliferate in response to mitogens without producing virus, generating progeny cells that can release infectious virus. Thus, assays relying on one round of activation underestimate reservoir size. Sequencing of independent clonal isolates of replication-competent virus revealed that 57% had env sequences identical to other isolates from the same patient. Identity was confirmed by full-genome sequencing and was not attributable to limited viral diversity. Phylogenetic and statistical analysis suggested that identical sequences arose from in vivo proliferation of infected cells, rather than infection of multiple cells by a dominant viral species. The possibility that much of the reservoir arises by cell proliferation presents challenges to cure. PMID:28341641
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Hosmane, Nina N; Kwon, Kyungyoon J; Bruner, Katherine M; Capoferri, Adam A; Beg, Subul; Rosenbloom, Daniel I S; Keele, Brandon F; Ho, Ya-Chi; Siliciano, Janet D; Siliciano, Robert F
2017-04-03
A latent reservoir for HIV-1 in resting CD4 + T lymphocytes precludes cure. Mechanisms underlying reservoir stability are unclear. Recent studies suggest an unexpected degree of infected cell proliferation in vivo. T cell activation drives proliferation but also reverses latency, resulting in productive infection that generally leads to cell death. In this study, we show that latently infected cells can proliferate in response to mitogens without producing virus, generating progeny cells that can release infectious virus. Thus, assays relying on one round of activation underestimate reservoir size. Sequencing of independent clonal isolates of replication-competent virus revealed that 57% had env sequences identical to other isolates from the same patient. Identity was confirmed by full-genome sequencing and was not attributable to limited viral diversity. Phylogenetic and statistical analysis suggested that identical sequences arose from in vivo proliferation of infected cells, rather than infection of multiple cells by a dominant viral species. The possibility that much of the reservoir arises by cell proliferation presents challenges to cure. © 2017 Hosmane et al.
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Residents’ attitudes toward tourism development: A structural model via Akcakoca sample
Erol Duran; Emrah Özkul
2012-01-01
The objective of this study is to showcase a structural model that explores residents’ attitudes towards sustainable tourism development. Factors influencing residents’ attitudes were examined using a model consisting five latent constructs and six path hypotheses. Within this context, findings from 300 resident-respondents from Akcakoca, Turkey were analyzed. Utilizing LISREL 8,54 structural equation analysis package, a confirmatory factor analysis and path analysis were performed successi...
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A developmental study of latent absolute pitch memory.
Jakubowski, Kelly; Müllensiefen, Daniel; Stewart, Lauren
2017-03-01
The ability to recall the absolute pitch level of familiar music (latent absolute pitch memory) is widespread in adults, in contrast to the rare ability to label single pitches without a reference tone (overt absolute pitch memory). The present research investigated the developmental profile of latent absolute pitch (AP) memory and explored individual differences related to this ability. In two experiments, 288 children from 4 to12 years of age performed significantly above chance at recognizing the absolute pitch level of familiar melodies. No age-related improvement or decline, nor effects of musical training, gender, or familiarity with the stimuli were found in regard to latent AP task performance. These findings suggest that latent AP memory is a stable ability that is developed from as early as age 4 and persists into adulthood.
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Classification criteria of syndromes by latent variable models
DEFF Research Database (Denmark)
Petersen, Janne
2010-01-01
patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...... standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...
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Emotional labor actors: a latent profile analysis of emotional labor strategies.
Gabriel, Allison S; Daniels, Michael A; Diefendorff, James M; Greguras, Gary J
2015-05-01
Research on emotional labor focuses on how employees utilize 2 main regulation strategies-surface acting (i.e., faking one's felt emotions) and deep acting (i.e., attempting to feel required emotions)-to adhere to emotional expectations of their jobs. To date, researchers largely have considered how each strategy functions to predict outcomes in isolation. However, this variable-centered perspective ignores the possibility that there are subpopulations of employees who may differ in their combined use of surface and deep acting. To address this issue, we conducted 2 studies that examined surface acting and deep acting from a person-centered perspective. Using latent profile analysis, we identified 5 emotional labor profiles-non-actors, low actors, surface actors, deep actors, and regulators-and found that these actor profiles were distinguished by several emotional labor antecedents (positive affectivity, negative affectivity, display rules, customer orientation, and emotion demands-abilities fit) and differentially predicted employee outcomes (emotional exhaustion, job satisfaction, and felt inauthenticity). Our results reveal new insights into the nature of emotion regulation in emotional labor contexts and how different employees may characteristically use distinct combinations of emotion regulation strategies to manage their emotional expressions at work. (c) 2015 APA, all rights reserved.
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van den Akker, A.L.; Deković, M.; Asscher, J.J.; Shiner, R.L.; Prinzie, P.
2013-01-01
This study investigated relations among children's personality types, trajectories of internalizing and externalizing problems, and overreactive parenting across 6 years. Latent Class Analysis of the Big 5 personality dimensions (modeled as latent factors, based on mother, father and teacher
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A Probability Distribution over Latent Causes, in the Orbitofrontal Cortex.
Chan, Stephanie C Y; Niv, Yael; Norman, Kenneth A
2016-07-27
The orbitofrontal cortex (OFC) has been implicated in both the representation of "state," in studies of reinforcement learning and decision making, and also in the representation of "schemas," in studies of episodic memory. Both of these cognitive constructs require a similar inference about the underlying situation or "latent cause" that generates our observations at any given time. The statistically optimal solution to this inference problem is to use Bayes' rule to compute a posterior probability distribution over latent causes. To test whether such a posterior probability distribution is represented in the OFC, we tasked human participants with inferring a probability distribution over four possible latent causes, based on their observations. Using fMRI pattern similarity analyses, we found that BOLD activity in the OFC is best explained as representing the (log-transformed) posterior distribution over latent causes. Furthermore, this pattern explained OFC activity better than other task-relevant alternatives, such as the most probable latent cause, the most recent observation, or the uncertainty over latent causes. Our world is governed by hidden (latent) causes that we cannot observe, but which generate the observations we see. A range of high-level cognitive processes require inference of a probability distribution (or "belief distribution") over the possible latent causes that might be generating our current observations. This is true for reinforcement learning and decision making (where the latent cause comprises the true "state" of the task), and for episodic memory (where memories are believed to be organized by the inferred situation or "schema"). Using fMRI, we show that this belief distribution over latent causes is encoded in patterns of brain activity in the orbitofrontal cortex, an area that has been separately implicated in the representations of both states and schemas. Copyright © 2016 the authors 0270-6474/16/367817-12$15.00/0.
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Golumbeanu, Monica; Cristinelli, Sara; Rato, Sylvie; Munoz, Miguel; Cavassini, Matthias; Beerenwinkel, Niko; Ciuffi, Angela
2018-04-24
Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle toward HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV-infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
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Latent profile analysis of sixth graders based on teacher ratings: Association with school dropout.
Orpinas, Pamela; Raczynski, Katherine; Peters, Jaclyn Wetherington; Colman, Laura; Bandalos, Deborah
2015-12-01
The goal of this study was to identify meaningful groups of sixth graders with common characteristics based on teacher ratings of assets and maladaptive behaviors, describe dropout rates for each group, and examine the validity of these groups using students' self-reports. The sample consisted of racially diverse students (n = 675) attending sixth grade in public schools in Northeast Georgia. The majority of the sample was randomly selected; a smaller group was identified by teachers as high risk for aggression. Based on teacher ratings of externalizing behaviors, internalizing problems, academic skills, leadership, and social assets, latent profile analysis yielded 7 classes that can be displayed along a continuum: Well-Adapted, Average, Average-Social Skills Deficit, Internalizing, Externalizing, Disruptive Behavior with School Problems, and Severe Problems. Dropout rate was lowest for the Well-adapted class (4%) and highest for the Severe Problems class (58%). However, students in the Average-Social Skills Deficit class did not follow the continuum, with a large proportion of students who abandoned high school (29%). The proportion of students identified by teachers as high in aggression consistently increased across the continuum from none in the Well-Adapted class to 84% in the Severe Problems class. Students' self-reports were generally consistent with the latent profile classes. Students in the Well-Adapted class reported low aggression, drug use, and delinquency, and high life satisfaction; self-reports went in the opposite direction for the Disruptive Behaviors with School Problems class. Results highlight the importance of early interventions to improve academic performance, reduce externalizing behaviors, and enhance social assets. (c) 2015 APA, all rights reserved).
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Trajectories of acute low back pain: a latent class growth analysis.
Downie, Aron S; Hancock, Mark J; Rzewuska, Magdalena; Williams, Christopher M; Lin, Chung-Wei Christine; Maher, Christopher G
2016-01-01
Characterising the clinical course of back pain by mean pain scores over time may not adequately reflect the complexity of the clinical course of acute low back pain. We analysed pain scores over 12 weeks for 1585 patients with acute low back pain presenting to primary care to identify distinct pain trajectory groups and baseline patient characteristics associated with membership of each cluster. This was a secondary analysis of the PACE trial that evaluated paracetamol for acute low back pain. Latent class growth analysis determined a 5 cluster model, which comprised 567 (35.8%) patients who recovered by week 2 (cluster 1, rapid pain recovery); 543 (34.3%) patients who recovered by week 12 (cluster 2, pain recovery by week 12); 222 (14.0%) patients whose pain reduced but did not recover (cluster 3, incomplete pain recovery); 167 (10.5%) patients whose pain initially decreased but then increased by week 12 (cluster 4, fluctuating pain); and 86 (5.4%) patients who experienced high-level pain for the whole 12 weeks (cluster 5, persistent high pain). Patients with longer pain duration were more likely to experience delayed recovery or nonrecovery. Belief in greater risk of persistence was associated with nonrecovery, but not delayed recovery. Higher pain intensity, longer duration, and workers' compensation were associated with persistent high pain, whereas older age and increased number of episodes were associated with fluctuating pain. Identification of discrete pain trajectory groups offers the potential to better manage acute low back pain.
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Wang, Hsueh-Cheng; Hsu, Li-Chuan; Tien, Yi-Min; Pomplun, Marc
2013-01-01
The morphological constituents of English compounds (e.g., “butter” and “fly” for “butterfly”) and two-character Chinese compounds may differ in meaning from the whole word. Subjective differences and ambiguity of transparency make the judgments difficult, and a computational alternative based on a general model may be a way to average across subjective differences. The current study proposes two approaches based on Latent Semantic Analysis (Landauer & Dumais, 1997): Model 1 compares the semantic similarity between a compound word and each of its constituents, and Model 2 derives the dominant meaning of a constituent based on a clustering analysis of morphological family members (e.g., “butterfingers” or “buttermilk” for “butter”). The proposed models successfully predicted participants’ transparency ratings, and we recommend that experimenters use Model 1 for English compounds and Model 2 for Chinese compounds, due to raters’ morphological processing in different writing systems. The dominance of lexical meaning, semantic transparency, and the average similarity between all pairs within a morphological family are provided, and practical applications for future studies are discussed. PMID:23784009
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Validation of an employee satisfaction model: A structural equation model approach
Directory of Open Access Journals (Sweden)
Ophillia Ledimo
2015-01-01
Full Text Available The purpose of this study was to validate an employee satisfaction model and to determine the relationships between the different dimensions of the concept, using the structural equation modelling approach (SEM. A cross-sectional quantitative survey design was used to collect data from a random sample of (n=759 permanent employees of a parastatal organisation. Data was collected using the Employee Satisfaction Survey (ESS to measure employee satisfaction dimensions. Following the steps of SEM analysis, the three domains and latent variables of employee satisfaction were specified as organisational strategy, policies and procedures, and outcomes. Confirmatory factor analysis of the latent variables was conducted, and the path coefficients of the latent variables of the employee satisfaction model indicated a satisfactory fit for all these variables. The goodness-of-fit measure of the model indicated both absolute and incremental goodness-of-fit; confirming the relationships between the latent and manifest variables. It also indicated that the latent variables, organisational strategy, policies and procedures, and outcomes, are the main indicators of employee satisfaction. This study adds to the knowledge base on employee satisfaction and makes recommendations for future research.
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Cyclist–motorist crash patterns in Denmark: A latent class clustering approach
DEFF Research Database (Denmark)
Kaplan, Sigal; Prato, Carlo Giacomo
2013-01-01
to prioritize safety issues and to devise efficient preventive measures. Method: The current study focused on cyclist–motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic...
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Morphometry of latent palmprints as a function of time.
Barros, Rodrigo M; Faria, Bruna E F; Kuckelhaus, Selma A S
2013-12-01
In many crimes, the elapsed time between production and collecting fingermark traces is crucial. and a method able to detect the aging of latent prints would represent an improvement in forensic procedures. Considering that as the latent print gets older, substantial changes in the relative proportion of individual components secreted by skin glands could affect the morphology of ridges, morphometry could be a potential tool to assess the aging of latent fingermarks. Then, considering the very limited research in the field, the present work aims to evaluate the morphometry of latent palmprint ridges, as a function of time, in order to identify an aging pattern. The latent marks were deposited by 20 donors on glass microscope slides considering pressure and contact angle, and then were maintained under controlled environmental conditions. The morphometric study was conducted on marks developed with magnetic powder in 7 different time intervals after deposition (0, 5, 10, 15, 20, 25 or 30 days); 60 ridges were evaluated for each developed mark. The results showed that: 1) the method for the replacement and mixing of skin secretions on the palm was appropriate to ensure reproducibility of latent prints, and 2) considering the studied group, there was a time-dependent reduction in the width of ridges and on the percentage of visible ridges over 30 days. Results suggest the possibility of using the morphometric method to determine an aging profile of latent palmprints on glass surface, aiming for forensic purposes. © 2013.
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Johnson, Ursula Y.; Hull, Darrell M.
2014-01-01
The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…
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Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.
2002-01-01
NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2001. Rainfall, latent heating and radar reflectivity structures between El Nino (DE 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs. west Pacific, Africa vs. S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in strtaiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. The Goddard Cumulus Ensemble Model is being used to simulate various mesoscale convective systems that developed in different geographic locations. Specifically, the model estimated rainfall, radar reflectivity and latent heating profiles will be compared to observational data collected from TRMM field campaigns over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and the central Pacific in 1999 (KWAJEX). Sounding diagnosed heating budgets and radar reflectivity from these experiments can provide the means to validate (heating product) as well as improve the GCE model.
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Bourdier, L; Morvan, Y; Kotbagi, G; Kern, L; Romo, L; Berthoz, S
2018-04-01
It is now recognized that emotions can influence food intake. While some people report eating less when distressed, others report either no change of eating or eating more in the same condition. The question whether this interindividual variability also occurs in response to positive emotions has been overlooked in most studies on Emotional Eating (EE). Using the Emotional Appetite Questionnaire (EMAQ) and Latent Profile Analysis, this study aimed to examine the existence of latent emotion-induced changes in eating profiles, and explore how these profiles differ by testing their relations with 1) age and sex, 2) BMI and risk for eating disorders (ED) and 3) factors that are known to be associated with EE such as perceived positive/negative feelings, depression, anxiety, stress symptoms and impulsivity. Among 401 university students (245 females) who completed the EMAQ, 3 profiles emerged (P1:11.2%, P2:60.1%, P3:28.7%), with distinct patterns of eating behaviors in response to negative emotions and situations but few differences regarding positive ones. Negative emotional overeaters (P1) and negative emotional undereaters (P3) reported similar levels of emotional distress and positive feelings, and were at greater risk for ED. However, the people in the former profile i) reported decreasing their food intake in a positive context, ii) were in majority females, iii) had higher BMI and iv) were more prone to report acting rashly when experiencing negative emotions. Our findings suggest that a person-centred analysis of the EMAQ scores offers a promising way to capture the inter-individual variability of emotionally-driven eating behaviors. These observations also add to the growing literature underscoring the importance of further investigating the role of different facets of impulsivity in triggering overeating and to develop more targeted interventions of EE. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Incorporating direct marketing activity into latent attrition models
Schweidel, David A.; Knox, George
2013-01-01
When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,
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Tseng, Mei-Chih Meg; Hu, Fu-Chang
2012-01-01
The implications of impulsivity in its relationship with binge-eating or purging behaviors remain unclear. This study examined the patterns of eating behaviors and co-morbid impulsive behaviors in individuals with bulimia nervosa n optimally homogeneous classes using latent class analysis (LCA). All participants (n=180) were asked to complete a series of self-reported inventories of impulsive behaviors and other psychological measures. Information regarding the lifetime presence of symptoms of eating disorder was assessed by clinical interviews. LCA was conducted using eating disorder symptoms, impulsive behaviors, and the number of purging methods. Three latent classes of bulimic women were identified. These were women who exhibited relatively higher rates of purging, symptoms of impulsive behavior, and multiple purging methods (17.8%), women who used no more than one purging method with a low occurrence of impulsive behavior (41.7%), and women who showed higher rates of purging behaviors and the use of multiple purging methods with a low rate of impulsive behavior (41.7%). The impulsive sub-group had comparable severity of eating-related measures, frequency of binge-eating, and higher levels of general psychopathology than that of the other two sub-groups. This study provides empirical support for the existence of an impulsive subgroup with distinctive features among a non-Western group of BN patients. This study also suggests that mechanisms other than impulse dysregulation may exist for the development of binge-eating and purging behaviors in bulimia nervosa patients, or the mechanisms contributing to binge-eating and impulsive behaviors may be different. Copyright © 2011 Elsevier Inc. All rights reserved.
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Multiple murder and criminal careers: a latent class analysis of multiple homicide offenders.
Vaughn, Michael G; DeLisi, Matt; Beaver, Kevin M; Howard, Matthew O
2009-01-10
To construct an empirically rigorous typology of multiple homicide offenders (MHOs). The current study conducted latent class analysis of the official records of 160 MHOs sampled from eight states to evaluate their criminal careers. A 3-class solution best fit the data (-2LL=-1123.61, Bayesian Information Criterion (BIC)=2648.15, df=81, L(2)=1179.77). Class 1 (n=64, class assignment probability=.999) was the low-offending group marked by little criminal record and delayed arrest onset. Class 2 (n=51, class assignment probability=.957) was the severe group that represents the most violent and habitual criminals. Class 3 (n=45, class assignment probability=.959) was the moderate group whose offending careers were similar to Class 2. A sustained criminal career with involvement in versatile forms of crime was observed for two of three classes of MHOs. Linkages to extant typologies and recommendations for additional research that incorporates clinical constructs are proffered.
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Identifying person-fit latent classes, and explanation of categorical and continuous person misfit
Conijn, J.M.; Sijtsma, K.; Emons, W.H.M.
2016-01-01
Latent class (LC) cluster analysis of a set of subscale lz person-fit statistics was proposed to explain person misfit on multiscale measures. The proposed explanatory LC person-fit analysis was used to analyze data of students (N = 91,648) on the nine-subscale School Attitude Questionnaire Internet
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Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling
Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon
2010-01-01
This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639
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Lehman, Li-Wei; Long, William; Saeed, Mohammed; Mark, Roger
2014-01-01
Patients in critical care often exhibit complex disease patterns. A fundamental challenge in clinical research is to identify clinical features that may be characteristic of adverse patient outcomes. In this work, we propose a data-driven approach for phenotype discovery of patients in critical care. We used Hierarchical Dirichlet Process (HDP) as a non-parametric topic modeling technique to automatically discover the latent "topic" structure of diseases, symptoms, and findings documented in hospital discharge summaries. We show that the latent topic structure can be used to reveal phenotypic patterns of diseases and symptoms shared across subgroups of a patient cohort, and may contain prognostic value in stratifying patients' post hospital discharge mortality risks. Using discharge summaries of a large patient cohort from the MIMIC II database, we evaluate the clinical utility of the discovered topic structure in identifying patients who are at high risk of mortality within one year post hospital discharge. We demonstrate that the learned topic structure has statistically significant associations with mortality post hospital discharge, and may provide valuable insights in defining new feature sets for predicting patient outcomes.
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Mental toughness latent profiles in endurance athletes.
Directory of Open Access Journals (Sweden)
Joanna S Zeiger
Full Text Available Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female. Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ, Psychological Performance Inventory-Alternative (PPI-A, and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE. A three-class solution emerged, designated as high mental toughness (High MT, moderate mental toughness (Moderate MT and low mental toughness (Low MT. ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; P<0.001, athletes who were over 55 compared to those who were 18-34 (OR = 2.52; 95% CI, 1.37, 4.62; P<0.01, high sports satisfaction (OR = 8.17; 95% CI, 5.63, 11.87; P<0.001, and high division placement (OR = 2.18; 95% CI, 1.46,3.26; P<0.001. The data showed that mental toughness latent profiles exist in endurance athletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training.
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Latent fingerprints on different type of screen protective films
Directory of Open Access Journals (Sweden)
Yuttana Sudjaroen
2016-07-01
Full Text Available The purpose of this research was to study the quality of latent fingerprint on different types of screen protective films including screen protector, matte screen protector, anti-fingerprint clear screen protector and anti-fingerprint matte screen protector by using black powder method in developing latent fingerprints. The fingerprints were performed by 10 volunteers whose fingers (right index, right thumb, left index and left thumb were stubbing at different types of screen protective films and subsequently latent fingerprints were developed by brushing with black powder. Automated Fingerprint Identification System (AFIS counted the numbers of minutiae points from 320 latent fingerprints. Anti-fingerprint matte screen protective film produced the best quality of latent fingerprint with an average minutiae point 72.65, followed by matte screen protective film, clear screen protective film and anti-fingerprint clear screen protective film with an average minutiae point of 155.2, 135.0 and 72.65 respectively. The quality of latent fingerprints developed between a clear and a matte surface of screen protective films showed a significant difference (sig>0.05, whereas the coat and the non-coat with anti-fingerprint chemical revealed a non-significant difference (sig<0.05 in their number of minutiae points.
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Park, Mi Jin; Park, Nan Sook; Chiriboga, David A
2018-05-01
This study presents an empirical typology of social activity and its association with the depressive symptoms and self-rated health of community-dwelling older adults (n = 464) in South Korea. Latent class analysis (LCA) was used to classify the types of social activities. Data analyses were conducted using Mplus 7.2 program for LCA and SPSS 22.0 for multiple regression analyses. LCA identified people who fell into one of the four activity groups: Diverse, Community Center/Disengaged, Religion Plus, and Friendship/Leisure. Membership in these four groups predicted differences in depressive symptoms and self-rated health. Results indicate that typologies of social activity could enhance practitioners' understanding of activity patterns and their associations with health and well-being.
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Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F
2014-11-01
Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.
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Fu, Yurong; Yi, Zhengjun; Li, Jianhua; Li, Ruifang
2014-03-01
The mechanisms of latent tuberculosis (TB) infection remain elusive. Roles of microRNA (miRNA) have been highlighted in pathogen-host interactions recently. To identify miRNAs involved in the immune response to TB, expression profiles of miRNAs in CD4(+) T cells from patients with latent TB, active TB and healthy controls were investigated by microarray assay and validated by RT-qPCR. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyse the significant functions and involvement in signalling pathways of the differentially expressed miRNAs. To identify potential target genes for miR-29, interferon-γ (IFN-γ) mRNA expression was measured by RT-qPCR. Our results showed that 27 miRNAs were deregulated among the three groups. RT-qPCR results were generally consistent with the microarray data. We observed an inverse correlation between miR-29 level and IFN-γ mRNA expression in CD4(+) T cells. GO and KEGG pathway analysis showed that the possible target genes of deregulated miRNAs were significantly enriched in mitogen-activated protein kinase signalling pathway, focal adhesion and extracellular matrix receptor interaction, which might be involved in the transition from latent to active TB. In all, for the first time, our study revealed that some miRNAs in CD4(+) T cells were altered in latent and active TB. Function and pathway analysis highlighted the possible involvement of miRNA-deregulated mRNAs in TB. The study might help to improve understanding of the relationship between miRNAs in CD4(+) T cells and TB, and laid an important foundation for further identification of the underlying mechanisms of latent TB infection and its reactivation. © 2013 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.
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Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M
2016-09-01
Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.
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Rothschild, Anthony J.; Lapane, Kate L.
2016-01-01
Abstract Objective: To characterize the association between functional impairment and major depression subtypes at baseline and to characterize changes in subtypes by functional impairment level in women receiving citalopram in level 1 of the Sequenced Treatment Alternatives to Relieve Depression trial. Method: Women who completed baseline and week 12 study visits were included. Items from the self-reported Quick Inventory of Depressive Symptomatology were used to define the latent depression subtypes. The Work and Social Adjustment Scale was used to classify baseline functional impairment. A latent transition analysis model provided estimates of the prevalence of subtype membership and transition probabilities by functional impairment level. Results: Of the 755 women included, 69% had major functional impairment at baseline. Regardless of functional impairment level, the subtypes were differentiated by depression severity, appetite changes, psychomotor disturbances, and insomnia. Sixty-seven percent of women with normal/significant functional impairment and 60% of women with major impairment were likely to transition to a symptom resolution subtype at week 12. Women with baseline major impairment who were in the severe with psychomotor agitation subtype at the beginning of the study were least likely to transition to the symptom resolution subtype (4% chance). Conclusions: Functional impairment level was related to both the baseline depression subtype and the likelihood of moving to a different subtype. These results underscore the need to incorporate not only depression symptoms but also functioning in the assessment and treatment of depression. PMID:26488110
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Prevalence and risk factors of latent Tuberculosis among ...
African Journals Online (AJOL)
Background: Latent Tuberculosis treatment is a key tuberculosis control intervention. Adolescents are a high risk group that is not routinely treated in low income countries. Knowledge of latent Tuberculosis (TB) burden among adolescents may influence policy. Objectives: We determined the prevalence and risk factors of ...
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A Latent Profile Analysis of Latino Parenting: The Infusion of Cultural Values on Family Conflict.
Ayón, Cecilia; Williams, Lela Rankin; Marsiglia, Flavio F; Ayers, Stephanie; Kiehne, Elizabeth
The purpose of the present study was to (a) examine how acculturation and social support inform Latinos' parenting behaviors, controlling for gender and education; (b) describe parenting styles among Latino immigrants while accounting for cultural elements; and (c) test how these parenting styles are associated with family conflict. A 3 step latent profile analysis with the sample ( N = 489) revealed best fit with a 4 profile model ( n = 410) of parenting: family parenting ( n = 268, 65%), child-centered parenting ( n = 68, 17%), moderate parenting ( n = 60, 15%), and disciplinarian parenting ( n = 14, 3%). Parents' gender, acculturation, and social support significantly predicted profile membership. Disciplinarian and moderate parenting were associated with more family conflict. Recommendations include integrating culturally based parenting practices as a critical element to family interventions to minimize conflict and promote positive youth development.
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Utzinger, Linsey M; Haukebo, Justine E; Simonich, Heather; Wonderlich, Stephen A; Cao, Li; Lavender, Jason M; Mitchell, James E; Engel, Scott G; Crosby, Ross D
2016-07-01
The aim of this study was to empirically examine naturally occurring groups of individuals with bulimia nervosa (BN) based on their childhood trauma (CT) histories and to compare these groups on a clinically relevant external validator, borderline personality disorder (BPD) psychopathology. This study examined the relationship between CT and BPD psychopathology among 133 women with BN using latent profile analysis (LPA) to classify participants based on histories of CT. Participants completed the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I/P), the Diagnostic Interview for Borderlines-Revised (DIB-R), and the Childhood Trauma Questionnaire (CTQ). The LPA revealed four trauma profiles: low/no trauma, emotional trauma, sexual trauma, and polytrauma. Results indicated that the sexual and polytrauma profiles displayed significantly elevated scores on the DIB-R and that the low/no and emotional trauma profiles did not differ significantly on the DIB-R. Secondary analyses revealed elevated levels of a composite CT score among those with both BN and BPD psychopathology compared to those with BN only. These findings suggest that both childhood sexual abuse and the additive effects of childhood polytrauma may be linked to BPD psychopathology in BN. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:689-694). © 2016 Wiley Periodicals, Inc.
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DEFF Research Database (Denmark)
Diel, R; Goletti, D; Ferrara, G
2011-01-01
We conducted a systematic review and meta-analysis to compare the accuracy of the QuantiFERON-TB® Gold In-Tube (QFT-G-IT) and the T-SPOT®.TB assays with the tuberculin skin test (TST) for the diagnosis of latent Mycobacterium tuberculosis infection (LTBI). The Medline, Embase and Cochrane databases...... of IGRAs varied 98-100%. In immunocompetent adults, NPV for progression to tuberculosis within 2 yrs were 97.8% for T-SPOT®.TB and 99.8% for QFT-G-IT. When test performance of an immunodiagnostic test was not restricted to prior positivity of another test, progression rates to tuberculosis among IGRA...
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Paternal Work Stress and Latent Profiles of Father-Infant Parenting Quality
Goodman, W. Benjamin; Crouter, Ann C.; Lanza, Stephanie T.; Cox, Martha J.; Vernon-Feagans, Lynne
2011-01-01
The current study used latent profile analysis (LPA) to examine the implications of fathers' experiences of work stress for paternal behaviors with infants across multiple dimensions of parenting in a sample of fathers living in nonmetropolitan communities (N = 492). LPA revealed five classes of fathers based on levels of social-affective…
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Directory of Open Access Journals (Sweden)
Hayduk Leslie A
2012-10-01
Full Text Available Abstract Background Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators. Discussion Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. Summary We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.
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A coarse to fine minutiae-based latent palmprint matching.
Liu, Eryun; Jain, Anil K; Tian, Jie
2013-10-01
With the availability of live-scan palmprint technology, high resolution palmprint recognition has started to receive significant attention in forensics and law enforcement. In forensic applications, latent palmprints provide critical evidence as it is estimated that about 30 percent of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae in a rolled fingerprint) and large area of foreground region in full palmprints, novel strategies need to be developed for efficient and robust latent palmprint matching. In this paper, a coarse to fine matching strategy based on minutiae clustering and minutiae match propagation is designed specifically for palmprint matching. To deal with the large number of minutiae, a local feature-based minutiae clustering algorithm is designed to cluster minutiae into several groups such that minutiae belonging to the same group have similar local characteristics. The coarse matching is then performed within each cluster to establish initial minutiae correspondences between two palmprints. Starting with each initial correspondence, a minutiae match propagation algorithm searches for mated minutiae in the full palmprint. The proposed palmprint matching algorithm has been evaluated on a latent-to-full palmprint database consisting of 446 latents and 12,489 background full prints. The matching results show a rank-1 identification accuracy of 79.4 percent, which is significantly higher than the 60.8 percent identification accuracy of a state-of-the-art latent palmprint matching algorithm on the same latent database. The average computation time of our algorithm for a single latent-to-full match is about 141 ms for genuine match and 50 ms for impostor match, on a Windows XP desktop system with 2
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Abstract: Inference and Interval Estimation for Indirect Effects With Latent Variable Models.
Falk, Carl F; Biesanz, Jeremy C
2011-11-30
Models specifying indirect effects (or mediation) and structural equation modeling are both popular in the social sciences. Yet relatively little research has compared methods that test for indirect effects among latent variables and provided precise estimates of the effectiveness of different methods. This simulation study provides an extensive comparison of methods for constructing confidence intervals and for making inferences about indirect effects with latent variables. We compared the percentile (PC) bootstrap, bias-corrected (BC) bootstrap, bias-corrected accelerated (BC a ) bootstrap, likelihood-based confidence intervals (Neale & Miller, 1997), partial posterior predictive (Biesanz, Falk, and Savalei, 2010), and joint significance tests based on Wald tests or likelihood ratio tests. All models included three reflective latent variables representing the independent, dependent, and mediating variables. The design included the following fully crossed conditions: (a) sample size: 100, 200, and 500; (b) number of indicators per latent variable: 3 versus 5; (c) reliability per set of indicators: .7 versus .9; (d) and 16 different path combinations for the indirect effect (α = 0, .14, .39, or .59; and β = 0, .14, .39, or .59). Simulations were performed using a WestGrid cluster of 1680 3.06GHz Intel Xeon processors running R and OpenMx. Results based on 1,000 replications per cell and 2,000 resamples per bootstrap method indicated that the BC and BC a bootstrap methods have inflated Type I error rates. Likelihood-based confidence intervals and the PC bootstrap emerged as methods that adequately control Type I error and have good coverage rates.
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Association between latent toxoplasmosis and cognition in adults: a cross-sectional study.
Gale, S D; Brown, B L; Erickson, L D; Berrett, A; Hedges, D W
2015-04-01
Latent infection from Toxoplasma gondii (T. gondii) is widespread worldwide and has been associated with cognitive deficits in some but not all animal models and in humans. We tested the hypothesis that latent toxoplasmosis is associated with decreased cognitive function in a large cross-sectional dataset, the National Health and Nutrition Examination Survey (NHANES). There were 4178 participants aged 20-59 years, of whom 19.1% had IgG antibodies against T. gondii. Two ordinary least squares (OLS) regression models adjusted for the NHANES complex sampling design and weighted to represent the US population were estimated for simple reaction time, processing speed and short-term memory or attention. The first model included only main effects of latent toxoplasmosis and demographic control variables, and the second added interaction terms between latent toxoplasmosis and the poverty-to-income ratio (PIR), educational attainment and race-ethnicity. We also used multivariate models to assess all three cognitive outcomes in the same model. Although the models evaluating main effects only demonstrated no association between latent toxoplasmosis and the cognitive outcomes, significant interactions between latent toxoplasmosis and the PIR, between latent toxoplasmosis and educational attainment, and between latent toxoplasmosis and race-ethnicity indicated that latent toxoplasmosis may adversely affect cognitive function in certain groups.
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Power and type I error of local fit statistics in multilevel latent class analysis
Nagelkerke, E.; Oberski, D.L.; Vermunt, J.K.
2017-01-01
In the social and behavioral sciences, variables are often categorical and people are often nested in groups. Models for such data, such as multilevel logistic regression or the multilevel latent class model, should account for not only the categorical nature of the variables, but also the nested
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Longo, Gregory S; Bray, Bethany C; Kim-Spoon, Jungmeen
2017-03-01
Prior research has documented robust associations between adolescent religiousness/spirituality (R/S) and psychopathology outcomes including externalizing and internalizing symptomatology, yet no previous studies have examined these associations with adolescent R/S profiles using a person-centred approach. We examined whether there are identifiable subgroups characterized by unique multidimensional patterns of R/S experiences and how these experiences may be related to externalizing and internalizing symptomatology. The sample consisted of 220 Appalachian adolescents between 12 and 18 years old who were primarily White and primarily Christian. Latent profile analysis revealed three profiles of adolescent R/S: high religiousness (28.4%), introjectors (47.6%), and low religiousness (24.0%). These profiles were differentially related to internalizing and externalizing symptomatology such that the high religiousness group was significantly lower than the introjectors with respect to internalizing and externalizing symptomatology and lower than the low religiousness group in externalizing symptomatology. Implications and suggestions for future research using person-centred approaches to better understand differential developmental trajectories of religious development are provided. Statement of contribution What is already known Prior research has demonstrated a negative relationship between adolescent religiousness and spirituality (R/S) and psychopathology. Numerous studies document the differential relationships between aspects of R/S and psychopathology; however, few have done so from a person-centred perspective. There are several theories that outline how R/S to study R/S when paying specific attention to culture. Saroglou's Big Four dimensions of religion (believing, bonding, behaving, and belonging) posits that these four dimensions (1) are able to delimit religion from proximal constructs; (2) translate major distinct dimensions of religiousness; (3) can be
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A latent profile analysis of Asian American men's and women's adherence to cultural values.
Wong, Y Joel; Nguyen, Chi P; Wang, Shu-Yi; Chen, Weilin; Steinfeldt, Jesse A; Kim, Bryan S K
2012-07-01
The goal of this study was to identify diverse profiles of Asian American women's and men's adherence to values that are salient in Asian cultures (i.e., conformity to norms, family recognition through achievement, emotional self-control, collectivism, and humility). To this end, the authors conducted a latent profile analysis using the 5 subscales of the Asian American Values Scale-Multidimensional in a sample of 214 Asian Americans. The analysis uncovered a four-cluster solution. In general, Clusters 1 and 2 were characterized by relatively low and moderate levels of adherence to the 5 dimensions of cultural values, respectively. Cluster 3 was characterized by the highest level of adherence to the cultural value of family recognition through achievement, whereas Cluster 4 was typified by the highest levels of adherence to collectivism, emotional self-control, and humility. Clusters 3 and 4 were associated with higher levels of depressive symptoms than Cluster 1. Furthermore, Asian American women and Asian American men had lower odds of being in Cluster 4 and Cluster 3, respectively. These findings attest to the importance of identifying specific patterns of adherence to cultural values when examining the relationship between Asian Americans' cultural orientation and mental health status.
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Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang
2017-12-01
Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.
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Polytomous latent scales for the investigation of the ordering of items
Ligtvoet, R.; van der Ark, L.A.; Bergsma, W. P.; Sijtsma, K.
2011-01-01
We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering
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Lomakin, Ya A; Shmidt, A A; Bobik, T V; Chernov, A S; Pyrkov, A Yu; Aleksandrova, N M; Okunola, D O; Vaskina, M I; Ponomarenko, N A; Telegin, G B; Dubina, M V; Belogurov, A A
2017-10-01
Intracellular fragments of latent phase protein LMP1 of Epstein-Barr virus, denoted as CTAR1/2/3, can trigger a variety of cell cascades and contribute to the transforming potential of the virus. Generation of recombinant proteins CTAR1/2/3 is expected to yield more ample data on functional and immunogenic characteristics of LMP1. We created genetic constructs for prokaryotic expression of LMP1 CTAR fragments and selected optimal conditions for their production and purification. Using a new library of LMP1 CTAR fragments, we carried out epitope mapping of a diagnostic anti-LMP1 antibody S12. Analysis of polyclonal serum antibodies from mice immunized with full-length LMP1 confirmed immunogenicity of CTAR elements comparable with that of full-length protein.
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International Nuclear Information System (INIS)
Sari, Ahmet; Sari, Hayati; Oenal, Adem
2004-01-01
The present study deals with two subjects. The first one is to determine the thermal properties of lauric acid (LA)-stearic acid (SA), myristic acid (MA)-palmitic acid (PA) and palmitic acid (PA)-stearic acid (SA) eutectic mixtures as latent heat storage material. The properties were measured by the differential scanning calorimetry (DSC) analysis technique. The second one is to study the thermal reliability of these materials in view of the change in their melting temperatures and latent heats of fusion with respect to repeated thermal cycles. For this aim, the eutectic mixtures were subjected to 360 repeated melt/freeze cycles, and their thermal properties were measured after 0, 90,180 and 360 thermal cycles by the technique of DSC analysis. The DSC thermal analysis results show that the binary systems of LA-SA in the ratio of 75.5:24.5 wt.%, MA-PA in the ratio of 58:42 wt.% and PA-SA in the ratio of 64.2:35.8 wt.% form eutectic mixtures with melting temperatures of 37.0, 42.60 and 52.30 deg. C and with latent heats of fusion of 182.7, 169.7 and 181.7 J g -1 , respectively. These thermal properties make them possible for heat storage in passive solar heating applications with respect to climate conditions. The accelerated thermal cycle tests indicate that the changes in the melting temperatures and latent heats of fusion of the studied eutectic mixtures are not regular with increasing number of thermal cycles. However, these materials, latent heat energy storage materials, have good thermal reliability in terms of the change in their thermal properties with respect to thermal cycling for about a one year utility period
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Latent uncertainties of the precalculated track Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Renaud, Marc-André; Seuntjens, Jan [Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4 (Canada); Roberge, David [Département de radio-oncologie, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec H2L 4M1 (Canada)
2015-01-15
Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of
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Latent uncertainties of the precalculated track Monte Carlo method
International Nuclear Information System (INIS)
Renaud, Marc-André; Seuntjens, Jan; Roberge, David
2015-01-01
Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D max . Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the
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A latent transition model of the effects of a teen dating violence prevention initiative.
Williams, Jason; Miller, Shari; Cutbush, Stacey; Gibbs, Deborah; Clinton-Sherrod, Monique; Jones, Sarah
2015-02-01
Patterns of physical and psychological teen dating violence (TDV) perpetration, victimization, and related behaviors were examined with data from the evaluation of the Start Strong: Building Healthy Teen Relationships initiative, a dating violence primary prevention program targeting middle school students. Latent class and latent transition models were used to estimate distinct patterns of TDV and related behaviors of bullying and sexual harassment in seventh grade students at baseline and to estimate transition probabilities from one pattern of behavior to another at the 1-year follow-up. Intervention effects were estimated by conditioning transitions on exposure to Start Strong. Latent class analyses suggested four classes best captured patterns of these interrelated behaviors. Classes were characterized by elevated perpetration and victimization on most behaviors (the multiproblem class), bullying perpetration/victimization and sexual harassment victimization (the bully-harassment victimization class), bullying perpetration/victimization and psychological TDV victimization (bully-psychological victimization), and experience of bully victimization (bully victimization). Latent transition models indicated greater stability of class membership in the comparison group. Intervention students were less likely to transition to the most problematic pattern and more likely to transition to the least problem class. Although Start Strong has not been found to significantly change TDV, alternative evaluation models may find important differences. Latent transition analysis models suggest positive intervention impact, especially for the transitions at the most and the least positive end of the spectrum. Copyright © 2015. Published by Elsevier Inc.
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Directory of Open Access Journals (Sweden)
Marianna Virtanen
Full Text Available Studies of work disability in diabetes have examined diabetes as a homogeneous disease. We sought to identify subgroups among persons with diabetes based on potential risk factors for work disability.Participants were 2,445 employees with diabetes from three prospective cohorts (the Finnish Public Sector study, the GAZEL study, and the Whitehall II study. Work disability was ascertained via linkage to registers of sickness absence and disability pensions during a follow-up of 4 years. Study-specific latent class analysis was used to identify subgroups according to prevalent comorbid disease and health-risk behaviours. Study-specific associations with work disability at follow-up were pooled using fixed-effects meta-analysis.Separate latent class analyses for men and women in each cohort supported a two-class solution with one subgroup (total n = 1,086; 44.4% having high prevalence of chronic somatic diseases, psychological symptoms, obesity, physical inactivity and abstinence from alcohol and the other subgroup (total n = 1,359; 55.6% low prevalence of these factors. In the adjusted meta-analyses, participants in the 'high-risk' group had more work disability days (pooled rate ratio = 1.66, 95% CI 1.38-1.99 and more work disability episodes (pooled rate ratio = 1.33, 95% CI 1.21-1.46. These associations were similar in men and women, younger and older participants, and across occupational groups.Diabetes is not a homogeneous disease in terms of work disability risk. Approximately half of people with diabetes are assigned to a subgroup characterised by clustering of comorbid health conditions, obesity, physical inactivity, abstinence of alcohol, and associated high risk of work disability; the other half to a subgroup characterised by a more favourable risk profile.
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A Behavioral Approach to Understanding Green Consumerism Using Latent Class Choice Analysis
DEFF Research Database (Denmark)
Peschel, Anne Odile; Grebitus, Carola; Steiner, Bodo
on individuals' environmental attitudes and values. Consumer involvement and environmental attitudes contribute significantly toward explaining sustainable choices, suggesting that greater consumer involvement may be targeted by policy makers and firms to more effectively nudge consumers toward green consumerism......To better understand motivations of consumers making choices among sustainability-labeled food products, this paper analyzes drivers of stated choices for a dietary staple labeled with carbon and water foodprints. Latent class modeling of survey responses reveals distinct consumer segments based...
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DEFF Research Database (Denmark)
Arnbak, Bodil; Jensen, Rikke Krüger; Manniche, Claus
2016-01-01
BACKGROUND: The aim of this study was to investigate subgroups of magnetic resonance imaging (MRI) findings for the spine and sacroiliac joints (SIJs) using latent class analysis (LCA), and to investigate whether these subgroups differ in their demographic and clinical characteristics. METHODS...
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Handbook of latent variable and related models
Lee, Sik-Yum
2011-01-01
This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.
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Aspects of physicochemical methods for the detection of latent fingerprints
International Nuclear Information System (INIS)
Knowles, A.M.
1978-01-01
This paper reviews physicochemical methods of detecting latent finger-prints on a wide range of materials commonly found at the scene of a crime, with particular emphasis placed on the newer autoradiographic techniques. This is set against a description of studies on the fundamental nature of the latent fingerprint and its host substrate, with a brief review of the history of reagents used in latent fingerprint examination. (author)
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Personality and trajectories of posttraumatic psychopathology: A latent change modelling approach.
Fletcher, Susan; O'Donnell, Meaghan; Forbes, David
2016-08-01
Survivors of traumatic events may develop a range of psychopathology, across the internalizing and externalizing dimensions of disorder and associated personality traits. However, research into personality-based internalizing and externalizing trauma responses has been limited to cross-sectional investigations of PTSD comorbidity. Personality typologies may present an opportunity to identify and selectively intervene with survivors at risk of posttraumatic disorder. Therefore this study examined whether personality prospectively influences the trajectory of disorder in a broader trauma-exposed sample. During hospitalization for a physical injury, 323 Australian adults completed the Multidimensional Personality Questionnaire-Brief Form and Structured Clinical Interview for DSM-IV, with the latter readministered 3 and 12 months later. Latent profile analysis conducted on baseline personality scores identified subgroups of participants, while latent change modelling examined differences in disorder trajectories. Three classes (internalizing, externalizing, and normal personality) were identified. The internalizing class showed a high risk of developing all disorders. Unexpectedly, however, the normal personality class was not always at lowest risk of disorder. Rather, the externalizing class, while more likely than the normal personality class to develop substance use disorders, were less likely to develop PTSD and depression. Results suggest that personality is an important mechanism in influencing the development and form of psychopathology after trauma, with internalizing and externalizing subtypes identifiable in the early aftermath of injury. These findings suggest that early intervention using a personality-based transdiagnostic approach may be an effective method of predicting and ultimately preventing much of the burden of posttraumatic disorder. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Ristova, Mimoza M; Radiceska, Pavlina; Bozinov, Igorco; Barandovski, Lambe
2016-05-01
One of the crucial factors determining the cyanoacrylate deposit quality over latent fingerprints appeared to be the extent of the humidity. This work focuses on the enhancement/refreshment of age-degraded latent fingerprints by irradiating the samples with UV, X-ray, or thermal neutrons prior to the cyanoacrylate (CA) fuming. Age degradation of latent fingerprints deposited on glass surfaces was examined through the decrease in the number of characteristic minutiae counts over time. A term "critical day" was introduced for the time at which the average number of identifiable minutiae definitions drops to one-half. Fingerprints older than their "critical day" were exposed to either UV, X-ray, or thermal neutrons. Identical reference samples were kept unexposed. All samples, both reference and irradiated, were developed during a single CA fuming procedure. Comparative latent fingerprint analysis showed that exposure to ionizing radiation enhances the CA fuming, yielding a 20-30% increase in average minutiae count. © 2015 American Academy of Forensic Sciences.
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Latent M. tuberculosis infection--pathogenesis, diagnosis, treatment and prevention strategies.
Druszczyńska, Magdalena; Kowalewicz-Kulbat, Magdalena; Fol, Marek; Włodarczyk, Marcin; Rudnicka, Wiesława
2012-01-01
One third of the earths population is infected with Mycobacterium tuberculosis (Mtb), but only 5-10% of the infected individuals develop active tuberculosis (TB) over their lifetime. The remaining 90-95% stay healthy and are called latently infected individuals. They are the biggest reservoir of the tubercle bacilli and identifying the cases of latent TB is a part of the global plan of TB control. From the clinical point of view detection of latent TB infections (LTBI) in individuals with the highest active TB risk including cases of HIV infection, autoimmune inflammatory diseases or cancer, is a priority. This review summarizes the recent findings in the pathogenesis of latent TB, its diagnosis, treatment and prevention.
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Thermal Analysis of Fluidized Bed and Fixed Bed Latent Heat Thermal Storage System
Beemkumar, N.; Karthikeyan, A.; Shiva Keshava Reddy, Kota; Rajesh, Kona; Anderson, A.
2017-05-01
Thermal energy storage technology is essential because its stores available energy at low cost. Objective of the work is to store the thermal energy in a most efficient method. This work is deal with thermal analysis of fluidized bed and fixed bed latent heat thermal storage (LHTS) system with different encapsulation materials (aluminium, brass and copper). D-Mannitol has been used as phase change material (PCM). Encapsulation material which is in orbicular shape with 4 inch diameter and 2 mm thickness orbicular shaped product is used. Therminol-66 is used as a heat transfer fluid (HTF). Arrangement of encapsulation material is done in two ways namely fluidized bed and fixed bed thermal storage system. Comparison was made between the performance of fixed bed and fluidized bed with different encapsulation material. It is observed that from the economical point of view aluminium in fluidized bed LHTS System has highest efficiency than copper and brass. The thermal energy storage system can be analyzed with fixed bed by varying mass flow rate of oil paves a way to find effective heat energy transfer.
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Vander Elst, Tinne; Näswall, Katharina; Bernhard-Oettel, Claudia; De Witte, Hans; Sverke, Magnus
2016-01-01
The current study contributes to the literature on job insecurity by highlighting threat to the benefits of work as an explanation of the effect of job insecurity on health complaints. Building on the latent deprivation model, we predicted that threats to both manifest (i.e., financial income) and latent benefits of work (i.e., collective purpose, social contacts, status, time structure, activity) mediate the relationships from job insecurity to subsequent mental and physical health complaints. In addition, in line with the conservation of resources theory, we proposed that financial resources buffer the indirect effect of job insecurity on health complaints through threat to the manifest benefit. Hypotheses were tested using a multilevel design, in which 3 measurements (time lag of 6 months between subsequent measurements) were clustered within 1,994 employees (in Flanders, Belgium). This allowed for the investigation of within-person processes, while controlling for variance at the between-person level. The results demonstrate that job insecurity was related to subsequent threats to both manifest and latent benefits, and that these threats in turn were related to subsequent health complaints (with an exception for threat to the manifest benefit that did not predict mental health complaints). Three significant indirect effects were found: threat to the latent benefits mediated the relationships between job insecurity and both mental and physical health complaints, and threat to the manifest benefit mediated the relationship between job insecurity and physical health complaints. Unexpectedly, the latter indirect effect was exacerbated by financial resources. (c) 2016 APA, all rights reserved).
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Hori, Hiroaki; Teraishi, Toshiya; Nagashima, Anna; Koga, Norie; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi
2017-08-01
While major depressive disorder (MDD) is considered to be a heterogeneous disorder, the nature of the heterogeneity remains unclear. Studies have attempted to classify patients with MDD using latent variable techniques, yet the empirical approaches to symptom-based subtyping of MDD have not provided conclusive evidence. Here we aimed to identify homogeneous classes of MDD based on personality traits, using a latent profile analysis. We studied 238 outpatients with DSM-IV MDD recruited from our specialized depression outpatient clinic and assessed their dimensional personality traits with the Temperament and Character Inventory. Latent profile analysis was conducted with 7 dimensions of the Temperament and Character Inventory as indicators. Relationships of the identified classes with symptomatology, prescription pattern, and social function were then examined. The latent profile analysis indicated that a 3-class solution best fit the data. Of the sample, 46.2% was classified into a "neurotic" group characterized by high harm avoidance and low self-directedness; 30.3% into an "adaptive" group characterized by high self-directedness and cooperativeness; and 23.5% into a "socially-detached" group characterized by low reward dependence and cooperativeness and high self-transcendence. The 2 maladaptive groups, namely neurotic and socially-detached groups, demonstrated unique patterns of symptom expression, different classes of psychotropic medication use, and lower social functioning. Generalizability of the findings was limited since our patients were recruited from the specialized depression outpatient clinic. Our personality-based latent profile analysis identified clinically meaningful 3 MDD groups that were markedly different in their personality profiles associated with distinct symptomatology and functioning. Copyright © 2017 Elsevier B.V. All rights reserved.
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Discrete response patterns in the upper range of hypnotic suggestibility: A latent profile analysis.
Terhune, Devin Blair
2015-05-01
High hypnotic suggestibility is a heterogeneous condition and there is accumulating evidence that highly suggestible individuals may be comprised of discrete subtypes with dissimilar cognitive and phenomenological profiles. This study applied latent profile analysis to response patterns on a diverse battery of difficult hypnotic suggestions in a sample of individuals in the upper range of hypnotic suggestibility. Comparisons among models indicated that a four-class model was optimal. One class was comprised of very highly suggestible (virtuoso) participants, two classes included highly suggestible participants who were alternately more responsive to inhibitory cognitive suggestions or posthypnotic amnesia suggestions, and the fourth class consisted primarily of medium suggestible participants. These results indicate that there are discrete response profiles in high hypnotic suggestibility. They further provide a number of insights regarding the optimization of hypnotic suggestibility measurement and have implications for the instrumental use of hypnosis for the modeling of different psychological conditions. Copyright © 2015 Elsevier Inc. All rights reserved.
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Dechartres, Agnes; Huas, Caroline; Godart, Nathalie; Pousset, Maud; Pham, Alexandra; Divac, Snezana M; Rouillon, Frederic; Falissard, Bruno
2011-01-01
To empirically classify phenotypes of eating disorders (ED) using latent class analysis (LCA), and to validate this classification based on clinical outcomes. LCA was applied to 968 inpatients. The resultant classes were validated by clinical outcomes including mortality. A 5-class solution showed the best fit. The symptoms of latent class 1 (LC1; 26% of the sample) resembled anorexia nervosa (AN), bingeing-purging (AN-B/P) subtype; those of LC2 (23%) resembled bulimia nervosa; those of LC3 (11%) were close to AN-B/P without weight and body concerns; those of LC4 resembled restrictive anorexia nervosa (RAN) without weight and body concerns, and those of LC5 RAN. A history of hospitalization for ED was significantly more frequent for LC3 and LC4. The lowest BMI at admission were presented in LC4. LC1 showed the highest level of psychological disturbances and LC4 the lowest. LC3 and LC4 differed from LC1 and LC5 by higher percentages of treatment dropout (64.9 vs. 57.2 and 55.7 vs. 47.5%, respectively; overall p = 0.001). Survival rates tended to be different between the LC (p = 0.09). Subgroups of AN patients with low weight and body concerns seem more severe at hospitalization and more difficult to manage, with a higher rate of treatment dropout than the 'typical' AN patients. Copyright © 2010 S. Karger AG, Basel.
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Barboza, Gia Elise
2015-01-01
This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Decomposition of multivariate phenotypic means in multigroup genetic covarinace structure analysis
Dolan, C.V.; Molenaar, P.C.M.; Boomsma, D.I.
1992-01-01
Uses D. Sorbom's (1974) method to study differences in latent means in multivariate twin data. By restricting the analysis to a comparison between groups, the results pertain only to the additive contributions of common genetic and environmental factors to the deviation of the group means from what
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Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus
2014-02-01
In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates
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PR.Latent-class methods to evaluate diagnostics tests for echinococcus infections in dogs.
Hartnack, S.; Budke, C.M.; Craig, P.S.; Jiamin, Q.; Boufana, B.; Campos Ponce, M.; Torgerson, P.R.
2013-01-01
Background: The diagnosis of canine echinococcosis can be a challenge in surveillance studies because there is no perfect gold standard that can be used routinely. However, unknown test specificities and sensitivities can be overcome using latent-class analysis with appropriate data. Methodology: We
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Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach.
LaBelle, Denise R; Walsh, Ryan R; Banks, Sarah J
2017-08-01
Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive
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International Nuclear Information System (INIS)
Kuo, V.
2016-01-01
Full text: The European Qualifications Framework categorizes learning objectives into three qualifiers “knowledge”, “skills”, and “competences” (KSCs) to help improve the comparability between different fields and disciplines. However, the management of KSCs remains a great challenge given their semantic fuzziness. Similar texts may describe different concepts and different texts may describe similar concepts among different domains. This is difficult for the indexing, searching and matching of semantically similar KSCs within an information system, to facilitate transfer and mobility of KSCs. We present a working example using a semantic inference method known as Latent Semantic Analysis, employing a matrix operation called Singular Value Decomposition, which have been shown to infer semantic associations within unstructured textual data comparable to that of human interpretations. In our example, a few natural language text passages representing KSCs in the nuclear sector are used to demonstrate the capabilities of the system. It can be shown that LSA is able to infer latent semantic associations between texts, and cluster and match separate text passages semantically based on these associations. We propose this methodology for modelling existing natural language KSCs in the nuclear domain so they can be semantically queried, retrieved and filtered upon request. (author
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Directory of Open Access Journals (Sweden)
Rabit Veseli
2015-05-01
Full Text Available The game of volleyball with its dynamic character is present in the world of the sport with permanent development and growing popularity and fans. Volleyball is part of a pollystructural complex sports activities. It is performed on a ground of a relatively small size (18 x 9 meters and is a kind of game that requires of players a high level of advanced motoric abilities (speed, strength, endurance, a fast rate of visual reaction, explosivity, as well as specific motoric skills (precision etc.. Scientific conclusion as well as the growing number of conducted researches in the very game, have a real contribution to its modern development and level of popularity. Situation-motoric skills make a significant dimension in the structure of volleyball game. The subject of the research is specific-motoric abilities and situation-motoric skills of 52 volleyball players aged from 16 to 17. The basic goal of the research is to establish the effect of specific-motoric abilities on situation-motoric skills of volleyball players in latent space. In order to assess the specific-motoric abilities 9 tests are used, and to assess the situation-motoric skills 3 precision tests are used. The results obtained from the 12 applied tests are worked out through the basic statistic parameters. Through component factor analysis 3 latent specific-motoric dimensions are isolated as well as one situation-motoric dimension. By regressive analysis there is established a low but statistically significant relation between the criterion and predictor latent dimensions. That confirms the dependence and relation between the specific-motoric abilities and situation-motoric skills. Researches in the fi eld of similar questions have been conducted by the following authors: Jurko et al., 2013 and Nešić, et al., 2011.
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Lawler, Margaret; Heary, Caroline; Nixon, Elizabeth
2017-08-17
Neglecting to take account of the underlying context or type of physical activity (PA) that underpins overall involvement has resulted in a limited understanding of adolescents' PA participation. The purpose of the present research was to identify male and female adolescents' leisure time PA patterns and examine whether psychological processes derived from self-determination theory differ as a function of the pattern of PA undertaken. Nine hundred ninety-five students (61.2% females, 38.8% males; M age = 13.72 years, SD = 1.25) from eight secondary schools in Dublin, Ireland completed a physical activity recall 7 day diary and measures of intrinsic motivation, competence, relatedness, autonomy and autonomy support. Based on the diary five binary indicators of physical activity were derived reflecting recommended levels of MVPA on a minimum of 3 days, at least three sessions of non-organized physical activity (e.g. jog), team sport, individual sport, and organized non-sport physical activity (e.g. dance). Latent class analysis was used to identify subgroups of adolescents that engaged in similar patterns of physical activity. Profiles of physical activity participation were subsequently compared on motivational characteristics using Kruskal-Wallis tests. Latent class analysis revealed six distinct classes for girls (Organized Run/Swim & Dance/Gym; Organized Dance; Leisure Active Team Sport; Active Individual Sport; Walk/Run/Outdoor games; Non-Participation) and five for boys (Leisure Active Gym; Leisure Active Individual Sport; Active Team Sport; Active Mixed Type; Non-Participation). Significant differences were found between the classes. Girls characterized by participation in team or individual sport, and boys represented by team sport participation demonstrated significantly higher self-determined motivational characteristics relative to other profiles of physical activity. This research offers a nuanced insight into the underlying type of activities that
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Directory of Open Access Journals (Sweden)
Margaret Lawler
2017-08-01
Full Text Available Abstract Background Neglecting to take account of the underlying context or type of physical activity (PA that underpins overall involvement has resulted in a limited understanding of adolescents’ PA participation. The purpose of the present research was to identify male and female adolescents’ leisure time PA patterns and examine whether psychological processes derived from self-determination theory differ as a function of the pattern of PA undertaken. Methods Nine hundred ninety-five students (61.2% females, 38.8% males; M age = 13.72 years, SD = 1.25 from eight secondary schools in Dublin, Ireland completed a physical activity recall 7 day diary and measures of intrinsic motivation, competence, relatedness, autonomy and autonomy support. Based on the diary five binary indicators of physical activity were derived reflecting recommended levels of MVPA on a minimum of 3 days, at least three sessions of non-organized physical activity (e.g. jog, team sport, individual sport, and organized non-sport physical activity (e.g. dance. Latent class analysis was used to identify subgroups of adolescents that engaged in similar patterns of physical activity. Profiles of physical activity participation were subsequently compared on motivational characteristics using Kruskal-Wallis tests. Results Latent class analysis revealed six distinct classes for girls (Organized Run/Swim & Dance/Gym; Organized Dance; Leisure Active Team Sport; Active Individual Sport; Walk/Run/Outdoor games; Non-Participation and five for boys (Leisure Active Gym; Leisure Active Individual Sport; Active Team Sport; Active Mixed Type; Non-Participation. Significant differences were found between the classes. Girls characterized by participation in team or individual sport, and boys represented by team sport participation demonstrated significantly higher self-determined motivational characteristics relative to other profiles of physical activity. Conclusion This research
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Directory of Open Access Journals (Sweden)
Cogo-Moreira H
2013-08-01
Full Text Available Hugo Cogo-Moreira,1 Carolina Alves Ferreira Carvalho,2 Adriana de Souza Batista Kida,2 Clara Regina Brandão de Avila,2 Giovanni Abrahão Salum,3,5 Tais Silveira Moriyama,1,4 Ary Gadelha,1,5 Luis Augusto Rohde,3,5 Luciana Monteiro de Moura,1 Andrea Parolin Jackowski,1 Jair de Jesus Mari11Department of Psychiatry, Federal University of São Paulo, São Paulo, 2Department of Hearing and Speech Pathology, Federal University of São Paulo, São Paulo, 3Department of Psychiatry, Federal University of Rio Grande do Sul, Rio Grande do Sul, 4Department of Psychiatry, University of São Paulo, São Paulo, 5National Institute for Developmental Psychiatry for Children and Adolescent, (National Counsel of Technological and Scientific Development, BrazilAim: To explore and validate the best returned latent class solution for reading and writing subtests from the Academic Performance Test (TDE.Sample: A total of 1,945 children (6–14 years of age, who answered the TDE, the Development and Well-Being Assessment (DAWBA, and had an estimated intelligence quotient (IQ higher than 70, came from public schools in São Paulo (35 schools and Porto Alegre (22 schools that participated in the ‘High Risk Cohort Study for Childhood Psychiatric Disorders’ project. They were on average 9.52 years old (standard deviation = 1.856, from the 1st to 9th grades, and 53.3% male. The mean estimated IQ was 102.70 (standard deviation = 16.44.Methods: Via Item Response Theory (IRT, the highest discriminating items (‘a’>1.7 were selected from the TDE subtests of reading and writing. A latent class analysis was run based on these subtests. The statistically and empirically best latent class solutions were validated through concurrent (IQ and combined attention deficit hyperactivity disorder [ADHD] diagnoses and discriminant (major depression diagnoses measures.Results: A three-class solution was found to be the best model solution, revealing classes of children with good, not
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Towards an HIV-1 cure: measuring the latent reservoir
Bruner, Katherine M.; Hosmane, Nina N.; Siliciano, Robert F.
2015-01-01
The latent reservoir of HIV-1 in resting memory CD4+ T cells serves as a major barrier to curing HIV-1 infection. While many PCR- and culture-based assays have been used to measure the size of the latent reservoir, correlation between results of different assays is poor and recent studies indicate that no available assay provides an accurate measurement of reservoir size. The discrepancies between assays are a hurdle to clinical trials that aim to measure the efficacy of HIV-1 eradication strategies. Here we describe the advantages and disadvantages of various approaches to measure the latent reservoir. PMID:25747663
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Perceived risk associated with ecstasy use: a latent class analysis approach
Martins, SS; Carlson, RG; Alexandre, PK; Falck, RS
2011-01-01
This study aims to define categories of perceived health problems among ecstasy users based on observed clustering of their perceptions of ecstasy-related health problems. Data from a community sample of ecstasy users (n=402) aged 18 to 30, in Ohio, was used in this study. Data was analyzed via Latent Class Analysis (LCA) and Regression. This study identified five different subgroups of ecstasy users based on their perceptions of health problems they associated with their ecstasy use. Almost one third of the sample (28.9%) belonged to a class with “low level of perceived problems” (Class 4). About one fourth (25.6%) of the sample (Class 2), had high probabilities of “perceiving problems on sexual-related items”, but generally low or moderate probabilities of perceiving problems in other areas. Roughly one-fifth of the sample (21.1%, Class 1) had moderate probabilities of perceiving ecstasy health-related problems in all areas. A small proportion of respondents (11.9%, Class 5) had high probabilities of reporting “perceived memory and cognitive problems, and of perceiving “ecstasy related-problems in all areas” (12.4%, Class 3). A large proportion of ecstasy users perceive either low or moderate risk associated with their ecstasy use. It is important to further investigate whether lower levels of risk perception are associated with persistence of ecstasy use. PMID:21296504
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International Nuclear Information System (INIS)
Nithyanandam, K.; Pitchumani, R.
2014-01-01
Integrating TES (thermal energy storage) in a CSP (concentrating solar power) plant allows for continuous operation even during times when solar irradiation is not available, thus providing a reliable output to the grid. In the present study, the cost and performance models of an EPCM-TES (encapsulated phase change material thermal energy storage) system and HP-TES (latent thermal storage system with embedded heat pipes) are integrated with a CSP power tower system model utilizing Rankine and s-CO 2 (supercritical carbon-dioxide) power conversion cycles, to investigate the dynamic TES-integrated plant performance. The influence of design parameters of the storage system on the performance of a 200 MW e capacity power tower CSP plant is studied to establish design envelopes that satisfy the U.S. Department of Energy SunShot Initiative requirements, which include a round-trip annualized exergetic efficiency greater than 95%, storage cost less than $15/kWh t and LCE (levelized cost of electricity) less than 6 ¢/kWh. From the design windows, optimum designs of the storage system based on minimum LCE, maximum exergetic efficiency, and maximum capacity factor are reported and compared with the results of two-tank molten salt storage system. Overall, the study presents the first effort to construct and analyze LTES (latent thermal energy storage) integrated CSP plant performance that can help assess the impact, cost and performance of LTES systems on power generation from molten salt power tower CSP plant. - Highlights: • Presents technoeconomic analysis of thermal energy storage integrated concentrating solar power plants. • Presents a comparison of different storage options. • Presents optimum design of thermal energy storage system for steam Rankine and supercritical carbon dioxide cycles. • Presents designs for maximizing exergetic efficiency while minimizing storage cost and levelized cost of energy
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Ridge Width Correlations between Inked Prints and Powdered Latent Fingerprints.
De Alcaraz-Fossoul, Josep; Barrot-Feixat, Carme; Zapico, Sara C; Mancenido, Michelle; Broatch, Jennifer; Roberts, Katherine A; Carreras-Marin, Clara; Tasker, Jack
2017-10-03
A methodology to estimate the time of latent fingerprint deposition would be of great value to law enforcement and courts. It has been observed that ridge topography changes as latent prints age, including the widths of ridges that could be measured as a function of time. Crime suspects are commonly identified using fingerprint databases that contain reference inked tenprints (flat and rolled impressions). These can be of interest in aging studies as they provide baseline information relating to the original (nonaged) ridges' widths. In practice, the age of latent fingerprints could be estimated following a comparison process between the evidentiary aged print and the corresponding reference inked print. The present article explores possible correlations between inked and fresh latent fingerprints deposited on different substrates and visualized with TiO 2 . The results indicate that the ridge width of flat inked prints is most similar to fresh latent fingerprints , and these should be used as the comparison standard for future aging studies. © 2017 American Academy of Forensic Sciences.
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Study of noninvasive detection of latent fingerprints using UV laser
Li, Hong-xia; Cao, Jing; Niu, Jie-qing; Huang, Yun-gang; Mao, Lin-jie; Chen, Jing-rong
2011-06-01
Latent fingerprints present a considerable challenge in forensics, and noninvasive procedure that captures a digital image of the latent fingerprints is significant in the field of criminal investigation. The capability of photography technologies using 266nm UV Nd:YAG solid state laser as excitation light source to provide detailed images of unprocessed latent fingerprints is demonstrated. Unprocessed latent fingerprints were developed on various non-absorbent and absorbing substrates. According to the special absorption, reflection, scattering and fluorescence characterization of the various residues in fingerprints (fatty acid ester, protein, and carbosylic acid salts etc) to the UV light to weaken or eliminate the background disturbance and increase the brightness contrast of fingerprints with the background, and using 266nm UV laser as excitation light source, fresh and old latent fingerprints on the surface of four types of non-absorbent objects as magazine cover, glass, back of cellphone, wood desktop paintwork and two types of absorbing objects as manila envelope, notebook paper were noninvasive detected and appeared through reflection photography and fluorescence photography technologies, and the results meet the fingerprint identification requirements in forensic science.
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Surface latent heat flux as an earthquake precursor
Directory of Open Access Journals (Sweden)
S. Dey
2003-01-01
Full Text Available The analysis of surface latent heat flux (SLHF from the epicentral regions of five recent earthquakes that occurred in close proximity to the oceans has been found to show anomalous behavior. The maximum increase of SLHF is found 2–7 days prior to the main earthquake event. This increase is likely due to an ocean-land-atmosphere interaction. The increase of SLHF prior to the main earthquake event is attributed to the increase in infrared thermal (IR temperature in the epicentral and surrounding region. The anomalous increase in SLHF shows great potential in providing early warning of a disastrous earthquake, provided that there is a better understanding of the background noise due to the tides and monsoon in surface latent heat flux. Efforts have been made to understand the level of background noise in the epicentral regions of the five earthquakes considered in the present paper. A comparison of SLHF from the epicentral regions over the coastal earthquakes and the earthquakes that occurred far away from the coast has been made and it has been found that the anomalous behavior of SLHF prior to the main earthquake event is only associated with the coastal earthquakes.
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Hurlocker, Margo C; Vidaurri, Desirae N; Cuccurullo, Lisa-Ann J; Maieritsch, Kelly; Franklin, C Laurel
2018-03-15
Posttraumatic stress disorder (PTSD) is a complex psychiatric illness that can be difficult to diagnose, due in part to its comorbidity with major depressive disorder (MDD). Given that researchers have found no difference in prevalence rates of PTSD and MDD after accounting for overlapping symptoms, the latent structures of PTSD and MDD may account for the high comorbidity. In particular, the PTSD Negative Alterations in Cognition and Mood (NACM) and Hyperarousal factors have been characterized as non-specific to PTSD. Therefore, we compared the factor structures of the Diagnostic and Statistical Manual of Mental Disorders, 5 th edition (DSM-5) PTSD and MDD and examined the mediating role of the PTSD NACM and Hyperarousal factors on the relationship between MDD and PTSD symptom severity. Participants included 598 trauma-exposed veterans (M age = 48.39, 89% male) who completed symptom self-report measures of DSM-5 PTSD and MDD. Confirmatory factor analyses indicated an adequate-fitting four-factor DSM-5 PTSD model and two-factor MDD model. Compared to other PTSD factors, the PTSD NACM factor had the strongest relationship with the MDD Affective factor, and the PTSD NACM and Hyperarousal factors had the strongest association with the MDD Somatic factor. Further, the PTSD NACM factor explained the relationship between MDD factors and PTSD symptom severity. More Affective and Somatic depression was related to more NACM symptoms, which in turn were related to increased severity of PTSD. Limitations include the reliance on self-report measures and the use of a treatment-seeking, trauma-exposed veteran sample which may not generalize to other populations. Implications concerning the shared somatic complaints and psychological distress in the comorbidity of PTSD and MDD are discussed. Published by Elsevier B.V.
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Latent tuberculosis in nursing professionals of a Brazilian hospital
Directory of Open Access Journals (Sweden)
Valim Andréia
2011-05-01
Full Text Available Abstract Tuberculosis (TB is considered an occupational disease among health-care workers (HCWs. Direct contact with TB patients leads to an increased risk to become latently infected by Mycobacterium tuberculosis. The objective of this study is to estimate the prevalence of latent M. tuberculosis minfection among nursing professionals of a hospital in Rio Grande do Sul, Brazil, assessed by tuberculin skin test (TST. From November 2009 to May 2010, latent M. tuberculosis infection was assessed by TST in 55 nursing professionals. Epidemiological information was collected using a standardized questionnaire. A positive TST result (> or = 10 mm was observed in 47.3% of the HCWs tested. There was no significant difference in TST positivity when duration of employment or professional category (technician or nurse was evaluated. The results of this work reinforce the need for control measures to prevent latent M. tuberculosis infection among nursing professionals at the hospital where the study was conducted.
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Gene variants associated with antisocial behaviour: a latent variable approach.
Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V; Lee, Maria; Yrigollen, Carolyn M; Pakstis, Andrew J; Katsovich, Liliya; Olds, David L; Grigorenko, Elena L; Leckman, James F
2013-10-01
The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation programme in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Eight single-nucleotide polymorphisms (SNPs) from eight genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all eight genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid and cholinergic signalling as well as stress response pathways in mediating susceptibility to antisocial behaviour. This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential 'co-action' of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the aetiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a
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Directory of Open Access Journals (Sweden)
R Duarte
2010-09-01
Full Text Available O diagnóstico e tratamento da infecção latente por Mycobacterium tuberculosis reduz significativamente o risco de desenvolvimento de tuberculose activa e a transmissão da doença na comunidade. O rastreio da tuberculose infecção latente deve passar pela exclusão de doença activa (inquérito de sintomas e radiografia pulmonar e avaliação da resposta imunológica ao M. tuberculosis através dos testes actualmente ao dispor, como o teste tuberculínico e os testes IGRA (interferon-gamma release assay. A escolha do esquema de tratamento deve ter em linha de conta a eficácia, a adesão e os efeitos colaterais associados ao mesmo Este documento actualiza as recomendações sobre tratamento da tuberculose infecção latente. São apresentadas indicações sobre quem deve ser rastreado e revistos os esquemas de tratamento.Diagnosis and treatment of latent infection with Mycobacterium tuberculosis (LTBI, significantly reduces the risk of developing active tuberculosis and the transmission of the disease in the community. LTBI screening must pass by the exclusion of active disease (symptoms enquiry and chest radiography and assessment of immune response to Mycobacterium tuberculosis testing with the tests currently available - tuberculin skin test and interferon-gamma release assay (IGRA. The choice of treatment must take into account the efficacy and side effects associated with the same. This document provides updated recommendations on latent tuberculosis infection treatment. Topics covered include whom to test for TB and reviewed LTBI treatment regimens.
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Religiousness and Levels of Hazardous Alcohol Use: A Latent Profile Analysis.
Jankowski, Peter J; Hardy, Sam A; Zamboanga, Byron L; Ham, Lindsay S; Schwartz, Seth J; Kim, Su Yeong; Forthun, Larry F; Bersamin, Melina M; Donovan, Roxanne A; Whitbourne, Susan Krauss; Hurley, Eric A; Cano, Miguel Ángel
2015-10-01
Prior person-centered research has consistently identified a subgroup of highly religious participants that uses significantly less alcohol when compared to the other subgroups. The construct of religious motivation is absent from existing examinations of the nuanced combinations of religiousness dimensions within persons, and alcohol expectancy valuations have yet to be included as outcome variables. Variable-centered approaches have found religious motivation and alcohol expectancy valuations to play a protective role against individuals' hazardous alcohol use. The current study examined latent religiousness profiles and hazardous alcohol use in a large, multisite sample of ethnically diverse college students. The sample consisted of 7412 college students aged 18-25 (M age = 19.77, SD age = 1.61; 75% female; 61% European American). Three latent profiles were derived from measures of religious involvement, salience, and religious motivations: Quest-Intrinsic Religiousness (highest levels of salience, involvement, and quest and intrinsic motivations; lowest level of extrinsic motivation), Moderate Religiousness (intermediate levels of salience, involvement, and motivations) and Extrinsic Religiousness (lowest levels of salience, involvement, and quest and intrinsic motivations; highest level of extrinsic motivation). The Quest-Intrinsic Religiousness profile scored significantly lower on hazardous alcohol use, positive expectancy outcomes, positive expectancy valuations, and negative expectancy valuations, and significantly higher on negative expectancy outcomes, compared to the other two profiles. The Extrinsic and Moderate Religiousness profiles did not differ significantly on positive expectancy outcomes, negative expectancy outcomes, negative expectancy valuations, or hazardous alcohol use. The results advance existing research by demonstrating that the protective influence of religiousness on college students' hazardous alcohol use may involve high levels on
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Jensen, Robert
2006-01-01
This paper critically assesses the scholarship in introductory psychology textbooks in relation to the topic of latent learning. A review of the treatment of latent learning in 48 introductory psychology textbooks published between 1948 and 2004, with 21 of these texts published since 1999, reveals that the scholarship on the topic of latent learning demonstrated in introductory textbooks warrants improvement. Errors that persist in textbooks include the assertion that the latent learning experiments demonstrate unequivocally that reinforcement was not necessary for learning to occur, that behavioral theories could not account for the results of the latent learning experiments, that B. F. Skinner was an S-R association behaviorist who argued that reinforcement is necessary for learning to occur, and that because behavioral theories (including that of B. F. Skinner) were unable explain the results of the latent learning experiments the cognitive map invoked by Edward Tolman is the only explanation for latent learning. Finally, the validity of the cognitive map is typically accepted without question. Implications of the presence of these errors for students and the discipline are considered. Lastly, remedies are offered to improve the scholarship found in introductory psychology textbooks.
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Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S
2003-12-01
The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.
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Burrus, Robert T.; Jones, Adam T.; Schuhmann, Peter W.
2016-01-01
University students' latent attitudes toward capitalism were quantified and used to predict self-reported cheating behaviors. Results suggest that the relationship between student academic dishonesty and attitudes toward capitalism are complex. Students indicating a strong degree of risk aversion are less likely to report cheating behaviors.…
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Altszyler, Edgar; Ribeiro, Sidarta; Sigman, Mariano; Fernández Slezak, Diego
2017-11-01
Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words associations in text and to identify the meaning of target words. Word-embeddings have been extensively studied in large datasets, but only a few studies analyze semantic representations in small corpora. To fill this gap, we compared Skip-gram and Latent Semantic Analysis (LSA) capabilities to extract semantic associations from dream reports. LSA showed better performance than Skip-gram in small size corpora in two tests. Furthermore, LSA captured relevant word associations in dream collection, even in cases with low-frequency words or small numbers of dreams. Word associations in dreams reports can thus be quantified by LSA, which opens new avenues for dream interpretation and decoding. Copyright © 2017 Elsevier Inc. All rights reserved.
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Current management options for latent tuberculosis: a review
Directory of Open Access Journals (Sweden)
Norton BL
2012-11-01
Full Text Available Brianna L Norton, David P HollandDepartment of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USAAbstract: Tuberculosis remains the world’s second leading infectious cause of death, with nearly one-third of the global population latently infected. Treatment of latent tuberculosis infection is a mainstay of tuberculosis-control efforts in low-to medium-incidence countries. Isoniazid monotherapy has been the standard of care for decades, but its utility is impaired by poor completion rates. However, new, shorter-course regimens using rifamycins improve completion rates and are cost-saving compared with standard isoniazid monotherapy. We review the currently available therapies for latent tuberculosis infection and their toxicities and include a brief economic comparison of the different regimens.Keywords: isoniazid, rifampin, rifapentine, tuberculin skin test, interferon-gamma release assay
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Content Themes of Alcohol Advertising in U.S. Television-Latent Class Analysis.
Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W G; Stoolmiller, Michael; Sargent, James D
2015-09-01
There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in U.S. television. Studies of alcohol ads from 2 decades ago did not identify "Partying" as a social theme. Aim of this study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Content analysis of all ads from the top 20 U.S. beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. About half of the advertisements (46%) were aired between 3 am and 8 pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed 5 content classes that exploited the "Partying," "Quality," "Sports," "Manly," and "Relax" themes. The partying class, indicative of ad messages surrounding partying, love, and sex, was the dominant theme comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. Copyright © 2015 by the Research Society on Alcoholism.
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Content Themes of Alcohol Advertising in US Television — Latent Class Analysis
Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W.G.; Stoolmiller, Michael; Sargent, James D.
2015-01-01
Background There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in US television. Studies of alcohol ads from two decades ago did not identify “partying” as a social theme. Aim of the present study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Methods Content analysis of all ads from the top 20 US beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. Results About half of the advertisements (46%) were aired between 3am and 8pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed five content classes that exploited the “Partying”, “Quality”, “Sports”, “Manly”, and “Relax” themes. The partying class, indicative of ad messages surrounding partying, love and sex, was the dominant theme, comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. Conclusions This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. PMID:26207317
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Perturbative corrections for approximate inference in gaussian latent variable models
DEFF Research Database (Denmark)
Opper, Manfred; Paquet, Ulrich; Winther, Ole
2013-01-01
Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact b...... illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution. © 2013 Manfred Opper, Ulrich Paquet and Ole Winther....
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Lonigan, Christopher J; Goodrich, J Marc; Farver, JoAnn M
2018-04-01
Despite acknowledgment that language-minority children come from a wide variety of home language backgrounds and have a wide range of proficiency in their first (L1) and second (L2) languages, it is unknown whether differences across language-minority children in relative and absolute levels of proficiency in L1 and L2 predict subsequent development of literacy-related skills. The purpose of this study was to identify subgroups of language-minority children and evaluate whether differences in level and rate of growth of early literacy skills differed across subgroups. Five-hundred and twenty-six children completed measures of Spanish and English language and early literacy skills at the beginning, middle, and end of the preschool year. Latent growth models indicated that children's early literacy skills were increasing over the course of the preschool year. Latent profile analysis indicated that language-minority children could be classified into nine distinct groups, each with unique patterns of absolute and relative levels of proficiency in L1 and L2. Results of three-step mixture models indicated that profiles were closely associated with level of early literacy skills at the beginning of the preschool year. Initial level of early literacy skills was positively associated with growth in code-related skills (i.e., print knowledge, phonological awareness) and inversely associated with growth in language skills. These findings suggest that language-minority children are a diverse group with regard to their L1 and L2 proficiencies and that growth in early literacy skills is most associated with level of proficiency in the same language. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Karsberg, Sidsel; Armour, Cherie; Elklit, Ask
2014-09-01
The current study had two main aims. The first was to identify groups of adolescents based on their similarity of responding across a number of victimizing and potentially traumatic events (PTEs). In doing so, we employed the statistical technique of Latent Class Analysis (LCA). The second aim was to assess the relationship between our resultant classes and the covariates of gender, suicide attempt, and PTSD. Two hundred and sixty-nine Greenlandic school students, aged 12-18 (M = 15.4, SD = 1.84) were assessed for their level of exposure to PTEs. In addition, adolescents were assessed for the psychological impact of these events. A LCA was performed on seven binary indicators representing PTEs. Logistic regression was subsequently implemented to ascertain the relationships between latent classes and covariates. Three distinct classes were uncovered: a violence, neglect, and bullying class (class 1), a wide-ranging multiple PTE class (class 2), and a normative/baseline class (class 3). Notably, classes 1 and 2 were largely separated by the presence or absence of sexual PTEs. Individuals who reported having previously attempted suicide were almost six times more likely to be members of class 1 (OR = 5.97) and almost four times more likely to be members of class 2 (OR = 3.87) compared to the baseline class (class 3). Individuals who met the diagnostic criteria for PTSD were five times as likely to be members of class 1 and class 2 (OR = 5.09) compared to the baseline class. No significant associations were found between classes and gender. The results underline the complexity of the interplay between multiple victimization experiences, traumatization, and suicide attempts.
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Treatment of Latent Tuberculosis Infection: An Updated Network Meta-analysis.
Zenner, Dominik; Beer, Netta; Harris, Ross J; Lipman, Marc C; Stagg, Helen R; van der Werf, Marieke J
2017-08-15
Treatment of latent tuberculosis infection (LTBI) is an important component of tuberculosis (TB) control, and this study updates a previous network meta-analysis of the best LTBI treatment options to inform public health action and programmatic management of LTBI. To evaluate the comparative efficacy and harms of LTBI treatment regimens aimed at preventing active TB among adults and children. PubMed, Embase, and Web of Science from indexing to 8 May 2017; clinical trial registries; and conference abstracts. No language restrictions were applied. Randomized controlled trials that evaluated human LTBI treatments and recorded at least 1 of 2 prespecified end points (hepatotoxicity and prevention of active TB). 2 investigators independently extracted data from eligible studies and assessed study quality according to a standard protocol. The network meta-analysis of 8 new and 53 previously included studies showed that isoniazid regimens of 6 months (odds ratio [OR], 0.65 [95% credible interval {CrI}, 0.50 to 0.83]) or 12 to 72 months (OR, 0.50 [CrI, 0.41 to 0.62]), rifampicin-only regimens (OR, 0.41 [CrI, 0.19 to 0.85]), rifampicin-isoniazid regimens of 3 to 4 months (OR, 0.53 [CrI, 0.36 to 0.78]), rifampicin-isoniazid-pyrazinamide regimens (OR, 0.35 [CrI, 0.19 to 0.61]), and rifampicin-pyrazinamide regimens (OR, 0.53 [CrI, 0.33 to 0.84]) were efficacious compared with placebo. Evidence existed for efficacy of weekly rifapentine-isoniazid regimens compared with no treatment (OR, 0.36 [CrI, 0.18 to 0.73]). No conclusive evidence showed that HIV status altered treatment efficacy. Evidence was sparse for many comparisons and hepatotoxicity outcomes, and risk of bias was high or unknown for many studies. Evidence exists for the efficacy and safety of 6-month isoniazid monotherapy, rifampicin monotherapy, and combination therapies with 3 to 4 months of isoniazid and rifampicin. U.K. National Institute for Health Research. (PROSPERO: CRD42016037871).
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Harry Potter and the sorcerer's scope: latent scope biases in explanatory reasoning.
Khemlani, Sangeet S; Sussman, Abigail B; Oppenheimer, Daniel M
2011-04-01
What makes a good explanation? We examine the function of latent scope, i.e., the number of unobserved phenomena that an explanation can account for. We show that individuals prefer narrow latent scope explanations-those that account for fewer unobserved effects-to broader explanations. In Experiments 1a-d, participants found narrow latent scope explanations to be both more satisfying and more likely. In Experiment 2 we directly manipulated base rate information and again found a preference for narrow latent scope explanations. Participants in Experiment 3 evaluated more natural explanations of unexpected observations, and again displayed a bias for narrow latent scope explanations. We conclude by considering what this novel bias tells us about how humans evaluate explanations and engage in causal reasoning.
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Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation
Institute of Scientific and Technical Information of China (English)
Tian Dongping
2017-01-01
In recent years, multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas, especially for automatic image annotation, whose purpose is to provide an efficient and effective searching environment for users to query their images more easily.In this paper, a semi-supervised learning based probabilistic latent semantic analysis ( PL-SA) model for automatic image annotation is presenred.Since it' s often hard to obtain or create la-beled images in large quantities while unlabeled ones are easier to collect, a transductive support vector machine ( TSVM) is exploited to enhance the quality of the training image data.Then, differ-ent image features with different magnitudes will result in different performance for automatic image annotation.To this end, a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible.Finally, a PLSA model with asymmetric mo-dalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores.Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PL-SA for the task of automatic image annotation.
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Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
Directory of Open Access Journals (Sweden)
Rita Ismayilova
2014-01-01
Full Text Available Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19% reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan.
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Dynamic Latent Classification Model
DEFF Research Database (Denmark)
Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre
as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...
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Multivariate data analysis approach to understand magnetic properties of perovskite manganese oxides
International Nuclear Information System (INIS)
Imamura, N.; Mizoguchi, T.; Yamauchi, H.; Karppinen, M.
2008-01-01
Here we apply statistical multivariate data analysis techniques to obtain some insights into the complex structure-property relations in antiferromagnetic (AFM) and ferromagnetic (FM) manganese perovskite systems, AMnO 3 . The 131 samples included in the present analyses are described by 21 crystal-structure or crystal-chemical (CS/CC) parameters. Principal component analysis (PCA), carried out separately for the AFM and FM compounds, is used to model and evaluate the various relationships among the magnetic properties and the various CS/CC parameters. Moreover, for the AFM compounds, PLS (partial least squares projections to latent structures) analysis is performed so as to predict the magnitude of the Neel temperature on the bases of the CS/CC parameters. Finally, so-called PLS-DA (PLS discriminant analysis) method is employed to find out the most influential/characteristic CS/CC parameters that differentiate the two classes of compounds from each other. - Graphical abstract: Statistical multivariate data analysis techniques are applied to detect structure-property relations in antiferromagnetic (AFM) and ferromagnetic (FM) manganese perovskites. For AFM compounds, partial least squares projections to latent structures analysis predict the magnitude of the Neel temperature on the bases of structural parameters only. Moreover, AFM and FM compounds are well separated by means of so-called partial least squares discriminant analysis method
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A Latent Class Approach to Estimating Test-Score Reliability
van der Ark, L. Andries; van der Palm, Daniel W.; Sijtsma, Klaas
2011-01-01
This study presents a general framework for single-administration reliability methods, such as Cronbach's alpha, Guttman's lambda-2, and method MS. This general framework was used to derive a new approach to estimating test-score reliability by means of the unrestricted latent class model. This new approach is the latent class reliability…
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National policies on the management of latent tuberculosis infection: review of 98 countries
Jagger, Ann; Reiter-karam, Silke; Getahun, Haileyesus
2018-01-01
Abstract Objective To review policies on management of latent tuberculosis infection in countries with low and high burdens of tuberculosis. Methods We divided countries reporting data to the World Health Organization (WHO) Global Tuberculosis Programme into low and high tuberculosis burden, based on WHO criteria. We identified national policy documents on management of latent tuberculosis through online searches, government websites, WHO country offices and personal communication with programme managers. We made a descriptive analysis with a focus on policy gaps and deviations from WHO policy recommendations. Findings We obtained documents from 68 of 113 low-burden countries and 30 of 35 countries with the highest burdens of tuberculosis or human immunodeficiency virus (HIV)-associated tuberculosis. Screening and treatment of latent tuberculosis infection in people living with HIV was recommended in guidelines of 29 (96.7%) high-burden and 54 (79.7%) low-burden countries. Screening for children aged countries. In most high-burden countries the recommendation was symptom screening alone before treatment, whereas in all low-burden countries it was testing before treatment. Some low-burden countries’ policies did not comply with WHO recommendations: nine (13.2%) recommended tuberculosis preventive treatment for travellers to high-burden countries and 10 (14.7%) for patients undergoing abdominal surgery. Conclusion Lack of solid evidence on certain aspects of management of latent tuberculosis infection results in national policies which vary considerably. This highlights a need to advance research and develop clear, implementable and evidence-based WHO policies. PMID:29531416
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Tuberculosis and latent tuberculosis infection among healthcare workers in Kisumu, Kenya.
Agaya, Janet; Nnadi, Chimeremma D; Odhiambo, Joseph; Obonyo, Charles; Obiero, Vincent; Lipke, Virginia; Okeyo, Elisha; Cain, Kevin; Oeltmann, John E
2015-12-01
To assess prevalence and occupational risk factors of latent TB infection and history of TB disease ascribed to work in a healthcare setting in western Kenya. We conducted a cross-sectional survey among healthcare workers in western Kenya in 2013. They were recruited from dispensaries, health centres and hospitals that offer both TB and HIV services. School workers from the health facilities' catchment communities were randomly selected to serve as the community comparison group. Latent TB infection was diagnosed by tuberculin skin testing. HIV status of participants was assessed. Using a logistic regression model, we determined the adjusted odds of latent TB infection among healthcare workers compared to school workers; and among healthcare workers only, we assessed work-related risk factors for latent TB infection. We enrolled 1005 healthcare workers and 411 school workers. Approximately 60% of both groups were female. A total of 22% of 958 healthcare workers and 12% of 392 school workers tested HIV positive. Prevalence of self-reported history of TB disease was 7.4% among healthcare workers and 3.6% among school workers. Prevalence of latent TB infection was 60% among healthcare workers and 48% among school workers. Adjusted odds of latent TB infection were 1.5 times higher among healthcare workers than school workers (95% confidence interval 1.2-2.0). Healthcare workers at all three facility types had similar prevalence of latent TB infection (P = 0.72), but increasing years of employment was associated with increased odds of LTBI (P Kenya which offer TB and HIV services are at increased risk of latent TB infection, and the risk is similar across facility types. Implementation of WHO-recommended TB infection control measures are urgently needed in health facilities to protect healthcare workers. © 2015 John Wiley & Sons Ltd.
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Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter
2013-01-01
The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.
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Directory of Open Access Journals (Sweden)
Liesje Coertjens
Full Text Available The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.
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Gygi, Jasmin T.; Fux, Elodie; Grob, Alexander; Hagmann-von Arx, Priska
2016-01-01
This study examined measurement invariance and latent mean differences in the German version of the Reynolds Intellectual Assessment Scales (RIAS) for 316 individuals with a migration background (defined as speaking German as a second language) and 316 sex- and age-matched natives. The RIAS measures general intelligence (single-factor structure) and its two components, verbal and nonverbal intelligence (two-factor structure). Results of a multi-group confirmatory factor analysis showed scalar invariance for the two-factor and partial scalar invariance for the single-factor structure. We conclude that the two-factor structure of the RIAS is comparable across groups. Hence, verbal and nonverbal intelligence but not general intelligence should be considered when comparing RIAS test results of individuals with and without a migration background. Further, latent mean differences especially on the verbal, but also on the nonverbal intelligence index indicate language barriers for individuals with a migration background, as subtests corresponding to verbal intelligence require higher skills in German language. Moreover, cultural, environmental, and social factors that have to be taken into account when assessing individuals with a migration background are discussed. PMID:27846270
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Directory of Open Access Journals (Sweden)
Jasmin T Gygi
Full Text Available This study examined measurement invariance and latent mean differences in the German version of the Reynolds Intellectual Assessment Scales (RIAS for 316 individuals with a migration background (defined as speaking German as a second language and 316 sex- and age-matched natives. The RIAS measures general intelligence (single-factor structure and its two components, verbal and nonverbal intelligence (two-factor structure. Results of a multi-group confirmatory factor analysis showed scalar invariance for the two-factor and partial scalar invariance for the single-factor structure. We conclude that the two-factor structure of the RIAS is comparable across groups. Hence, verbal and nonverbal intelligence but not general intelligence should be considered when comparing RIAS test results of individuals with and without a migration background. Further, latent mean differences especially on the verbal, but also on the nonverbal intelligence index indicate language barriers for individuals with a migration background, as subtests corresponding to verbal intelligence require higher skills in German language. Moreover, cultural, environmental, and social factors that have to be taken into account when assessing individuals with a migration background are discussed.
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Directory of Open Access Journals (Sweden)
David P Kao
Full Text Available Heart failure patients with reduced ejection fraction (HFREF are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF.A total of 1121 patients with nonischemic HFREF from the β-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial.A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes.The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate development of personalized
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Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype
Frewen, Paul A.; Brown, Matthew F. D.; Steuwe, Carolin; Lanius, Ruth A.
2015-01-01
Objective A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. Method We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. Conclusions The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD. PMID:25854673
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Directory of Open Access Journals (Sweden)
Anak Agung Putri Ratna
2017-06-01
Full Text Available Computerized cross-language plagiarism detection has recently become essential. With the scarcity of scientific publications in Bahasa Indonesia, many Indonesian authors frequently consult publications in English in order to boost the quantity of scientific publications in Bahasa Indonesia (which is currently rising. Due to the syntax disparity between Bahasa Indonesia and English, most of the existing methods for automated cross-language plagiarism detection do not provide satisfactory results. This paper analyses the probability of developing Latent Semantic Analysis (LSA for a computerized cross-language plagiarism detector for two languages with different syntax. To improve performance, various alterations in LSA are suggested. By using a linear vector quantization (LVQ classifier in the LSA and taking into account the Frobenius norm, output has reached up to 65.98% in accuracy. The results of the experiments showed that the best accuracy achieved is 87% with a document size of 6 words, and the document definition size must be kept below 10 words in order to maintain high accuracy. Additionally, based on experimental results, this paper suggests utilizing the frequency occurrence method as opposed to the binary method for the term–document matrix construction.
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A latent class analysis of cancer risk behaviors among U.S. college students.
Kang, Joseph; Ciecierski, Christina Czart; Malin, Emily L; Carroll, Allison J; Gidea, Marian; Craft, Lynette L; Spring, Bonnie; Hitsman, Brian
2014-07-01
The purpose of this study is to understand how cancer risk behaviors cluster in U.S. college students and vary by race and ethnicity. Using the fall 2010 wave of the National College Health Assessment (NCHA), we conducted a latent class analysis (LCA) to evaluate the clustering of cancer risk behaviors/conditions: tobacco use, physical inactivity, unhealthy diet, alcohol binge drinking, and overweight/obesity. The identified clusters were then examined separately by students' self-reported race and ethnicity. Among 30,093 college students surveyed, results show a high prevalence of unhealthy diet as defined by insufficient fruit and vegetable intake (>95%) and physical inactivity (>60%). The LCA identified behavioral clustering for the entire sample and distinct clustering among Black and American Indian students. Cancer risk behaviors/conditions appear to cluster among college students differentially by race. Understanding how risk behaviors cluster in young adults can lend insight to racial disparities in cancer through adulthood. Health behavior interventions focused on modifying multiple risk behaviors and tailored to students' racial group could potentially have a much larger effect on cancer prevention than those targeting any single behavior. Copyright © 2014 Elsevier Inc. All rights reserved.
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Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype
Directory of Open Access Journals (Sweden)
Paul A. Frewen
2015-04-01
Full Text Available Objective: A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD. However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5 currently does not assess depersonalization and derealization. Method: We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results: A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1 severe or 2 moderate PTSD symptom severity (D-PTSD classes. Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1 Reexperiencing, 2 Emotional Numbing/Anhedonia, 3 Dissociation, 4 Negative Alterations in Cognition & Mood, 5 Avoidance, and 6 Hyperarousal. Conclusions: The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.
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Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype.
Frewen, Paul A; Brown, Matthew F D; Steuwe, Carolin; Lanius, Ruth A
2015-01-01
A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.
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Mental toughness latent profiles in endurance athletes.
Zeiger, Joanna S; Zeiger, Robert S
2018-01-01
Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female). Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ), Psychological Performance Inventory-Alternative (PPI-A), and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE). A three-class solution emerged, designated as high mental toughness (High MT), moderate mental toughness (Moderate MT) and low mental toughness (Low MT). ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; Pathletes who were over 55 compared to those who were 18-34 (OR = 2.52; 95% CI, 1.37, 4.62; Pathletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training.
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Competing risk model for reduction in life expectancy from radiogenic latent cancer
International Nuclear Information System (INIS)
Davis, H.T.
1978-01-01
Because of the large number of persons who could potentially receive low doses of radiation as a result of a nuclear reactor accident, the number of fatalities from latent cancers is generally larger than the early, or prompt, fatalities. For this reason the latent cancer fatality risk of reactor accidents is perceived as being more important than the early fatality risk. In addition, there exists the temptation to add the latent cancer fatality risk to the early fatality risk for the purpose of comparing reactor accident risks to other risks that society is exposed to, such as automobile accidents, airplane accidents, hurricanes, etc. However, the impact on the individual, and society as a whole, due to latent cancer fatalities is significantly different from the impact produced by early fatalities. Early fatalities generally result in appreciable life shortening for the affected individual while latent cancer fatalities generally result in very limited life shortening. A mathematical model was developed to express the reduction in life expectancy due to latent radiogenic cancer as a function of dose received
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DEFF Research Database (Denmark)
Weiss, Harold B.; Kaplan, Sigal; Prato, Carlo Giacomo
2016-01-01
, infrastructure characteristics, environmental conditions, demographic characteristics, driving behaviour, and pre-crash manoeuvres. The analysis yielded 15 and 8 latent classes of, respectively, single-vehicle and multi-vehicle crashes, and average posterior probabilities measured the odds of correct...
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Directory of Open Access Journals (Sweden)
Angelika Glöckner-Rist
2011-12-01
Full Text Available This paper investigates whether there are different patterns of traditionality in different countries with regard to a perceived negative impact of labor-force participation of mothers on their children and family life. For this purpose, individual-level traditionality subgroups and segments of countries with different traditionality patterns of their nationals were identified simultaneously by means of multilevel latent-class (ML-LC analysis of the answers to three items of the Changing Family and Gender Roles module of the International Social Survey Program (ISSP. This module was fielded in 22 countries in the years 1994 and 2002. Six individual-level subgroups and five country segments can be discerned. The structure of individual-level subgroups is almost identical in both years. Four individual-level subgroups differ only quantitatively in their level of traditionality. Two further subgroups are characterized by a unique tendency to defend working mothers against criticism. From 1994 to 2002 the sizes of traditional subgroups decrease, and there is also some change in the composition of country segments. This paper investigates whether there are different patterns of traditionality in different countries with regard to a perceived negative impact of labor-force participation of mothers on their children and family life. For this purpose, individual-level traditionality subgroups and segments of countries with different traditionality patterns of their nationals were identified simultaneously by means of multilevel latent-class (ML-LC analysis of the answers to three items of the Changing Family and Gender Roles module of the International Social Survey Program (ISSP. This module was fielded in 22 countries in the years 1994 and 2002. Six individual-level subgroups and five country segments can be discerned. The structure of individual-level subgroups is almost identical in both years. Four individual-level subgroups differ only
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Hildebrandt, Mario; Kiltz, Stefan; Krapyvskyy, Dmytro; Dittmann, Jana; Vielhauer, Claus; Leich, Marcus
2011-11-01
A machine-assisted analysis of traces from crime scenes might be possible with the advent of new high-resolution non-destructive contact-less acquisition techniques for latent fingerprints. This requires reliable techniques for the automatic extraction of fingerprint features from latent and exemplar fingerprints for matching purposes using pattern recognition approaches. Therefore, we evaluate the NIST Biometric Image Software for the feature extraction and verification of contact-lessly acquired latent fingerprints to determine potential error rates. Our exemplary test setup includes 30 latent fingerprints from 5 people in two test sets that are acquired from different surfaces using a chromatic white light sensor. The first test set includes 20 fingerprints on two different surfaces. It is used to determine the feature extraction performance. The second test set includes one latent fingerprint on 10 different surfaces and an exemplar fingerprint to determine the verification performance. This utilized sensing technique does not require a physical or chemical visibility enhancement of the fingerprint residue, thus the original trace remains unaltered for further investigations. No particular feature extraction and verification techniques have been applied to such data, yet. Hence, we see the need for appropriate algorithms that are suitable to support forensic investigations.
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Two distinct phenotypes of asthma in elite athletes identified by latent class analysis.
Couto, Mariana; Stang, Julie; Horta, Luís; Stensrud, Trine; Severo, Milton; Mowinckel, Petter; Silva, Diana; Delgado, Luís; Moreira, André; Carlsen, Kai-Håkon
2015-01-01
Clusters of asthma in athletes have been insufficiently studied. Therefore, the present study aimed to characterize asthma phenotypes in elite athletes using latent class analysis (LCA) and to evaluate its association with the type of sport practiced. In the present cross-sectional study, an analysis of athletes' records was carried out in databases of the Portuguese National Anti-Doping Committee and the Norwegian School of Sport Sciences. Athletes with asthma, diagnosed according to criteria given by the International Olympic Committee, were included for LCA. Sports practiced were categorized into water, winter and other sports. Of 324 files screened, 150 files belonged to asthmatic athletes (91 Portuguese; 59 Norwegian). LCA retrieved two clusters: "atopic asthma" defined by allergic sensitization, rhinitis and allergic co-morbidities and increased exhaled nitric oxide levels; and "sports asthma", defined by exercise-induced respiratory symptoms and airway hyperesponsiveness without allergic features. The risk of developing the phenotype "sports asthma" was significantly increased in athletes practicing water (OR = 2.87; 95% CI [1.82-4.51]) and winter (OR = 8.65; 95% CI [2.67-28.03]) sports, when compared with other athletes. Two asthma phenotypes were identified in elite athletes: "atopic asthma" and "sports asthma". The type of sport practiced was associated with different phenotypes: water and winter sport athletes had three- and ninefold increased risk of "sports asthma". Recognizing different phenotypes is clinically relevant as it would lead to distinct targeted treatments.
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PET CT Identifies Reactivation Risk in Cynomolgus Macaques with Latent M. tuberculosis.
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Philana Ling Lin
2016-07-01
Full Text Available Mycobacterium tuberculosis infection presents across a spectrum in humans, from latent infection to active tuberculosis. Among those with latent tuberculosis, it is now recognized that there is also a spectrum of infection and this likely contributes to the variable risk of reactivation tuberculosis. Here, functional imaging with 18F-fluorodeoxygluose positron emission tomography and computed tomography (PET CT of cynomolgus macaques with latent M. tuberculosis infection was used to characterize the features of reactivation after tumor necrosis factor (TNF neutralization and determine which imaging characteristics before TNF neutralization distinguish reactivation risk. PET CT was performed on latently infected macaques (n = 26 before and during the course of TNF neutralization and a separate set of latently infected controls (n = 25. Reactivation occurred in 50% of the latently infected animals receiving TNF neutralizing antibody defined as development of at least one new granuloma in adjacent or distant locations including extrapulmonary sites. Increased lung inflammation measured by PET and the presence of extrapulmonary involvement before TNF neutralization predicted reactivation with 92% sensitivity and specificity. To define the biologic features associated with risk of reactivation, we used these PET CT parameters to identify latently infected animals at high risk for reactivation. High risk animals had higher cumulative lung bacterial burden and higher maximum lesional bacterial burdens, and more T cells producing IL-2, IL-10 and IL-17 in lung granulomas as compared to low risk macaques. In total, these data support that risk of reactivation is associated with lung inflammation and higher bacterial burden in macaques with latent Mtb infection.
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Lange, Rense
2015-02-01
An extension of concurrent validity is proposed that uses qualitative data for the purpose of validating quantitative measures. The approach relies on Latent Semantic Analysis (LSA) which places verbal (written) statements in a high dimensional semantic space. Using data from a medical / psychiatric domain as a case study - Near Death Experiences, or NDE - we established concurrent validity by connecting NDErs qualitative (written) experiential accounts with their locations on a Rasch scalable measure of NDE intensity. Concurrent validity received strong empirical support since the variance in the Rasch measures could be predicted reliably from the coordinates of their accounts in the LSA derived semantic space (R2 = 0.33). These coordinates also predicted NDErs age with considerable precision (R2 = 0.25). Both estimates are probably artificially low due to the small available data samples (n = 588). It appears that Rasch scalability of NDE intensity is a prerequisite for these findings, as each intensity level is associated (at least probabilistically) with a well- defined pattern of item endorsements.
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Lee, Hyoin; Jung, Seungmoon; Lee, Peter; Jeong, Yong
2017-10-01
epileptogenesis were examined by graph theoretical network analysis. Interestingly, increase in the power of low frequency oscillations was observed during the latent period. These results suggest that, even if there are no apparent ictal seizure events during the latent period, there are ongoing changes in the rsFC in the epileptic brain. Furthermore, these results suggest that the pathophysiology of epilepsy may be related to widespread altered intrinsic functional connectivity. These findings can help enhance our understanding of epileptogenesis, and accordingly, changes in intrinsic functional connectivity can serve as an early diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.
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Siphai, Sunan; Srisa-ard, Boonchoom
2015-01-01
The purpose of this study was 1) to develop good citizenship indicators of Rajabhat Universities' Students in the Northeast of Thailand. 2) to classify latent profile of good citizenship of Rajabhat University's students in the northeast of Thailand. The sample was 800 Rajabhat University's students in the northeast of Thailand. Findings 1) there…
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Skin Resistivity Value of Upper Trapezius Latent Trigger Points
Directory of Open Access Journals (Sweden)
Elżbieta Skorupska
2015-01-01
Full Text Available Introduction. The skin resistivity (SkR measurement is commonly recommended for acupoints measurement, but for trigger points (TrPs only one study is available. The purpose of the study was to evaluate SkR for latent TrPs compared to non-TrPs and the surrounding tissue. Material and Methods. Forty-two healthy volunteers with unilateral latent upper trapezius TrPs (12 men, 30 women aged 21–23 (mean age: 22.1 ± 0.6 y participated in the study. Keithley electrometer 610B was used for measuring SkR (Ag/AgCl self-adhesive, disposable ground electrode: 30 mm diameter. SkR was measured for latent TrPs and compared to opposite non-TrPs sites and the surrounding tissue. Results. The SkR decrease of TrPs-positive sites as compared to TrPs-negative sites and the surrounding tissue was confirmed. However, no statistically significant difference in the SkR value occurred when all data were analyzed. The same was confirmed after gender division and for TrPs-positive subjects examined for referred pain and twitch response presence. Conclusion. SkR reactive changes at latent TrPs are possible but the results were not consistent with the previous study. Thus, caution in applying SkR to latent TrPs isolation is recommended and its clinical use should not be encouraged yet. Further studies, especially on active TrPs, are yet required.
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Inverse Ising problem in continuous time: A latent variable approach
Donner, Christian; Opper, Manfred
2017-12-01
We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.
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The structure and stability of common mental disorders - The NEMESIS Study
Vollebergh, W.A.M.; Iedema, J; Bijl, R.V.; de Graaf, R.; Smit, F.; Ormel, J.
Background: We analyzed the underlying latent structure of 12-month DSM-III-R diagnoses of 9 common disorders for the general population in the Netherlands. In addition, we sought to establish (1) the stability of the latent structure underlying mental disorders across a 1-year period (structural
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Detection of herpes simplex virus-specific DNA sequences in latently infected mice and in humans.
Efstathiou, S; Minson, A C; Field, H J; Anderson, J R; Wildy, P
1986-02-01
Herpes simplex virus-specific DNA sequences have been detected by Southern hybridization analysis in both central and peripheral nervous system tissues of latently infected mice. We have detected virus-specific sequences corresponding to the junction fragment but not the genomic termini, an observation first made by Rock and Fraser (Nature [London] 302:523-525, 1983). This "endless" herpes simplex virus DNA is both qualitatively and quantitatively stable in mouse neural tissue analyzed over a 4-month period. In addition, examination of DNA extracted from human trigeminal ganglia has shown herpes simplex virus DNA to be present in an "endless" form similar to that found in the mouse model system. Further restriction enzyme analysis of latently infected mouse brainstem and human trigeminal DNA has shown that this "endless" herpes simplex virus DNA is present in all four isomeric configurations.
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Comorbidity profiles of psoriasis in Taiwan: A latent class analysis.
Wu, Chen-Yi; Hu, Hsiao-Yun; Li, Chung-Pin; Chou, Yiing-Jeng; Chang, Yun-Ting
2018-01-01
Psoriasis is associated with many comorbidities. An understanding of these comorbidity patterns can help foster better care of patients with psoriasis. To identify the heterogeneity of psoriasis comorbidities using latent class analysis (LCA). LCA was used to empirically identify psoriasis comorbidity patterns in a nationwide sample of 110,729 incident cases of psoriasis (2002-2012) from the National Health Insurance database in Taiwan. The mean age of incident psoriasis was 46.1 years. Hypertension (28.8%), dyslipidemia (18.9%), and chronic liver disease/cirrhosis/hepatitis (18.1%) were the top three comorbidities in patients with psoriasis. LCA identified four distinct comorbidity classes among these patients, including 9.9% of patients in the "multi-comorbidity" class, 17.9% in the "metabolic syndrome" class, 11.3% in the "hypertension and chronic obstructive pulmonary disease (COPD)" class, and 60.9% in the "relatively healthy" class. Psoriatic arthritis was evenly distributed among each class. Relative to membership in the "relative healthy" class, an increase of one year of age had a higher probability of membership in the "multi-comorbidity" (odds ratio [OR], 1.25), "metabolic syndrome" (OR, 1.11), or "hypertension and COPD" (OR, 1.34) classes. Relative to membership in the "relative healthy" class, compared to women, men had a higher probability of membership in the "multi-comorbidity" (OR, 1.39), "metabolic syndrome" (OR, 1.77), or "hypertension and COPD" (OR, 1.22) classes. We observed four distinct classes of psoriasis comorbidities, including the "multi-comorbidity", "metabolic syndrome", "hypertension and COPD", and "relatively healthy" classes, as well as the clustering of liver diseases with metabolic syndrome and clustering of COPD with hypertension.
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Chuma, Clotrida; Kihunrwa, Albert; Matovelo, Dismas; Mahendeka, Marietha
2014-02-12
Interventions given to women admitted in latent or active phase of labor may influence the outcomes of labor and ameliorate complications which can affect the mother and fetus. Labour management, maternal and fetal outcomes among low risk women presenting both in latent phase and active phase of labour in Tanzania have not recently been explored. This was a descriptive cross-sectional study. It was done from February to April 2013. Case notes were collected serially until the sample size was reached. A structured checklist was used to extract data. Data was analyzed using SPSS version 17. A p women were collected, half of each presented in latent phase and active phase of labour. Key interventions including augmentation with oxytocin, artificial rupture of membranes and caesarean section were significantly higher in the latent phase group than the active phase group 84(33.6%) versus 52(20.8%) p women admitted initially in active phase than in latent phase groups 180(72.0%), versus 153(61.2%) p > 0.01). There were more women in the active phase group who sustained genital tract tear and postpartum haemorrhage than in the latent phase group 101(18.6%), versus 38(15.6%) p women admitted at BMC in latent phase of labour are subjected to more obstetric interventions than those admitted in the active phase. There is need to produce guidelines on management of women admitted in latent phase of labour at BMC to reduce the risk of unnecessary interventions.
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Felder, Jennifer N; Roubinov, Danielle; Bush, Nicole R; Coleman-Phox, Kimberly; Vieten, Cassandra; Laraia, Barbara; Adler, Nancy E; Epel, Elissa
2018-02-28
We examined whether prenatal mindfulness training was associated with lower depressive symptoms through 18-months postpartum compared to treatment as usual (TAU). A controlled, quasi-experimental trial compared prenatal mindfulness training (MMT) to TAU. We collected depressive symptom data at post-intervention, 6-, and 18-months postpartum. Latent profile analysis identified depressive symptom profiles, and multinomial logistic regression examined whether treatment condition predicted profile. Three depressive symptom severity profiles emerged: none/minimal, mild, and moderate. Adjusting for relevant covariates, MMT participants were less likely than TAU participants to be in the moderate profile than the none/minimal profile (OR = 0.13, 95% CI = 0.03-0.54, p = .005). Prenatal mindfulness training may have benefits for depressive symptoms during the transition to parenthood. © 2018 Wiley Periodicals, Inc.
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Torgersen, Leila; Ystrom, Eivind; Siega-Riz, Anna Maria; Berg, Cecilie Knoph; Zerwas, Stephanie C; Reichborn-Kjennerud, Ted; Bulik, Cynthia M
2015-01-01
Knowledge of infant diet and feeding practices among children of mothers with eating disorders is essential to promote healthy eating in these children. This study compared the dietary patterns of 6-month-old children of mothers with anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified-purging subtype, to the diet of children of mothers with no eating disorders (reference group). The study was based on 53,879 mothers in the Norwegian Mother and Child Cohort Study (MoBa). Latent class analysis (LCA) was used to identify discrete latent classes of infant diet based on the mothers' responses to questions about 16 food items. LCA identified five classes, characterized by primarily homemade vegetarian food (4% of infants), homemade traditional food (8%), commercial cereals (35%), commercial jarred baby food (39%), and a mix of all food groups (11%). The association between latent dietary classes and maternal eating disorders were estimated by multinomial logistic regression. Infants of mothers with bulimia nervosa had a lower probability of being in the homemade traditional food class compared to the commercial jarred baby food class, than the referent (O.R. 0.59; 95% CI 0.36-0.99). Infants of mothers with binge eating disorder had a lower probability of being in the homemade vegetarian class compared to the commercial jarred baby food class (O.R. 0.77; 95% CI 0.60-0.99), but only before adjusting for relevant confounders. Anorexia nervosa and eating disorder not otherwise specified-purging subtype were not statistically significantly associated with any of the dietary classes. These results suggest that maternal eating disorders may to some extent influence the child's diet at 6 months; however, the extent to which these differences influence child health and development remains an area for further inquiry. Copyright © 2014 Elsevier Ltd. All rights reserved.
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31P-magnetic resonance spectroscopy: Impaired energy metabolism in latent hyperthyroidism
International Nuclear Information System (INIS)
Theissen, P.; Kaldewey, S.; Moka, D.; Bunke, J.; Voth, E.; Schicha, H.
1993-01-01
31 Phosphorous magnetic resonance spectroscopy allows an in vivo examination of energy metabolism. The present study was designed to evaluate whether in patients with latent hyperthyroidism alterations of muscle energy metabolism could be found similar to those observed in patients with overt hyperthyroidism. In 10 patients with overt hyperthyroidism before therapy and 20 with latent hyperthyroidism (also without therapy) and in 24 healthy volunteers magnetic resonance spectroscopy of the calf muscle was performed within a 1.5-Tesla magnet. Muscle concentrations of phosphocreatine, inorganic phosphate, and ATP were quantified compared to an external standard solution of K 2 HPO 4 . In the patients with overt hyperthyroidism and with latent hyperthyroidism a significant decrease of phosphocreatine was found. Further, the ATP concentration in patients with latent and manifest hyperthyroidism tended towards lower values. There were no significant differences in the decrease of phosphocreatine and ATP between both patient groups. Therefore, this study for the first time shows that alterations of energy metabolism in latent hyperthyroidism can be measured and that they are similar to those observed in overt hyperthyroidism. (orig.) [de
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Convective and Stratiform Precipitation Processes and their Relationship to Latent Heating
Tao, Wei-Kuo; Lang, Steve; Zeng, Xiping; Shige, Shoichi; Takayabu, Yukari
2009-01-01
The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. An improved convective -stratiform heating (CSH) algorithm has been developed to obtain the 3D structure of cloud heating over the Tropics based on two sources of information: 1) rainfall information, namely its amount and the fraction due to light rain intensity, observed directly from the Precipitation Radar (PR) on board the TRMM satellite and 2) synthetic cloud physics information obtained from cloud-resolving model (CRM) simulations of cloud systems. The cloud simulations provide details on cloud processes, specifically latent heating, eddy heat flux convergence and radiative heating/cooling, that. are not directly observable by satellite. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. One of the major differences between new and old algorithms is that the level of maximum cloud heating occurs 1 to 1.5 km lower in the atmosphere in the new algorithm. This can effect the structure of the implied air currents associated with the general circulation of the atmosphere in the Tropics. The new CSH algorithm will be used provide retrieved heating data to other heating algorithms to supplement their performance.
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Directory of Open Access Journals (Sweden)
Leonardo Rodriguez-Urrego
2015-01-01
Full Text Available This paper presents a fault diagnosis application of the Latent Nestling Method to IGBTs. The paper extends the Latent Nestling Method based in Coloured Petri Nets (CPNs to hybrid systems in such a manner that IGBTs performance can be modeled. CPNs allow for an enhanced capability for synthesis and modeling in contrast to the classical phenomena of combinational state explosion when Finite State Machine methods are applied. We present an IGBT model with different fault modes including those of intermittent nature that can be used advantageously as predictive symptoms within a predictive maintenance strategy. Ageing stress tests have been experimentally applied to the IGBTs modules and intermittent faults are diagnosed as precursors of permanent failures. In addition, ageing is validated with morphological analysis (Scanning Electron Microscopy and semiqualitative analysis (Energy Dispersive Spectrometry.
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Psychological features of North Korean female refugees on the MMPI-2: latent profile analysis.
Kim, Seong-Hyeon; Kim, Hee Kyung; Lee, Narae
2013-12-01
This study examined the heterogeneity in the Minnesota Multiphasic Personality Inventory-2nd Edition (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) profiles of North Korean female refugee population (N = 2,163) using latent profile analysis (LPA). The North Korean female refugee sample arrived at Hanawon, South Korea's resettlement center for North Korean refugees in 2008 and 2009 and took the MMPI-2 as part of an initial psychological screen. The analysis, which included the T scores of the 6 validity scales and the 10 standard clinical scales, identified 4 classes with distinctive psychological features: Class 1 (nonclinical), Class 2 (demoralized), Class 3 (somatized), and Class 4 (detached). The 4 covariates entered into the model (age, education, affiliation with a religion, and the number of forced repatriations) impacted the likelihood of belonging to certain classes. As hypothesized, older age, fewer years of education, and more incidents of forced repatriation predicted higher proneness to psychopathology. However, contrary to our expectation, having a religious faith did not emerge as a salient protective factor. The current LPA results revealed distinct heterogeneous subgroups that previous research on the MMPI and MMPI-2 profiles of refugee populations overlooked with the assumption of a homogeneous sample. Clinical implications for the treatment of North Korean female refugees and the limitations of the study are discussed. (c) 2013 APA, all rights reserved.
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A solar air collector with integrated latent heat thermal storage
Directory of Open Access Journals (Sweden)
Klimes Lubomir
2012-04-01
Full Text Available Simulations of the behaviour of a solar air collector with integrated latent heat thermal storage were performed. The model of the collector was created with the use of coupling between TRNSYS 17 and MATLAB. Latent heat storage (Phase Change Material - PCM was integrated with the solar absorber. The model of the latent heat storage absorber was created in MATLAB and the model of the solar air collector itself was created in TRNSYS with the use of TYPE 56. The model of the latent heat storage absorber allows specification of the PCM properties as well as other parameters. The simulated air collector was the front and back pass collector with the absorber in the middle of the air cavity. Two variants were considered for comparison; the light-weight absorber made of sheet metal and the heat-storage absorber with the PCM. Simulations were performed for the climatic conditions of the Czech Republic (using TMY weather data.
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An introduction to latent variable growth curve modeling concepts, issues, and application
Duncan, Terry E; Strycker, Lisa A
2013-01-01
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples.Updated throughout, the second edition features three new chapters-growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group is...
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Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
Leite, Walter L.; Stapleton, Laura M.
2011-01-01
In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…
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Evenson, Kelly R; Wen, Fang; Hales, Derek; Herring, Amy H
2016-05-03
Applying latent class analysis (LCA) to accelerometry can help elucidated underlying patterns. This study described the patterns of accelerometer-determined sedentary behavior and physical activity among youth by applying LCA to a nationally representative United States (US) sample. Using 2003-2006 National Health and Nutrition Examination Survey data, 3998 youths 6-17 years wore an ActiGraph 7164 accelerometer for one week, providing > =3 days of wear for > =8 h/day from 6:00 am-midnight. Cutpoints defined sedentary behavior ( = 2296 counts/minute), and vigorous activity (> = 4012 counts/minute). To account for wear time differences, outcomes were expressed as percent of day in a given intensity. LCA was used to classify daily (Monday through Sunday) patterns of average counts/minute, sedentary behavior, light activity, MVPA, and vigorous activity separately. The latent classes were explored overall and by age (6-11, 12-14, 15-17 years), gender, and whether or not youth attended school during measurement. Estimates were weighted to account for the sampling frame. For average counts/minute/day, four classes emerged from least to most active: 40.9% of population (mean 323.5 counts/minute/day), 40.3% (559.6 counts/minute/day), 16.5% (810.0 counts/minute/day), and 2.3% (1132.9 counts/minute/day). For percent of sedentary behavior, four classes emerged: 13.5% of population (mean 544.6 min/day), 30.1% (455.1 min/day), 38.5% (357.7 min/day), and 18.0% (259.2 min/day). For percent of light activity, four classes emerged: 12.3% of population (mean 222.6 min/day), 29.3% (301.7 min/day), 41.8% (384.0 min/day), and 16.6% (455.5 min/day). For percent of MVPA, four classes emerged: 59.9% of population (mean 25.0 min/day), 33.3% (60.9 min/day), 3.1% (89.0 min/day), and 3.6% (109.3 min/day). For percent of vigorous activity, three classes emerged: 76.8% of population (mean 7.1 min/day), 18.5% (23.9 min/day), and 4.7% (47.4 min/day). Classes were developed by age
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Directory of Open Access Journals (Sweden)
Boeschoten Laura
2017-12-01
Full Text Available Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible combinations with scores on other variables. Furthermore, the latent class model, by multiply imputing a new variable, enhances the quality of statistics based on the composite data set. The performance of this method is investigated by a simulation study, which shows that whether or not the method can be applied depends on the entropy R2 of the latent class model and the type of analysis a researcher is planning to do. Finally, the method is applied to public data from Statistics Netherlands.
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Rapid Exploitation and Analysis of Documents
Energy Technology Data Exchange (ETDEWEB)
Buttler, D J; Andrzejewski, D; Stevens, K D; Anastasiu, D; Gao, B
2011-11-28
Analysts are overwhelmed with information. They have large archives of historical data, both structured and unstructured, and continuous streams of relevant messages and documents that they need to match to current tasks, digest, and incorporate into their analysis. The purpose of the READ project is to develop technologies to make it easier to catalog, classify, and locate relevant information. We approached this task from multiple angles. First, we tackle the issue of processing large quantities of information in reasonable time. Second, we provide mechanisms that allow users to customize their queries based on latent topics exposed from corpus statistics. Third, we assist users in organizing query results, adding localized expert structure over results. Forth, we use word sense disambiguation techniques to increase the precision of matching user generated keyword lists with terms and concepts in the corpus. Fifth, we enhance co-occurrence statistics with latent topic attribution, to aid entity relationship discovery. Finally we quantitatively analyze the quality of three popular latent modeling techniques to examine under which circumstances each is useful.
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Latent class models for classification
Vermunt, J.K.; Magidson, J.
2003-01-01
An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised
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On Latent Growth Models for Composites and Their Constituents.
Hancock, Gregory R; Mao, Xiulin; Kher, Hemant
2013-09-01
Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.
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Sanislow, Charles A; Little, Todd D; Ansell, Emily B; Grilo, Carlos M; Daversa, Maria; Markowitz, John C; Pinto, Anthony; Shea, M Tracie; Yen, Shirley; Skodol, Andrew E; Morey, Leslie C; Gunderson, John G; Zanarini, Mary C; McGlashan, Thomas H
2009-08-01
Evaluation of the validity of personality disorder (PD) diagnostic constructs is important for the impending revision of the Diagnostic and Statistical Manual of Mental Disorders. Prior factor analytic studies have tested these constructs in cross-sectional studies, and models have been replicated longitudinally, but no study has tested a constrained longitudinal model. The authors examined 4 PDs in the Collaborative Longitudinal Personality Disorders study (schizotypal, borderline, avoidant, and obsessive-compulsive) over 7 time points (baseline, 6 months, 1 year, 2 years, 4 years, 6 years, and 10 years). Data for 2-, 4-, 6- and 10-year assessments were obtained in semistructured interviews by raters blind to prior PD diagnoses at each assessment. The latent structure of the 4 constructs was differentiated during the initial time points but became less differentiated over time as the mean levels of the constructs dropped and stability increased. Obsessive-compulsive PD became more correlated with schizotypal and borderline PD than with avoidant PD. The higher correlation among the constructs in later years may reflect greater shared base of pathology for chronic personality disorders.
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Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.
2013-01-01
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…
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Rapid detection of drug metabolites in latent fingermarks.
Hazarika, Pompi; Jickells, Sue M; Russell, David A
2009-01-01
Magnetic particles functionalised with anti-cotinine antibody have been used to image latent fingermarks through the detection of the cotinine antigen in the sweat deposited within the fingerprints of smokers. The antibody-magnetic particle conjugates are readily applied to latent fingerprints while excess reagents are removed through the use of a magnetic wand. The results have shown that drug metabolites, such as cotinine, can be detected and used to image the fingermark to establish the identity of an individual within 15 minutes.
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Choi, Kilchan
2011-01-01
This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…
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Effects of latent toxoplasmosis on autoimmune thyroid diseases in pregnancy.
Kaňková, Šárka; Procházková, Lucie; Flegr, Jaroslav; Calda, Pavel; Springer, Drahomíra; Potluková, Eliška
2014-01-01
Toxoplasmosis, one of the most common zoonotic diseases worldwide, can induce various hormonal and behavioural alterations in infected hosts, and its most common form, latent toxoplasmosis, influences the course of pregnancy. Autoimmune thyroid diseases (AITD) belong to the well-defined risk factors for adverse pregnancy outcomes. The aim of this study was to investigate whether there is a link between latent toxoplasmosis and maternal AITD in pregnancy. Cross-sectional study in 1248 consecutive pregnant women in the 9-12th gestational weeks. Serum thyroid-stimulating hormone (TSH), thyroperoxidase antibodies (TPOAb), and free thyroxine (FT4) were assessed by chemiluminescence; the Toxoplasma status was detected by the complement fixation test (CFT) and anti-Toxoplasma IgG enzyme-linked immunosorbent assay (ELISA). Overall, 22.5% of the women were positive for latent toxoplasmosis and 14.7% were screened positive for AITD. Women with latent toxoplasmosis had more often highly elevated TPOAb than the Toxoplasma-negative ones (p = 0.004), and latent toxoplasmosis was associated with decrease in serum TSH levels (p = 0.049). Moreover, we found a positive correlation between FT4 and the index of positivity for anti-Toxoplasma IgG antibodies (p = 0.033), which was even stronger in the TPOAb-positive Toxoplasma-positive women, (p = 0.014), as well as a positive correlation between FT4 and log2 CFT (p = 0.009). Latent toxoplasmosis was associated with a mild increase in thyroid hormone production in pregnancy. The observed Toxoplasma-associated changes in the parameters of AITD are mild and do not seem to be clinically relevant; however, they could provide new clues to the complex pathogenesis of autoimmune thyroid diseases.
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MOTOR STRUCTURE AND BASIC MOVEMENT COMPETENCES IN EARLY CHILD DEVELOPMENT
Directory of Open Access Journals (Sweden)
Rado Pišot
2010-12-01
Full Text Available Motor development consists of dynamic and continuous development in motor behaviour and is reflected in motor competences (on the locomotive, manipulative and postural level and motor abilities (coordination, strength, speed, balance, flexibility, precision and endurance. This is a complex process in which a child acquires motor abilities and knowledge in interaction with inherited and environmental factors. A sample of 603 boys and girls, of which 263 were aged five (age deviation +/- 3 days; 18,5 ± 3,1kg body weight; 109,4 ± 4,3 cm body height and 340 were aged six and a half (age deviation +/- 3 days; 23, 7 ± 4, 3 kg body weight; 121 ± 4,8 cm body height, were involved in this study after written consent was obtained from their parents. The children's motor structure was established through the application of 28 tests that had been verified on the Slovene population and established as adequate for the study of motor abilities in the sample children. The factor analysis was applied to uncover the latent structure of motor space, and PB (Štalec Momirović criteria were used to establish the number of significant basic components. The analysis of the motor space structure revealed certain particularities for each age period. In the sample of 5 year old children, the use of PB criterion revealed four latent motor dimensions, in 6.5 year old children, the latent motor space structure was described with four (boys and five (girls factors. Despite the existence of gender differences in motor space structure and certain particularities in each age period mostly related to the factors which influence movement coordination, several very similar dimensions were discovered in both sexes.
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Performance of a new solar air heater with packed-bed latent storage energy for nocturnal use
International Nuclear Information System (INIS)
Bouadila, Salwa; Kooli, Sami; Lazaar, Mariem; Skouri, Safa; Farhat, Abdelhamid
2013-01-01
Highlights: • A new solar air heater collector using a phase change material. • Experimental study of the new solar air heater collector with latent storage. • Energy and exergy analysis of the solar heater with latent storage collector. • Nocturnal use of solar air heater collector. - Abstract: An experimental study was conducted to evaluate the thermal performance of a new solar air heater collector using a packed bed of spherical capsules with a latent heat storage system. Using both first and second law of thermodynamics, the energetic and exegetic daily efficiencies were calculated in Closed/Opened and Opened cycle mode. The solar energy was stored in the packed bed through the diurnal period and extracted at night. The experimentally obtained results are used to analyze the performance of the system, based on temperature distribution in different localization of the collectors. The daily energy efficiency varied between 32% and 45%. While the daily exergy efficiency varied between 13% and 25%
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Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa
2011-01-01
The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…