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Sample records for latent structure analysis

  1. Analysis of latent structures in linear systems

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2004-01-01

    that are useful, when studying latent structures. It is shown how loading weight vectors are generated and how they can be interpreted in analyzing the latent structure. It is shown how the covariance can be used to get useful ‘apriori’ information on the modeling task. Also some simple methods are presented...... to use for deciding if single or multiple latent structures should be used. The last part is about choosing the variables that should be used in the analysis. The traditional procedures to select variables to include in the model are presented and the insufficiencies of such approaches are demonstrated...

  2. Generalized Structured Component Analysis with Latent Interactions

    Science.gov (United States)

    Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

    2010-01-01

    Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

  3. Analysis of latent structures in linear systems

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2004-01-01

    In chemometrics the emphasis is on latent structure models. The latent structure is the part of the data that the modeling task is based upon. This paper is addressing some fundamental issues, when latent structures are used. The paper consists of three parts. The first part is concerned defining...

  4. Clarifying Boundaries of Binge Eating Disorder and Psychiatric Comorbidity: A Latent Structure Analysis

    OpenAIRE

    Hilbert, Anja; Denise E. Wilfley; Dohm, Faith-Anne; Pike, Kathleen M; Fairburn, Christopher G.; Striegel-Moore, Ruth H.

    2010-01-01

    Binge eating disorder (BED) presents with substantial psychiatric comorbidity. This latent structure analysis sought to delineate boundaries of BED given its comorbidity with affective and anxiety disorders. A population-based sample of 151 women with BED, 102 women with affective or anxiety disorders, and 259 women without psychiatric disorders was assessed with clinical interviews and self-report questionnaires. Taxometric analyses were conducted using DSM-IV criteria of BED and of affectiv...

  5. Ecological time-series analysis through structural modelling with latent constructs: concepts, methods and applications.

    Science.gov (United States)

    Almaraz, Pablo

    2005-04-01

    Time-series analyses in ecology usually involve the use of autoregressive modelling through direct and/or delayed difference equations, which severely restricts the ability of the modeler to structure complex causal relationships within a multivariate frame. This is especially problematic in the field of population regulation, where the proximate and ultimate causes of fluctuations in population size have been hotly debated for decades. Here it is shown that this debate can benefit from the implementation of structural modelling with latent constructs (SEM) to time-series analysis in ecology. A nonparametric bootstrap scheme illustrates how this modelling approach can circumvent some problems posed by the climate-ecology interface. Stochastic Monte Carlo simulation is further used to assess the effects of increasing time-series length and different parameter estimation methods on the performance of several model fit indexes. Throughout, the advantages and limitations of the SEM method are highlighted.

  6. Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis.

    Science.gov (United States)

    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.

  7. Latent semantic analysis.

    Science.gov (United States)

    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.

  8. Latent Structure Analysis of Longitudinal Data on Relations Between Intellectual Abilities and School Achievement.

    Science.gov (United States)

    Kuusinen, J; Leskinen, E

    1988-01-01

    Covariance structure modelling by LISREL was applied to analyze the relations between intellectual ability, as measured by ITPA, and achievement in reading, writing, foreign language and mathematics in longitudinal data with 8 to 10 years' time interval between measurements. The subjects' (N = 234) ability scores were obtained at 5-7 years of age, and their achievement was measured at 14-16 years of age. The effect of ability to achievement was studied by analyzing structural equation models on both first-order ability and achievement factors and by developing a two-stage second-order factor estimation method for structural equation parameters between first-order ability and achievement factors. Squared multiple correlations and coefficients of determination as indices of explained variance were derived for reduced forms of structural equations. The general latent intellectual ability explained 49% of variance in school achievement. The results showed the high validity of ITPA in explaining school success as well as the great flexibility and usefulness of covariance structure modelling by LISREL in analyzing longitudinal data.

  9. Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysis

    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...

  10. Latent variable models an introduction to factor, path, and structural equation analysis

    CERN Document Server

    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

  11. Study on TCM Syndrome Differentiation of Primary Liver Cancer Based on the Analysis of Latent Structural Model

    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.

  12. Evaluating the Latent Structure of the MMPI-2 F(p) Scale in a Forensic Sample: A Taxometric Analysis

    Science.gov (United States)

    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…

  13. PROC LCA: A SAS Procedure for Latent Class Analysis

    Science.gov (United States)

    Lanza, Stephanie T.; Collins, Linda M.; Lemmon, David R.; Schafer, Joseph L.

    2007-01-01

    Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across…

  14. PROC LCA: A SAS Procedure for Latent Class Analysis

    Science.gov (United States)

    Lanza, Stephanie T.; Collins, Linda M.; Lemmon, David R.; Schafer, Joseph L.

    2007-01-01

    Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across…

  15. Sensitivity analysis for linear structural equation models, longitudinal mediation with latent growth models and blended learning in biostatistics education

    Science.gov (United States)

    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

  16. Orthogonal projection to latent structures combined with artificial neural networks in non-destructive analysis of Ampicillin powder.

    Science.gov (United States)

    Wang, Bin; Liu, Guoliang; Fei, Qiang; Zuo, Ye; Ren, YuLin

    2009-01-01

    A new method orthogonal projection to latent structures (O-PLS) combined with artificial neural networks is investigated for non-destructive determination of Ampicillin powder via near-infrared (NIR) spectroscopy. The modern NIR spectroscopy analysis technique is efficient, simple and non-destructive, which has been used in chemical analysis in diverse fields. Be a preprocessing method, O-PLS provides a way to remove systematic variation from an input data set X not correlated to the response set Y, and does not disturb the correlation between X and Y. In this paper, O-PLS pretreated spectral data was applied to establish the ANN model of Ampicillin powder, in this model, the concentration of Ampicillin as the active component was determined. The degree of approximation was employed as the selective criterion of the optimum network parameters. In order to compare the OPLS-ANN model, the calibration models that using first-derivative and second-derivative preprocessing spectra were also designed. Experimental results showed that the OPLS-ANN model was the best.

  17. Orthogonal projection to latent structures combined with artificial neural networks in non-destructive analysis of ebastine powder.

    Science.gov (United States)

    Ibrahim, Fawzia Ahmed; Wahba, Mary Elias Kamel

    2014-01-01

    A new method orthogonal projection to latent structures (O-PLS) combined with artificial neural networks is investigated for non-destructive determination of ebastine powder via near-infrared (NIR) spectroscopy. The modern NIR spectroscopy is efficient, simple and non-destructive technique, which has been used in chemical analysis in diverse fields. Being a preprocessing method, O-PLS provides a way to remove systematic variation from an input data set X not correlated to the response set Y, and does not disturb the correlation between X and Y. In this paper, O-PLS pretreated spectral data was applied to establish the ANN model of ebastine powder, in this model, the concentration of ebastine as the active component was determined. The degree of approximation was employed as the selective criterion of the optimum network parameters. In order to compare the OPLS-ANN model, the calibration models that use first-derivative and second-derivative preprocessing spectra were also designed. Experimental results showed that the OPLS-ANN model was the best.

  18. Evaluation of three 3ABC ELISAs for foot-and-mouth disease non-structural antibodies using latent class analysis

    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

  19. Introduction to Latent Class Analysis with Applications

    Science.gov (United States)

    Porcu, Mariano; Giambona, Francesca

    2017-01-01

    Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence…

  20. Introduction to Latent Class Analysis with Applications

    Science.gov (United States)

    Porcu, Mariano; Giambona, Francesca

    2017-01-01

    Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence…

  1. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    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...... 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...... prediction performance of the learning based approaches and other widely used link prediction approaches in 14 networks ranging from medium size to large networks with more than a million nodes. While link prediction is typically well above chance for all networks, we find that the learning based mixed...

  2. Nonparametric spectral-based estimation of latent structures

    OpenAIRE

    Bonhomme, Stéphane; Jochmans, Koen; Robin, Jean-Marc

    2014-01-01

    We present a constructive identification proof of p-linear decompositions of q-way arrays. The analysis is based on the joint spectral decomposition of a set of matrices. It has applications in the analysis of a variety of latent-structure models, such as q-variate mixtures of p distributions. As such, our results provide a constructive alternative to Allman, Matias and Rhodes [2009]. The identification argument suggests a joint approximate-diagonalization estimator that is easy to implement ...

  3. Latent Class and Latent Transition Analysis With Applications in the Social, Behavioral, and Health Sciences

    CERN Document Server

    Collins, Linda M

    2010-01-01

    One of the few books on latent class analysis (LCA) and latent transition analysis (LTA) with a comprehensive treatment of longitudinal latent class models, Latent Class and Latent Transition Analysis reflects improvements in statistical computing as the most up-to-date reference for theoretical, technical, and practical issues in cross-sectional and longitudinal data. Plentiful examples enable the reader to acquire a thorough conceptual and technical understanding and to apply techniques to address empirical research questions. Researchers seeking an advanced introduction to LCA and LTA and g

  4. Latent common manifold learning with alternating diffusion: analysis and applications

    CERN Document Server

    Talmon, Ronen

    2016-01-01

    The analysis of data sets arising from multiple sensors has drawn significant research attention over the years. Traditional methods, including kernel-based methods, are typically incapable of capturing nonlinear geometric structures. We introduce a latent common manifold model underlying multiple sensor observations for the purpose of multimodal data fusion. A method based on alternating diffusion is presented and analyzed; we provide theoretical analysis of the method under the latent common manifold model. To exemplify the power of the proposed framework, experimental results in several applications are reported.

  5. Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

    Science.gov (United States)

    Yang, Bo; Fu, Xiao; Sidiropoulos, Nicholas D.

    2017-01-01

    Dimensionality reduction techniques play an essential role in data analytics, signal processing and machine learning. Dimensionality reduction is usually performed in a preprocessing stage that is separate from subsequent data analysis, such as clustering or classification. Finding reduced-dimension representations that are well-suited for the intended task is more appealing. This paper proposes a joint factor analysis and latent clustering framework, which aims at learning cluster-aware low-dimensional representations of matrix and tensor data. The proposed approach leverages matrix and tensor factorization models that produce essentially unique latent representations of the data to unravel latent cluster structure -- which is otherwise obscured because of the freedom to apply an oblique transformation in latent space. At the same time, latent cluster structure is used as prior information to enhance the performance of factorization. Specific contributions include several custom-built problem formulations, corresponding algorithms, and discussion of associated convergence properties. Besides extensive simulations, real-world datasets such as Reuters document data and MNIST image data are also employed to showcase the effectiveness of the proposed approaches.

  6. Bayesian latent structure modeling of walking behavior in a physical activity intervention

    Science.gov (United States)

    Lawson, Andrew B; Ellerbe, Caitlyn; Carroll, Rachel; Alia, Kassandra; Coulon, Sandra; Wilson, Dawn K; VanHorn, M Lee; St George, Sara M

    2017-01-01

    The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are addressed via posterior sampling and a simulated evaluation of the longitudinal model’s ability to recover latent structure and predictor effects is considered. We evaluate the effect of a variety of socio-psychological and spatial neighborhood predictors on the propensity to walk and the estimation of latent ability and willingness in the full study. PMID:24741000

  7. Latent factor structure of a behavioral economic marijuana demand curve.

    Science.gov (United States)

    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.

  8. Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables

    Science.gov (United States)

    Lee, Sik-Yum; Song, Xin-Yuan; Tang, Nian-Sheng

    2007-01-01

    The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. This approach produces a Bayesian estimate that has the same statistical optimal properties as a…

  9. Latent Class Analysis of YBOCS Symptoms in Obsessive Compulsive Disorder

    Science.gov (United States)

    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.

    2010-01-01

    Objective 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. Method Latent class analysis (LCA) models using 61 obsessive-compulsive symptoms (OCS) collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, gender, symptom severity and comorbid tic disorders were tested for relationship to class membership. Results LCA models of best fit yielded three classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher YBOCS symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes. Conclusions 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. PMID:21145539

  10. 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...

  11. Gaussian Process Structural Equation Models with Latent Variables

    CERN Document Server

    Silva, Ricardo

    2010-01-01

    In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure. This corresponds to a family of graphical models known as the structural equation model with latent variables. While linear non-Gaussian variants have been well-studied, inference in nonparametric structural equation models is still underdeveloped. We introduce a sparse Gaussian process parameterization that defines a non-linear structure connecting latent variables, unlike common formulations of Gaussian process latent variable models. An efficient Markov chain Monte Carlo procedure is described. We evaluate the stability of the sampling procedure and the predictive ability of the model compared against the current practice.

  12. Attachment insecurities, maladaptive perfectionism, and eating disorder symptoms: a latent mediated and moderated structural equation modeling analysis across diagnostic groups.

    Science.gov (United States)

    Dakanalis, Antonios; Timko, C Alix; Zanetti, M Assunta; Rinaldi, Lucio; Prunas, Antonio; Carrà, Giuseppe; Riva, Giuseppe; Clerici, Massimo

    2014-01-30

    Although 96-100% of individuals with eating disorders (EDs) report insecure attachment, the specific mechanisms by which adult insecure attachment dimensions affect ED symptomatology remain to date largely unknown. This study examined maladaptive perfectionism as both a mediator and a moderator of the relationship between insecure attachment (anxiety and avoidance) and ED symptomatology in a clinical, treatment seeking, sample. Insecure anxious and avoidant attachment, maladaptive perfectionism, and ED symptomatology were assessed in 403 participants from three medium size specialized care centres for EDs in Italy. Structural equation modeling indicated that maladaptive perfectionism served as mediator between both insecure attachment patterns and ED symptomatology. It also interacted with insecure attachment to predict higher levels of ED symptoms - highlighting the importance of both insecure attachment patterns and maladaptive aspects of perfectionism as treatment targets. Multiple-group comparison analysis did not reveal differences across diagnostic groups (AN, BN, EDNOS) in mediating, main and interaction effects of perfectionism. These findings are consistent with recent discussions on the classification and treatment of EDs that have highlighted similarities between ED diagnostic groups and could be viewed through the lens of the Trans-theoretical Model of EDs. Implications for future research and intervention are discussed.

  13. An Application of Latent Variable Structural Equation Modeling For Experimental Research in Educational Technology

    National Research Council Canada - National Science Library

    Hyeon Woo LEE

    2011-01-01

      AN APPLICATION OF LATENT VARIABL AN APPLICATION OF LATENT VARIABLE STRUCTURAL EQUATION MODELING FOR EXPERIMENTAL RESEARCH IN EDUCATIONAL TECHNOLOGY As the technology-enriched learning environments...

  14. Experimental analysis of the performance of optimized fin structures in a latent heat energy storage test rig

    Science.gov (United States)

    Johnson, Maike; Hübner, Stefan; Reichmann, Carsten; Schönberger, Manfred; Fiß, Michael

    2017-06-01

    Energy storage systems are a key technology for developing a more sustainable energy supply system and lowering overall CO2 emissions. Among the variety of storage technologies, high temperature phase change material (PCM) storage is a promising option with a wide range of applications. PCM storages using an extended finned tube storage concept have been designed and techno-economically optimized for solar thermal power plant operations. These finned tube components were experimentally tested in order to validate the optimized design and simulation models used. Analysis of the charging and discharging characteristics of the storage at the pilot scale gives insight into the heat distribution both axially as well as radially in the storage material, thereby allowing for a realistic validation of the design. The design was optimized for discharging of the storage, as this is the more critical operation mode in power plant applications. The data show good agreement between the model and the experiments for discharging.

  15. Amatchmethod Based on Latent Semantic Analysis for Earthquakehazard Emergency Plan

    Science.gov (United States)

    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.

  16. Chromatin Structure of Epstein-Barr Virus Latent Episomes.

    Science.gov (United States)

    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.

  17. A Taxometric Exploration of the Latent Structure of Hoarding

    Science.gov (United States)

    Timpano, Kiara R.; Broman-Fulks, Joshua J.; Glaesmer, Heide; Exner, Cornelia; Rief, Winfried; Olatunji, Bunmi O.; Keough, Meghan E.; Riccardi, Christina J.; Brahler, Elmar; Wilhelm, Sabine; Schmidt, Norman B.

    2013-01-01

    Despite controversy regarding the classification and diagnostic status of hoarding disorder, there remains a paucity of research on the nosology of hoarding that is likely to inform the classification debate. The present investigation examined the latent structure of hoarding in three, large independent samples. Data for three well-validated…

  18. A Taxometric Exploration of the Latent Structure of Hoarding

    Science.gov (United States)

    Timpano, Kiara R.; Broman-Fulks, Joshua J.; Glaesmer, Heide; Exner, Cornelia; Rief, Winfried; Olatunji, Bunmi O.; Keough, Meghan E.; Riccardi, Christina J.; Brahler, Elmar; Wilhelm, Sabine; Schmidt, Norman B.

    2013-01-01

    Despite controversy regarding the classification and diagnostic status of hoarding disorder, there remains a paucity of research on the nosology of hoarding that is likely to inform the classification debate. The present investigation examined the latent structure of hoarding in three, large independent samples. Data for three well-validated…

  19. The Latent Structure of Psychopathy in Youth: A Taxometric Investigation

    Science.gov (United States)

    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…

  20. Structuring latent consumer needs using LISREL

    DEFF Research Database (Denmark)

    Juhl, Hans Jørn; Kristensen, Kai; Bech, Anne C.

    1995-01-01

    A LISREL (Linear Structural Relationships) model is formulated according to the hierarchical division of customer needs presented in the literature on Quality Function Deployment (QFD). The purpose is to evaluate the relative importance of first-h impression and taste experience as regards food...

  1. Structuring latent consumer needs using LISREL

    DEFF Research Database (Denmark)

    Juhl, Hans Jørn; Poulsen, Carsten Stig; Kristensen, Kai

    1995-01-01

    Executive summary A LISREL (Linear Structural Relationships) model is formulated according to the hierarchical division of customer needs presented in the literature on Quality Function Deployment (QFD). The purpose is to evaluate the relative importance of first-hand impression and taste...

  2. The latent structure of secure base script knowledge.

    Science.gov (United States)

    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

    2015-06-01

    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 that such basic information about the factor structure and distributional properties of these individual differences has important conceptual implications for our understanding of how representations of early experience are organized and generalized, as well as methodological significance in relation to maximizing statistical power and precision. In this study, we report factor and taxometric analyses that examined the latent structure of secure base script knowledge in 2 large samples. Results suggested that variation in secure base script knowledge-as measured by both the adolescent (N = 674) and adult (N = 714) versions of the Attachment Script Assessment-is generalized across relationships and continuously distributed.

  3. A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe; Hagos, Samson

    2016-09-01

    Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfall amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.

  4. Latent structures of female sexual functioning.

    Science.gov (United States)

    Carvalho, Joana; Vieira, Armando Luís; Nobre, Pedro

    2012-08-01

    For the last three decades, male and female sexual responses have been conceptualized as similar, based on separated and sequential phases as proposed by the models of Masters and Johnson (1966) and Kaplan (1979) model. However, there is a growing debate around the need to conceptualize female sexual response and the classification of sexual dysfunction in women, in view of the upcoming editions of the DSM and ICD. The aim of this study was to test, using structural equation modeling, five conceptual, alternative models of female sexual function, using a sample of women with sexual difficulties and a sample of women without sexual problems. A total of 1993 Portuguese women participated in the study and completed a modified version of the Female Sexual Function Index. Findings suggested a four-factor solution as the model that best fit the data regarding women presenting sexual difficulties: (1) desire/arousal; (2) lubrication; (3) orgasm; (4) pain/vaginismus. In relation to sexually healthy women, the best model was a five-factor solution comprising of (1) desire; (2) arousal; (3) lubrication; (4) orgasm; and (5) pain/vaginismus. Discriminant validity between factors was supported, suggesting that these dimensions measure distinct phenomena. Model fit to the data significantly decreased in both samples, as models began to successively consider greater levels of overlap among phases of sexual function, towards a single-factor solution. By suggesting the overlap between pain and vaginismus, results partially support the new classification that is currently being discussed regarding DSM-5. Additionally, results on the relationship between sexual desire and arousal were inconclusive as sexually healthy women were better characterized by a five-factor model that considered the structural independence among these factors, whereas women with sexual difficulties better fit with a four-factor model merging sexual desire and subjective sexual arousal.

  5. The latent structure of generalized anxiety disorder in midlife adults.

    Science.gov (United States)

    Marcus, David K; Sawaqdeh, Abere; Kwon, Paul

    2014-02-28

    Generalized anxiety disorder (GAD) is identified as a discrete disorder in the DSM-5, but evidence suggests that GAD and the related construct of pathological worry possesses a dimensional latent structure. The objective of this study was to ascertain the latent structure of GAD using taxometric methods. A subsample of adults (N=2061) from the Midlife in the United States Study, a national sample of Americans, provided the data. Additional data from individuals who were re-interviewed 10 year later (n=1228) were also analyzed. Items corresponding to the DSM-IV-TR diagnostic criteria for GAD were used to generate indicators for the taxometric analyses. Multiple taxometric procedures provided no evidence that GAD has a categorical or taxonic latent structure. Instead, the results were more consistent with the proposition that GAD exists on a continuum. Evidence that GAD is dimensional suggests that dichotomizing individuals into GAD versus non-GAD groups will typically result in decreased statistical power. They also suggest that any diagnostic thresholds for identifying GAD are likely to be arbitrary. The findings are consistent with models that locate GAD within the framework of extant dimensional models of personality and with research that emphasizes a multifactorial etiology for GAD. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. 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.

  7. Improving knowledge management systems with latent semantic analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sebok, A.; Plott, C. [Alion Science and Technology, MA and D Operation, 4949 Pearl East Circle, Boulder, CO 80301 (United States); LaVoie, N. [Pearson Knowledge Technologies, 4940 Pearl East Circle, Boulder, CO 80301 (United States)

    2006-07-01

    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)

  8. Discovering shared and individual latent structure in multiple time series

    CERN Document Server

    Saria, Suchi; Penn, Anna

    2010-01-01

    This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared features in a set of time series that exhibit significant individual variability. Our method builds on the framework of latent Diricihlet allocation (LDA) and its extension to hierarchical Dirichlet processes, which allows us to characterize each series as switching between latent ``topics'', where each topic is characterized as a distribution over ``words'' that specify the series dynamics. However, unlike standard applications of LDA, we discover the words as we learn the model. We apply this model to the task of tracking the physiological signals of premature infants; our model obtains clinically significant insights as well as useful features for supervised learning tasks.

  9. 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...... Probabilistic Latent Semantic Analysis (PLSA) approach and a global multiway PLSA method. The analysis indicates that the global analysis method is able to identify relevant trends which are difficult to get using a step-by-step approach. Furthermore we show that inspection of PLSA models with different number...

  10. Analyzing Latent State-Trait and Multiple-Indicator Latent Growth Curve Models as Multilevel Structural Equation Models

    Directory of Open Access Journals (Sweden)

    Christian eGeiser

    2013-12-01

    Full Text Available Latent state-trait (LST and latent growth curve (LGC models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM or multilevel (ML; hierarchical linear modeling frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1 a large number of time points, (2 individually-varying times of observation, (3 unequally spaced time intervals, and/or (4 incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person using the software Mplus (Muthén & Muthén, 1998-2012 and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models.

  11. A Magnetically Responsive Polydiacetylene Precursor for Latent Fingerprint Analysis.

    Science.gov (United States)

    Lee, Joosub; Lee, Chan Woo; Kim, Jong-Man

    2016-03-01

    A magnetically responsive diacetylene (DA) powder was developed for the visualization of latent fingerprints. A mixture of the DA and magnetite nanoparticles, applied to a surface containing latent fingermarks, becomes immobilized along the ridge patterns of the fingerprints when a magnetic field is applied. Alignment along the ridge structures is a consequence of favorable hydrophobic interactions occurring between the long alkyl chains in the DAs and the lipid-rich, sebaceous latent fingermarks. UV irradiation of the DA-magnetite composite immobilized on the latent fingerprint results in the generation of blue-colored PDAs. Heat treatment of the blue-colored image promotes a blue-to-red transition as well as fluorescence turn-on. A combination of the aligned pale brown-colored monomeric state, UV irradiation generated blue-colored PDA state, as well as the heat treatment generated red-colored and fluorescent PDA state enables efficient visual imaging of a latent fingerprint, which is deposited on various colored solid surfaces.

  12. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

    Directory of Open Access Journals (Sweden)

    Jeban Ganesalingam

    Full Text Available BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

  13. Multilevel Latent Class Analysis: Parametric and Nonparametric Models

    Science.gov (United States)

    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…

  14. Developing Coping Typologies of Minority Adolescents: A Latent Profile Analysis

    Science.gov (United States)

    Aldridge, Arianna A.; Roesch, Scott C.

    2008-01-01

    Latent profile analysis (LPA) was used to develop a coping typology of minority adolescents (M = 15.5 years). A multiethnic sample (n = 354) was recruited from a program aimed at serving low-income students. LPA revealed three distinct coping profiles. The first comprised adolescents who used a number of specific coping strategies at a low level…

  15. Exploring Different Types of Academic Delayers: A Latent Profile Analysis

    Science.gov (United States)

    Grunschel, Carola; Patrzek, Justine; Fries, Stefan

    2013-01-01

    In this study, we explored whether there are different types of academic delayers (i.e., types of students who delay academic tasks). Latent profile analysis based on 554 university students' reasons for academic delay revealed four distinct types: inconspicuous, successful pressure-seeking, worried/anxious, and discontent with studies. The types…

  16. 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 ...

  17. Changes in latent fingerprint examiners' markup between analysis and comparison.

    Science.gov (United States)

    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%).

  18. Generalized latent variable modeling multilevel, longitudinal, and structural equation models

    CERN Document Server

    Skrondal, Anders

    2004-01-01

    METHODOLOGY THE OMNI-PRESENCE OF LATENT VARIABLES Introduction 'True' variable measured with error Hypothetical constructs Unobserved heterogeneity Missing values and counterfactuals Latent responses Generating flexible distributions Combining information Summary MODELING DIFFERENT RESPONSE PROCESSES Introduction Generalized linear models Extensions of generalized linear models Latent response formulation Modeling durations or survival Summary and further reading CLASSICAL LATENT VARIABLE MODELS Introduction Multilevel regression models Factor models and item respons

  19. Latent variables and structural equation models for longitudinal relationships: an illustration in nutritional epidemiology

    Directory of Open Access Journals (Sweden)

    Basdevant Arnaud

    2010-04-01

    Full Text Available Abstract Background The use of structural equation modeling and latent variables remains uncommon in epidemiology despite its potential usefulness. The latter was illustrated by studying cross-sectional and longitudinal relationships between eating behavior and adiposity, using four different indicators of fat mass. Methods Using data from a longitudinal community-based study, we fitted structural equation models including two latent variables (respectively baseline adiposity and adiposity change after 2 years of follow-up, each being defined, by the four following anthropometric measurement (respectively by their changes: body mass index, waist circumference, skinfold thickness and percent body fat. Latent adiposity variables were hypothesized to depend on a cognitive restraint score, calculated from answers to an eating-behavior questionnaire (TFEQ-18, either cross-sectionally or longitudinally. Results We found that high baseline adiposity was associated with a 2-year increase of the cognitive restraint score and no convincing relationship between baseline cognitive restraint and 2-year adiposity change could be established. Conclusions The latent variable modeling approach enabled presentation of synthetic results rather than separate regression models and detailed analysis of the causal effects of interest. In the general population, restrained eating appears to be an adaptive response of subjects prone to gaining weight more than as a risk factor for fat-mass increase.

  20. Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints.

    Science.gov (United States)

    Helwig, Nathaniel E

    2017-07-01

    Longitudinal data are inherently multimode in the sense that such data are often collected across multiple modes of variation, for example, time × variables × subjects. In many longitudinal studies, multiple variables are collected to measure some latent construct(s) of interest. In such cases, the goal is to understand temporal trends in the latent variables, as well as individual differences in the trends. Multimode component analysis models provide a powerful framework for discovering latent trends in longitudinal data. However, classic implementations of multimode models do not take into consideration functional information (i.e., the temporal sequence of the collected data) or structural information (i.e., which variables load onto which latent factors) about the study design. In this paper, we reveal how functional and structural constraints can be imposed in multimode models (Parafac and Parafac2) in order to elucidate trends in longitudinal data. As a motivating example, we consider a longitudinal study on per capita alcohol consumption trends conducted from 1970 to 2013 by the U.S. National Institute on Alcohol Abuse and Alcoholism. We demonstrate how functional and structural information about the study design can be incorporated into the Parafac and Parafac2 alternating least squares algorithms to understand temporal and regional trends in three latent constructs: beer consumption, spirits consumption, and wine consumption. Our results reveal that Americans consume more than the recommended amount of alcohol, and total alcohol consumption trends show no signs of decreasing in the last decade. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Segmentation and Enhancement of Latent Fingerprints: A Coarse to Fine Ridge Structure Dictionary.

    Science.gov (United States)

    Cao, Kai; Liu, Eryun; Jain, Anil K

    2014-09-01

    Latent fingerprint matching has played a critical role in identifying suspects and criminals. However, compared to rolled and plain fingerprint matching, latent identification accuracy is significantly lower due to complex background noise, poor ridge quality and overlapping structured noise in latent images. Accordingly, manual markup of various features (e.g., region of interest, singular points and minutiae) is typically necessary to extract reliable features from latents. To reduce this markup cost and to improve the consistency in feature markup, fully automatic and highly accurate ("lights-out" capability) latent matching algorithms are needed. In this paper, a dictionary-based approach is proposed for automatic latent segmentation and enhancement towards the goal of achieving "lights-out" latent identification systems. Given a latent fingerprint image, a total variation (TV) decomposition model with L1 fidelity regularization is used to remove piecewise-smooth background noise. The texture component image obtained from the decomposition of latent image is divided into overlapping patches. Ridge structure dictionary, which is learnt from a set of high quality ridge patches, is then used to restore ridge structure in these latent patches. The ridge quality of a patch, which is used for latent segmentation, is defined as the structural similarity between the patch and its reconstruction. Orientation and frequency fields, which are used for latent enhancement, are then extracted from the reconstructed patch. To balance robustness and accuracy, a coarse to fine strategy is proposed. Experimental results on two latent fingerprint databases (i.e., NIST SD27 and WVU DB) show that the proposed algorithm outperforms the state-of-the-art segmentation and enhancement algorithms and boosts the performance of a state-of-the-art commercial latent matcher.

  2. KOPLS-DA在掺杂牛奶判别中的应用%Application of Kernel Orthogonal Projection to Latent Structure Discriminant Analysis in the Discrimination of Adulterated Milk

    Institute of Scientific and Technical Information of China (English)

    刘蓉; 杨仁杰; 苗静; 徐可欣

    2013-01-01

    Based on the method of kernet Orthogonal Projection to Latent Structure Discriminant Analysis,discrimination models for adulterated milk were established in the present paper.Forty adulterated milk samples with melamine(0.01~3 g · L-1)and 40 adulterated milk samples with urea (1 ~20 g · L-1)were prepared,respectively.Then the near-infrared absorption spectra of all samples were measured.The spectra in the range of 4 200~4 800 cm 1 were selected to construct the KOPLS-DA models for milk adulterated with melamine,milk adulterated with urea and milk adulterated with both melamine and urea The results showed that,compared with PLS-DA and OPLS-DA models,KOPLS-DA model had better discriminant ability for the adulterated milk,and its classification accuracy rate (CAR) for milk adulterated with melamine,milk adulterated with urea and milk adulterated with both melamine and urea were 95%,100% and 97.5%,respectively.%运用核隐变量正交投影(kernel orthogonal projection to latent structure,KOPLS)方法,建立掺杂牛奶与纯牛奶的判别模型.分别配置含有三聚氰胺牛奶(0.01~3g·L-1)和尿素牛奶(1~20 g·L-1)样品各40个,采集纯牛奶及掺杂牛奶样品的近红外光谱.选择4 200~4 800 em-1为建模区间,采用KOPLS分别建立掺杂三聚氰胺、掺杂尿素、两种掺杂牛奶与纯牛奶的判别模型,并利用这些模型对未知样品进行判别.研究结果表明:与偏最小二乘判别(partial least squares discriminant analysis,PLS-DA)和隐变量正交投影判别(orthogonal projections to latent structures discriminant analysis,OPLS-DA)建模方法相比,KOPLS-DA具有更强的掺杂判别能力,对掺杂三聚氰胺、掺杂尿素牛奶和两种掺杂牛奶的判别正确率分别为95%,100%和97.5%.

  3. Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment

    Science.gov (United States)

    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…

  4. Predictors of drinking patterns in adolescence: a latent class analysis.

    Science.gov (United States)

    Jackson, Nicki; Denny, Simon; Sheridan, Janie; Fleming, Terry; Clark, Terryann; Teevale, Tasileta; Ameratunga, Shanthi

    2014-02-01

    Uni-dimensional measures of alcohol consumption may be unable to fully capture the complexity of adolescent drinking and experience of alcohol-related harms. Latent class analysis provides an empirical method to understand different adolescent drinking patterns. Latent class analysis was used to create typologies of drinking among the 5018 current drinkers in the national Youth '07 survey. Determinants of drinking patterns were identified using multinomial logistic regression. Four latent classes were identified, demonstrating an overall increase in risk of alcohol-related outcomes from increasing consumption. One class strongly deviated from this pattern, having moderate consumption patterns but disproportionately high levels of alcohol-related problems. Multinomial logistic regression found that the strongest predictors of belonging to high-risk drinking typologies were having a positive attitude to regular alcohol use, buying own alcohol, peers using alcohol, and obtaining alcohol from friends and/or other adults. Other significant predictors included being male, having a strong connection to friends, having parents with a low level of knowledge of their daily activities and poor connection to school. Class membership also varied by ethnicity. The latent class approach demonstrated variability in alcohol-related harms across groups of students with different drinking patterns. Longitudinal studies are necessary to determine the causes of this variability in order to inform the development of targeted policy and preventative interventions. Legislative controls, such as increasing the legal purchase age and reducing the commercial availability of alcohol, will continue to be important strategies for reducing harm in young people. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Relations of the morphological characteristic latent structure and body posture indicators in children aged seven to nine years.

    Science.gov (United States)

    Pausić, Jelena; Cavala, Marijana; Katić, Ratko

    2006-09-01

    With the aim of determining the connection between the indicators of body posture and latent structure of morphological variables in children aged 7 and 8 years, first and second grade of primary school, a set of 17 morphological measures and 12 body posture indicators were longitudinally applied to a sample of 110 boys and 114 girls. The latent structure of morphological variables in both sexes was defined by three factors but at a different order of significance: in boys, the order was longitudinal dimensionality, voluminosity, mass and subcutaneous fat tissue and transverse dimensionality, whereas in girls the order was voluminosity, mass and subcutaneous fat tissue, longitudinal dimensionality and transverse dimensionality. The latent structure of torax body posture indicator was defined by two factors, the status of body posture of the rear part of the thorax, and status of the body posture of the front part of the thorax. The results obtained by canonical correlation analysis between predictive variables, morphological latent structure and criterion variables, latent structure of thorax body posture indicators with two posture indicators of the chest and one of the foot status, showed two important pairs of canonical roots on each measurement, suggesting a significant association between these two sets of parameters.

  6. Psychiatric comorbidity among adults with schizophrenia: a latent class analysis.

    Science.gov (United States)

    Tsai, Jack; Rosenheck, Robert A

    2013-11-30

    Schizophrenia is a severe mental illness that often co-occurs with and can be exacerbated by other psychiatric conditions. There have not been adequate efforts to examine schizophrenia and psychiatric comorbidity beyond pairwise examination using clusters of diagnoses. This study used latent class analysis to characterize patterns of 5-year psychiatric comorbidity among a national sample of adults with schizophrenia. Baseline data from 1446 adults with schizophrenia across 57 sites in the United States were analyzed. Three latent classes were identified labeled Solely Schizophrenia, Comorbid Anxiety and Depressive Disorders with Schizophrenia, and Comorbid Addiction and Schizophrenia. Adults in the Solely Schizophrenia class had significantly better mental health than those in the two comorbid classes, but poorer illness and treatment insight than those with comorbid anxiety and depressive disorders. These results suggest that addiction and schizophrenia may represent a separate latent profile from depression, anxiety, and schizophrenia. More research is needed on how treatment can take advantage of the greater insight possessed by those with schizophrenia and comorbid anxiety and depression.

  7. Sex determination of human skeletal populations using latent profile analysis.

    Science.gov (United States)

    Passalacqua, Nicholas V; Zhang, Zhen; Pierce, Steven J

    2013-08-01

    Accurately estimating biological sex from the human skeleton can be especially difficult for fragmentary or incomplete remains often encountered in bioarchaeological contexts. Where typical anatomically dimorphic skeletal regions are incomplete or absent, observers often take their best guess to classify biological sex. Latent profile analysis (LPA) is a mixture modeling technique which uses observed continuous data to estimate unobserved categorical group membership using posterior probabilities. In this study, sex is the latent variable (male and female are the two latent classes), and the indicator variables used here were eight standard linear measurements (long bone lengths, diaphyseal and articular breadths, and circumferences). Mplus (Muthén and Muthén: Mplus user's guide, 6th ed. Los Angeles: Muthén & Muthén, 2010) was used to obtain maximum likelihood estimates for latent class membership from a known sample of individuals from the forensic data bank (FDB) (Jantz and Moore-Jansen: Database for forensic anthropology in the United States 1962-1991, Ann Arbor, MI: Interuniversity Consortium for Political and Social Research, 2000) (n = 1,831), yielding 87% of correct classification for sex. Then, a simulation extracted 5,000 different random samples of 206 complete cases each from the FDB (these cases also had known sex). We then artificially imposed patterns of missing data similar to that observed in a poorly preserved bioarchaeological sample from Medieval Asturias, Spain (n = 206), and ran LPA on each sample. This tested the efficacy of LPA under extreme conditions of poor preservation (missing data, 42%). The simulation yielded an average of 82% accuracy, indicating that LPA is robust to large amounts of missing data when analyzing incomplete skeletons.

  8. BEYOND SEM: GENERAL LATENT VARIABLE MODELING

    National Research Council Canada - National Science Library

    Muthén, Bengt O

    2002-01-01

    This article gives an overview of statistical analysis with latent variables. Using traditional structural equation modeling as a starting point, it shows how the idea of latent variables captures a wide variety of statistical concepts...

  9. DISCOVERY OF LATENT STRUCTURES: EXPERIENCE WITH THE COIL CHALLENGE 2000 DATA SET

    Institute of Scientific and Technical Information of China (English)

    Nevin L. ZHANG; Yi WANG; Tao CHEN

    2008-01-01

    The authors present a case study to demonstrate the possibility of discovering complex and interesting latent structures using hierarchical latent class (HLC) models. A similar effort was made earlier by Zhang (2002), but that study involved only small applications with 4 or 5 observed variables and no more than 2 latent variables due to the lack of efficient learning algorithms. Significant progress has been made since then on algorithmic research, and it is now possible to learn HLC models with dozens of observed variables. This allows us to demonstrate the benefits of HLC models more convincingly than before. The authors have successfully analyzed the CoIL Challenge 2000 data set using HLC models. The model obtained consists of 22 latent variables, and its structure is intuitively appealing. It is exciting to know that such a large and meaningful latent structure can be automatically inferred from data.

  10. A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

    Science.gov (United States)

    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)

  11. Latent Factor Structure of DSM-5 Posttraumatic Stress Disorder

    Science.gov (United States)

    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

  12. Latent Factor Structure of DSM-5 Posttraumatic Stress Disorder.

    Science.gov (United States)

    Gentes, Emily; Dennis, Paul A; Kimbrel, Nathan A; Kirby, Angela C; Hair, Lauren P; Beckham, Jean C; Calhoun, Patrick S

    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.

  13. From paragraph to graph: latent semantic analysis for information visualization.

    Science.gov (United States)

    Landauer, Thomas K; Laham, Darrell; Derr, Marcia

    2004-04-01

    Most techniques for relating textual information rely on intellectually created links such as author-chosen keywords and titles, authority indexing terms, or bibliographic citations. Similarity of the semantic content of whole documents, rather than just titles, abstracts, or overlap of keywords, offers an attractive alternative. Latent semantic analysis provides an effective dimension reduction method for the purpose that reflects synonymy and the sense of arbitrary word combinations. However, latent semantic analysis correlations with human text-to-text similarity judgments are often empirically highest at approximately 300 dimensions. Thus, two- or three-dimensional visualizations are severely limited in what they can show, and the first and/or second automatically discovered principal component, or any three such for that matter, rarely capture all of the relations that might be of interest. It is our conjecture that linguistic meaning is intrinsically and irreducibly very high dimensional. Thus, some method to explore a high dimensional similarity space is needed. But the 2.7 x 10(7) projections and infinite rotations of, for example, a 300-dimensional pattern are impossible to examine. We suggest, however, that the use of a high dimensional dynamic viewer with an effective projection pursuit routine and user control, coupled with the exquisite abilities of the human visual system to extract information about objects and from moving patterns, can often succeed in discovering multiple revealing views that are missed by current computational algorithms. We show some examples of the use of latent semantic analysis to support such visualizations and offer views on future needs.

  14. Development of Fraction Comparison Strategies: A Latent Transition Analysis.

    Science.gov (United States)

    Rinne, Luke F; Ye, Ai; Jordan, Nancy C

    2017-02-20

    The present study investigated the development of fraction comparison strategies through a longitudinal analysis of children's responses to a fraction comparison task in 4th through 6th grades (N = 394). Participants were asked to choose the larger value for 24 fraction pairs blocked by fraction type. Latent class analysis of performance over item blocks showed that most children initially exhibited a "whole number bias," indicating that larger numbers in numerators and denominators produce larger fraction values. However, some children instead chose fractions with smaller numerators and denominators, demonstrating a partial understanding that smaller numbers can yield larger fractions. Latent transition analysis showed that most children eventually adopted normative comparison strategies. Children who exhibited a partial understanding by choosing fractions with smaller numbers were more likely to adopt normative comparison strategies earlier than those with larger number biases. Controlling for general math achievement and other cognitive abilities, whole number line estimation accuracy predicted the probability of transitioning to normative comparison strategies. Exploratory factor analyses showed that over time, children appeared to increasingly represent fractions as discrete magnitudes when simpler strategies were unavailable. These results support the integrated theory of numerical development, which posits that an understanding of numbers as magnitudes unifies the process of learning whole numbers and fractions. The findings contrast with conceptual change theories, which propose that children must move from a view of numbers as counting units to a new view that accommodates fractions to overcome whole number bias. (PsycINFO Database Record

  15. Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error.

    Science.gov (United States)

    Marsh, Herbert W; Lüdtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthén, Bengt; Nagengast, Benjamin

    2009-11-30

    This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2) levels and sampling error due the sampling of persons in the aggregation of L1 characteristics to form L2 constructs. We consider a set of models that are latent or manifest in relation to sampling items (measurement error) and sampling of persons (sampling error) and discuss when different models might be most useful. We demonstrate the flexibility of these 4 core models by extending them to include random slopes, latent (single-level or cross-level) interactions, and latent quadratic effects. Substantively we use these models to test the big-fish-little-pond effect (BFLPE), showing that individual student levels of academic self-concept (L1-ASC) are positively associated with individual level achievement (L1-ACH) and negatively associated with school-average achievement (L2-ACH)-a finding with important policy implications for the way schools are structured. Extending tests of the BFLPE in new directions, we show that the nonlinear effects of the L1-ACH (a latent quadratic effect) and the interaction between gender and L1-ACH (an L1 × L1 latent interaction) are not significant. Although random-slope models show no significant school-to-school variation in relations between L1-ACH and L1-ASC, the negative effects of L2-ACH (the BFLPE) do vary somewhat with individual L1-ACH. We conclude with implications for diverse applications of the set of latent contextual models, including recommendations about their implementation, effect size estimates (and confidence intervals) appropriate to multilevel models, and directions for further research in contextual effect analysis.

  16. Pathways of Children’s Long-Term Living Arrangements: A Latent Class Analysis

    Science.gov (United States)

    Mitchell, Katherine Stamps

    2013-01-01

    This study employed latent class analysis to create children’s family structure trajectories from birth through adolescence using merged mother and child data from the National Longitudinal Survey of Youth (N=1,870). Input variables distinguished between biological fathers and stepfathers as well as mother’s marriages and cohabitations. The best-fitting model revealed 5 latent trajectories of children’s long-term family structure: continuously married biological parents (55%), long-term single mothers (18%), married biological parents who divorce (12%), a highly unstable trajectory distinguished by gaining at least one stepfather (11%), and cohabiting biological parents who either marry or break up (4%). Multinomial logistic regression indicated that mother’s education, race, teen birth status, and family of origin characteristics were important predictors of the long-term family trajectories in which their children grew up. These findings suggest that latent class analysis is a valuable statistical tool for understanding children’s complete family structure experiences. PMID:23859731

  17. High resolution ultraviolet imaging spectrometer for latent image analysis.

    Science.gov (United States)

    Lyu, Hang; Liao, Ningfang; Li, Hongsong; Wu, Wenmin

    2016-03-21

    In this work, we present a close-range ultraviolet imaging spectrometer with high spatial resolution, and reasonably high spectral resolution. As the transmissive optical components cause chromatic aberration in the ultraviolet (UV) spectral range, an all-reflective imaging scheme is introduced to promote the image quality. The proposed instrument consists of an oscillating mirror, a Cassegrain objective, a Michelson structure, an Offner relay, and a UV enhanced CCD. The finished spectrometer has a spatial resolution of 29.30μm on the target plane; the spectral scope covers both near and middle UV band; and can obtain approximately 100 wavelength samples over the range of 240~370nm. The control computer coordinates all the components of the instrument and enables capturing a series of images, which can be reconstructed into an interferogram datacube. The datacube can be converted into a spectrum datacube, which contains spectral information of each pixel with many wavelength samples. A spectral calibration is carried out by using a high pressure mercury discharge lamp. A test run demonstrated that this interferometric configuration can obtain high resolution spectrum datacube. The pattern recognition algorithm is introduced to analyze the datacube and distinguish the latent traces from the base materials. This design is particularly good at identifying the latent traces in the application field of forensic imaging.

  18. The latent structure of attention deficit/hyperactivity disorder in an adult sample.

    Science.gov (United States)

    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.

  19. Bayesian Analysis of Multivariate Latent Curve Models with Nonlinear Longitudinal Latent Effects

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum; Hser, Yih-Ing

    2009-01-01

    In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social, psychological, and medical research, investigators often deal with latent variables that cannot be observed directly…

  20. Temporal eating patterns: a latent class analysis approach.

    Science.gov (United States)

    Leech, Rebecca M; Worsley, Anthony; Timperio, Anna; McNaughton, Sarah A

    2017-01-07

    There is some evidence that large energy intakes towards the end of the day are associated with adverse health outcomes, however, studies of temporal eating patterns across the day are rare. This study examines the temporal eating patterns of Australian adults using latent class analysis (LCA), as a novel approach. Dietary data (n = 2402 men and n = 2840 women, ≥19 years) from two 24-h recalls collected during the 2011-12 Australian National Nutrition and Physical Activity Survey were analyzed. LCA was performed to identify distinct temporal eating patterns based on whether or not an eating occasion (EO) occurred within each hour of the day. F and adjusted-chi(2) tests assessed differences in sociodemographic and eating patterns (e.g., meal, snack and EO frequency) between latent classes. Three patterns, labelled "Conventional" (men: 43%, women: 41%), "Later lunch" (men: 34%, women: 34%) and "Grazing" (men: 23%, women: 25%) were identified. Men and women with a "Grazing" pattern were significantly younger (P patterns. The "Grazing" pattern was also characterized by a higher EO frequency (P patterns in adults that varied by age, EO frequency, snack frequency and energy intake pattern. LCA is a useful approach to capture differences in EO timing across the day. Future research should examine associations between temporal eating patterns and health.

  1. A Herpesviral Lytic Protein Regulates the Structure of Latent Viral Chromatin

    Directory of Open Access Journals (Sweden)

    Priya Raja

    2016-05-01

    Full Text Available Latent infections by viruses usually involve minimizing viral protein expression so that the host immune system cannot recognize the infected cell through the viral peptides presented on its cell surface. Herpes simplex virus (HSV, for example, is thought to express noncoding RNAs such as latency-associated transcripts (LATs and microRNAs (miRNAs as the only abundant viral gene products during latent infection. Here we describe analysis of HSV-1 mutant viruses, providing strong genetic evidence that HSV-infected cell protein 0 (ICP0 is expressed during establishment and/or maintenance of latent infection in murine sensory neurons in vivo. Studies of an ICP0 nonsense mutant virus showed that ICP0 promotes heterochromatin and latent and lytic transcription, arguing that ICP0 is expressed and functional. We propose that ICP0 promotes transcription of LATs during establishment or maintenance of HSV latent infection, much as it promotes lytic gene transcription. This report introduces the new concept that a lytic viral protein can be expressed during latent infection and can serve dual roles to regulate viral chromatin to optimize latent infection in addition to its role in epigenetic regulation during lytic infection. An additional implication of the results is that ICP0 might serve as a target for an antiviral therapeutic acting on lytic and latent infections.

  2. Statistical identification of syndromes feature and structure of disease of western medicine based on general latent structure model.

    Science.gov (United States)

    Yang, Wei; Yi, Dan-Hui; Xie, Yan-Ming; Tian, Feng

    2012-11-01

    Syndrome differentiation is the character of Chinese medicine (CM). Disease differentiation is the principle of Western medicine (WM). Identifying basic syndromes feature and structure of disease of WM is an important avenue for prevention and treatment of integrated Chinese and Western medicine. The idea here is first to divide all patients suffering from a disease of WM into several groups in the light of the stage of the disease, and secondly to identify basic syndromes feature in a distinct stage, and finally to achieve the purpose of syndrome differentiation. Syndrome differentiation is simply taken as a classifier that classifies patients into distinct classes primarily based on overall observation of their symptoms. Previous clustering methods are unable to cope with the complexity of CM. We therefore show a new multi-dimensional clustering method in the form of general latent structure (GLS) model, which is a suitable statistical learning technique of latent class analysis. In this paper, we learn an optimal GLS model which reflects much better model quality compared with other latent class models from the osteoporosis patient of community women (OPCW) real data including 40-65 year-old women whose bone mineral density (BMD) is less than mean-2.0 standard deviation (M-2.0SD). Further, we illustrate a case analysis of statistical identification of CM syndromes feature and structure of OPCW from qualitative and quantitative contents through the GLS model. Our analysis has discovered natural clusters and structures that correspond well to CM basic syndrome and factors of osteoporosis patients (OP). The GLS model suggests the possibility of establishing objective and quantitative diagnosis standards for syndrome differentiation on OPCW. Hence, for the future it can provide a reference for the similar study from the perspective of a combination of disease differentiation and syndrome differentiation.

  3. Modeling Relational Data via Latent Factor Blockmodel

    CERN Document Server

    Gao, Sheng; Gallinari, Patrick

    2012-01-01

    In this paper we address the problem of modeling relational data, which appear in many applications such as social network analysis, recommender systems and bioinformatics. Previous studies either consider latent feature based models but disregarding local structure in the network, or focus exclusively on capturing local structure of objects based on latent blockmodels without coupling with latent characteristics of objects. To combine the benefits of the previous work, we propose a novel model that can simultaneously incorporate the effect of latent features and covariates if any, as well as the effect of latent structure that may exist in the data. To achieve this, we model the relation graph as a function of both latent feature factors and latent cluster memberships of objects to collectively discover globally predictive intrinsic properties of objects and capture latent block structure in the network to improve prediction performance. We also develop an optimization transfer algorithm based on the general...

  4. Extraction of Latent Dynamical Structure from Time-Series Spectral Data

    Science.gov (United States)

    Murata, Shin; Nagata, Kenji; Uemura, Makoto; Okada, Masato

    2016-10-01

    The estimation of latent dynamics from time-series data is an important problem in a broad range of fields. In this research, we focused on time-series spectral data, which are obtained in planetary science, condensed matter science, and many other fields, and their latent dynamics. Time-series spectral data have a multiple-peak structure and the center, width, and amplitude of each peak reflect the nature of the subject. Here, we propose a method to estimate the parameters of peaks, the parameters of their latent dynamics, the number of peaks, and the order of the model by using Bayesian inference.

  5. Latent semantic analysis: a new method to measure prose recall.

    Science.gov (United States)

    Dunn, John C; Almeida, Osvaldo P; Barclay, Lee; Waterreus, Anna; Flicker, Leon

    2002-02-01

    The aim of this study was to compare traditional methods of scoring the Logical Memory test of the Wechsler Memory Scale-III with a new method based on Latent Semantic Analysis (LSA). LSA represents texts as vectors in a high-dimensional semantic space and the similarity of any two texts is measured by the cosine of the angle between their respective vectors. The Logical Memory test was administered to a sample of 72 elderly individuals, 14 of whom were classified as cognitively impaired by the Mini-Mental State Examination (MMSE). The results showed that LSA was at least as valid and sensitive as traditional measures. Partial correlations between prose recall measures and measures of cognitive function indicated that LSA explained all the relationship between Logical Memory and general cognitive function. This suggests that LSA may serve as an improved measure of prose recall.

  6. PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

    Science.gov (United States)

    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.

  7. Development and study of a parallel algorithm of iteratively forming latent functionally-determined structures for classification and analysis of meteorological data

    Science.gov (United States)

    Sorokin, V. A.; Volkov, Yu V.; Sherstneva, A. I.; Botygin, I. A.

    2016-11-01

    This paper overviews a method of generating climate regions based on an analytic signal theory. When applied to atmospheric surface layer temperature data sets, the method allows forming climatic structures with the corresponding changes in the temperature to make conclusions on the uniformity of climate in an area and to trace the climate changes in time by analyzing the type group shifts. The algorithm is based on the fact that the frequency spectrum of the thermal oscillation process is narrow-banded and has only one mode for most weather stations. This allows using the analytic signal theory, causality conditions and introducing an oscillation phase. The annual component of the phase, being a linear function, was removed by the least squares method. The remaining phase fluctuations allow consistent studying of their coordinated behavior and timing, using the Pearson correlation coefficient for dependence evaluation. This study includes program experiments to evaluate the calculation efficiency in the phase grouping task. The paper also overviews some single-threaded and multi-threaded computing models. It is shown that the phase grouping algorithm for meteorological data can be parallelized and that a multi-threaded implementation leads to a 25-30% increase in the performance.

  8. pong: fast analysis and visualization of latent clusters in population genetic data.

    Science.gov (United States)

    Behr, Aaron A; Liu, Katherine Z; Liu-Fang, Gracie; Nakka, Priyanka; Ramachandran, Sohini

    2016-09-15

    A series of methods in population genetics use multilocus genotype data to assign individuals membership in latent clusters. These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. Inference from mixed-membership models can produce different output matrices when repeatedly applied to the same inputs, and the number of latent clusters is a parameter that is often varied in the analysis pipeline. For these reasons, quantifying, visualizing, and annotating the output from mixed-membership models are bottlenecks for investigators across multiple disciplines from ecology to text data mining. We introduce pong, a network-graphical approach for analyzing and visualizing membership in latent clusters with a native interactive D3.js visualization. pong leverages efficient algorithms for solving the Assignment Problem to dramatically reduce runtime while increasing accuracy compared with other methods that process output from mixed-membership models. We apply pong to 225 705 unlinked genome-wide single-nucleotide variants from 2426 unrelated individuals in the 1000 Genomes Project, and identify previously overlooked aspects of global human population structure. We show that pong outpaces current solutions by more than an order of magnitude in runtime while providing a customizable and interactive visualization of population structure that is more accurate than those produced by current tools. pong is freely available and can be installed using the Python package management system pip. pong's source code is available at https://github.com/abehr/pong aaron_behr@alumni.brown.edu or sramachandran@brown.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  9. Future expectations among adolescents: a latent class analysis.

    Science.gov (United States)

    Sipsma, Heather L; Ickovics, Jeannette R; Lin, Haiqun; Kershaw, Trace S

    2012-09-01

    Future expectations have been important predictors of adolescent development and behavior. Its measurement, however, has largely focused on single dimensions and misses potentially important components. This analysis investigates whether an empirically-driven, multidimensional approach to conceptualizing future expectations can substantively contribute to our understanding of adolescent risk behavior. We use data from the National Longitudinal Survey of Youth 1997 to derive subpopulations of adolescents based on their future expectations with latent class analysis. Multinomial regression then determines which covariates from Bronfenbrenner's ecological systems theory are associated with class membership. After modeling these covariates, we examine whether future expectations is associated with delinquency, substance use, and sexual experience. Our analysis suggests the emergence of four distinct classes labeled the Student Expectations, Student/Drinking Expectations, Victim Expectations, and Drinking/Arrest Expectations classes according to their indicator profiles. These classes differ with respect to covariates associated with membership; furthermore, they are all statistically and differentially associated with at least one adolescent risk behavior. This analysis demonstrates the additional benefit derived from using this multidimensional approach for studying future expectations. Further research is needed to investigate its stability and role in predicting adolescent risk behavior over time.

  10. Latent Semantic Learning with Structured Sparse Representation for Human Action Recognition

    CERN Document Server

    Lu, Zhiwu

    2011-01-01

    This paper proposes a novel latent semantic learning method for extracting high-level features (i.e. latent semantics) from a large vocabulary of abundant mid-level features (i.e. visual keywords) with structured sparse representation, which can help to bridge the semantic gap in the challenging task of human action recognition. To discover the manifold structure of midlevel features, we develop a spectral embedding approach to latent semantic learning based on L1-graph, without the need to tune any parameter for graph construction as a key step of manifold learning. More importantly, we construct the L1-graph with structured sparse representation, which can be obtained by structured sparse coding with its structured sparsity ensured by novel L1-norm hypergraph regularization over mid-level features. In the new embedding space, we learn latent semantics automatically from abundant mid-level features through spectral clustering. The learnt latent semantics can be readily used for human action recognition with ...

  11. Latent Variable Graphical Model Selection using Harmonic Analysis: Applications to the Human Connectome Project (HCP).

    Science.gov (United States)

    Kim, Won Hwa; Kim, Hyunwoo J; Adluru, Nagesh; Singh, Vikas

    2016-06-01

    A major goal of imaging studies such as the (ongoing) Human Connectome Project (HCP) is to characterize the structural network map of the human brain and identify its associations with covariates such as genotype, risk factors, and so on that correspond to an individual. But the set of image derived measures and the set of covariates are both large, so we must first estimate a 'parsimonious' set of relations between the measurements. For instance, a Gaussian graphical model will show conditional independences between the random variables, which can then be used to setup specific downstream analyses. But most such data involve a large list of 'latent' variables that remain unobserved, yet affect the 'observed' variables sustantially. Accounting for such latent variables is not directly addressed by standard precision matrix estimation, and is tackled via highly specialized optimization methods. This paper offers a unique harmonic analysis view of this problem. By casting the estimation of the precision matrix in terms of a composition of low-frequency latent variables and high-frequency sparse terms, we show how the problem can be formulated using a new wavelet-type expansion in non-Euclidean spaces. Our formulation poses the estimation problem in the frequency space and shows how it can be solved by a simple sub-gradient scheme. We provide a set of scientific results on ~500 scans from the recently released HCP data where our algorithm recovers highly interpretable and sparse conditional dependencies between brain connectivity pathways and well-known covariates.

  12. Modeling Psychological Attributes in Psychology - An Epistemological Discussion: Network Analysis vs. Latent Variables.

    Science.gov (United States)

    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.

  13. Exploration and confirmation of the latent variable structure of the Jefferson scale of empathy.

    Science.gov (United States)

    Hojat, Mohammadreza; LaNoue, Marianna

    2014-04-20

    To reaffirm the underlying components of the JSE by using exploratory factor analysis (EFA), and to confirm its latent variable structure by using confirmatory factor analysis (CFA). Research participants included 2,612 medical students who entered Jefferson Medical College between 2002 and 2012. This sample was divided into two groups: Matriculants between 2002 and 2007 (n=1,380) and be-tween 2008 and 2012 (n=1,232). Data for 2002-2007 matriculants were subjected to EFA (principal component factor extraction), and data for matriculants of 2008-2012 were used for CFA (structural equation modeling, and root mean square error for approximation. The EFA resulted in three factors: "perspective-taking," "compassionate care" and "walking in patient's shoes" replicating the 3-factor model reported in most of the previous studies. The CFA showed that the 3-factor model was an acceptable fit, thus confirming the latent variable structure emerged in the EFA. Corrected item-total score correlations for the total sample were all positive and statistically significant, ranging from 0.13 to 0.61 with a median of 0.44 (p=0.01). The item discrimination effect size indices (contrasting item mean scores for the top-third versus bottom-third JSE scorers) ranged from 0.50 to 1.4 indicating that the differences in item mean scores between top and bottom scorers on the JSE were of practical importance. Cronbach's alpha coefficient of the JSE for the total sample was 0.80, ranging from 0.75 to 0.84 for matriculatnts of different years. Findings provided further support for under-lying constructs of the JSE, adding to its credibility.

  14. 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.

  15. 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.

  16. Sentiment Detection of Web Users Using Probabilistic Latent Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Weijian Ren

    2014-10-01

    Full Text Available With the wide application of Internet in almost all fields, it has become the most important way for information publication, providing a large number of channels for spreading public opinion. Public opinions, as the response of Internet users to the information such as social events and government policies, reflect the status of both society and economics, which is highly valuable for the decision-making and public relations of enterprises. At present, the analysis methods for Internet public opinion are mainly based on discriminative approaches, such as Support Vector Machine (SVM and neural network. However, when these approaches analyze the sentiment of Internet public opinion, they are failed to exploit information hidden in text, e.g. topic. Motivated by the above observation, this paper proposes a detection method for public sentiment based on Probabilistic Latent Semantic Analysis (PLSA model. PLSA inherits the advantages of LSA, exploiting the semantic topic hidden in data. The procedure of detecting the public sentiment using this algorithm is composed of three main steps: (1 Chinese word segmentation and word refinement, with which each document is represented by a bag of words; (2 modeling the probabilistic distribution of documents using PLSA; (3 using the Z-vector of PLSA as the features of documents and delivering it to SVM for sentiment detection. We collect a set of text data from Weibo, blog, BBS etc. to evaluate our proposed approach. The experimental results shows that the proposed method in this paper can detect the public sentiment with high accuracy, outperforming the state-of-the-art approaches, i.e., word histogram based approach. The results also suggest that, text semantic analysis using PLSA could significantly boost the sentiment detection

  17. A Latent Class Analysis of Heterosexual Young Men's Masculinities.

    Science.gov (United States)

    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.

  18. A Typology of Child School Behavior: Investigation Using Latent Profile Analysis and Cluster Analysis

    Science.gov (United States)

    Mindrila, Diana L.

    2016-01-01

    To describe and facilitate the identification of child school behavior patterns, we developed a typology of child school behavior (ages 6-11 years) using the norming data (N = 2,338) for the second edition of the Behavior Assessment System for Children Teacher Rating-Child form). Latent profile analysis was conducted with the entire data set,…

  19. A Typology of Child School Behavior: Investigation Using Latent Profile Analysis and Cluster Analysis

    Science.gov (United States)

    Mindrila, Diana L.

    2016-01-01

    To describe and facilitate the identification of child school behavior patterns, we developed a typology of child school behavior (ages 6-11 years) using the norming data (N = 2,338) for the second edition of the Behavior Assessment System for Children Teacher Rating-Child form). Latent profile analysis was conducted with the entire data set,…

  20. Malingering as a Categorical or Dimensional Construct: The Latent Structure of Feigned Psychopathology as Measured by the SIRS and MMPI-2

    Science.gov (United States)

    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…

  1. Measuring the level of social support using latent class analysis.

    Science.gov (United States)

    Santos, Letícia Marques; Amorim, Leila Denise A F; Santos, Darci Neves; Barreto, Maurício L

    2015-03-01

    Different instruments have been used to measure social support in epidemiological studies of which the most widely used is the Medical Outcomes Study Social Support Scale (SSS-MOS). However, these studies lack measures of the level of social support on health risks. We used latent class analysis (LCA) to distinguish subgroups with different levels of perceived social support and tested the consistency of these subgroups by their associations with the prevalence of Common Mental Disorders (CMD). This is a cross-sectional study of 1013 mothers living in the city of Salvador, Brazil in which psychosocial data were collected through home visits using the SSS-MOS and the Self Reporting Questionnaire-20. For each dimension of social support analysed here, we selected models with two classes using LCA. Multivariate logistic regression models were used to estimate the association between participants' perceived social support and the prevalence of CMD to verify the consistency of the groups defined by LCA. There was a clear difference in the reporting of perceived social support between those classified as high or low using LCA. The probability of perceiving several types of social support was lower in the subgroup classified as low level of social support (13.7-59.8%), and it was much higher in the group classified as high level of social support (84.3-98%). A greater prevalence of CMD was found among mothers with lower levels of social support. LCA seems to be a useful tool to improve measurement of perceived social support by separation into two levels in which the lower level is associated with an increased prevalence of CMD. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Structural Equation Models of Latent Interactions: An Appropriate Standardized Solution and Its Scale-Free Properties

    Science.gov (United States)

    Wen, Zhonglin; Marsh, Herbert W.; Hau, Kit-Tai

    2010-01-01

    Standardized parameter estimates are routinely used to summarize the results of multiple regression models of manifest variables and structural equation models of latent variables, because they facilitate interpretation. Although the typical standardization of interaction terms is not appropriate for multiple regression models, straightforward…

  3. Heterogeneity in the Latent Structure of PTSD Symptoms among Canadian Veterans

    Science.gov (United States)

    Naifeh, James A.; Richardson, J. Don; Del Ben, Kevin S.; Elhai, Jon D.

    2010-01-01

    The current study used factor mixture modeling to identify heterogeneity (i.e., latent classes) in 2 well-supported models of posttraumatic stress disorder's (PTSD) factor structure. Data were analyzed from a clinical sample of 405 Canadian veterans evaluated for PTSD. Results were consistent with our hypotheses. Each PTSD factor model was best…

  4. A Taxometric Study of the Latent Structure of Disgust Sensitivity: Converging Evidence for Dimensionality

    Science.gov (United States)

    Olatunji, Bunmi O.; Broman-Fulks, Joshua J.

    2007-01-01

    Disgust sensitivity has recently been implicated as a specific vulnerability factor for several anxiety-related disorders. However, it is not clear whether disgust sensitivity is a dimensional or categorical phenomenon. The present study examined the latent structure of disgust by applying three taxometric procedures (maximum eigenvalue, mean…

  5. A Taxometric Study of the Latent Structure of Disgust Sensitivity: Converging Evidence for Dimensionality

    Science.gov (United States)

    Olatunji, Bunmi O.; Broman-Fulks, Joshua J.

    2007-01-01

    Disgust sensitivity has recently been implicated as a specific vulnerability factor for several anxiety-related disorders. However, it is not clear whether disgust sensitivity is a dimensional or categorical phenomenon. The present study examined the latent structure of disgust by applying three taxometric procedures (maximum eigenvalue, mean…

  6. Mediation Analysis in a Latent Growth Curve Modeling Framework

    Science.gov (United States)

    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…

  7. 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...

  8. Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

    Science.gov (United States)

    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.

  9. Where are Children Active and Does it Matter for Physical Activity? A Latent Transition Analysis.

    Science.gov (United States)

    Colabianchi, Natalie; Griffin, Jamie L; McIver, Kerry L; Dowda, Marsha; Pate, Russell R

    2016-12-01

    Numerous studies have focused on the role of environments in promoting physical activity, but few studies have examined the specific locations where children are active and whether being active in these locations is associated with physical activity levels over time. Self-reported locations of where physical activity occurred and physical activity measured via accelerometry were obtained for a cohort of 520 children in 5th and 6th grades. Latent class analysis was used to generate classes of children defined by the variety of locations where they were active (ie, home, school grounds, gyms, recreational centers, parks or playgrounds, neighborhood, and church). Latent transition analyses were used to characterize how these latent classes change over time and to determine whether the latent transitions were associated with changes in physical activity levels. Two latent classes were identified at baseline with the majority of children in the class labeled as 'limited variety.' Most children maintained their latent status over time. Physical activity levels declined for all groups, but significantly less so for children who maintained their membership in the 'greater variety' latent status. Supporting and encouraging physical activity in a variety of locations may improve physical activity levels in children.

  10. A latent factor linear mixed model for high-dimensional longitudinal data analysis.

    Science.gov (United States)

    An, Xinming; Yang, Qing; Bentler, Peter M

    2013-10-30

    High-dimensional longitudinal data involving latent variables such as depression and anxiety that cannot be quantified directly are often encountered in biomedical and social sciences. Multiple responses are used to characterize these latent quantities, and repeated measures are collected to capture their trends over time. Furthermore, substantive research questions may concern issues such as interrelated trends among latent variables that can only be addressed by modeling them jointly. Although statistical analysis of univariate longitudinal data has been well developed, methods for modeling multivariate high-dimensional longitudinal data are still under development. In this paper, we propose a latent factor linear mixed model (LFLMM) for analyzing this type of data. This model is a combination of the factor analysis and multivariate linear mixed models. Under this modeling framework, we reduced the high-dimensional responses to low-dimensional latent factors by the factor analysis model, and then we used the multivariate linear mixed model to study the longitudinal trends of these latent factors. We developed an expectation-maximization algorithm to estimate the model. We used simulation studies to investigate the computational properties of the expectation-maximization algorithm and compare the LFLMM model with other approaches for high-dimensional longitudinal data analysis. We used a real data example to illustrate the practical usefulness of the model. Copyright © 2013 John Wiley & Sons, Ltd.

  11. Latent Class Analysis of Differential Item Functioning on the Peabody Picture Vocabulary Test-III

    Science.gov (United States)

    Webb, Mi-young Lee; Cohen, Allan S.; Schwanenflugel, Paula J.

    2008-01-01

    This study investigated the use of latent class analysis for the detection of differences in item functioning on the Peabody Picture Vocabulary Test-Third Edition (PPVT-III). A two-class solution for a latent class model appeared to be defined in part by ability because Class 1 was lower in ability than Class 2 on both the PPVT-III and the…

  12. Models with discrete latent variables for analysis of categorical data: a framework and a MATLAB MDLV toolbox.

    Science.gov (United States)

    Yu, Hsiu-Ting

    2013-12-01

    Studies in the social and behavioral sciences often involve categorical data, such as ratings, and define latent constructs underlying the research issues as being discrete. In this article, models with discrete latent variables (MDLV) for the analysis of categorical data are grouped into four families, defined in terms of two dimensions (time and sampling) of the data structure. A MATLAB toolbox (referred to as the "MDLV toolbox") was developed for applying these models in practical studies. For each family of models, model representations and the statistical assumptions underlying the models are discussed. The functions of the toolbox are demonstrated by fitting these models to empirical data from the European Values Study. The purpose of this article is to offer a framework of discrete latent variable models for data analysis, and to develop the MDLV toolbox for use in estimating each model under this framework. With this accessible tool, the application of data modeling with discrete latent variables becomes feasible for a broad range of empirical studies.

  13. Latent Utility Shocks in a Structural Empirical Asset Pricing Model

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper; Raahauge, Peter

    We consider a random utility extension of the fundamental Lucas (1978) equilibriumasset pricing model. The resulting structural model leads naturally to a likelihoodfunction. We estimate the model using U.S. asset market data from 1871 to2000, using both dividends and earnings as state variables....... We find that current dividendsdo not forecast future utility shocks, whereas current utility shocks do forecastfuture dividends. The estimated structural model produces a sequence of predictedutility shocks which provide better forecasts of future long-horizon stock market returnsthan the classical...... dividend-price ratio.KEYWORDS: Randomutility, asset pricing, maximumlikelihood, structuralmodel,return predictability...

  14. 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.

  15. Screening for personality disorders: A new questionnaire and its validation using Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Julia Lange

    2012-12-01

    Full Text Available Background: We evaluated a new screening instrument for personality disorders. The Personality Disorder Screening (PDS is a self-administered screening questionnaire that includes 12 items from the Personality Self Portrait (Oldham & Morris, 1990. Sampling and methods: The data of n = 966 participants recruited from the non-clinical population and from different clinical settings were analyzed using latent class analysis. Results: A 4-class model fitted the data best. It confirmed a classification model for personality disorders proposed by Gunderson (1984 and showed high reliability and validity. One class corresponded to “healthy” individuals (40.6 %, and one class to individuals with personality disorders (17.2 %. Two additional classes represented individuals with specific personality styles. Evidence for convergent validity was found in terms of strong associations of the classification with the Structured Clinical Interview (SCID-II for diagnosing personality disorders. The latent classes also showed theoretically expected associations with membership in different subsamples. Conclusions: The PDS shows promise as a new instrument for identifying different classes of personality disorder severity already at the screening stage of the diagnostic process.

  16. Structural equation modeling with latent variables for longitudinal blood pressure traits using general pedigrees.

    Science.gov (United States)

    Song, Yeunjoo E; Morris, Nathan J; Stein, Catherine M

    2016-01-01

    Structural equation modeling (SEM) has been used in a wide range of applied sciences including genetic analysis. The recently developed R package, strum, implements a framework for SEM for general pedigree data. We explored different SEM techniques using strum to analyze the multivariate longitudinal data and to ultimately test the association of genotypes on blood pressure traits. The quantitative blood pressure (BP) traits, systolic BP (SBP) and diastolic BP (DBP) were analyzed as the main traits of interest with age, sex, and smoking status as covariates. The single nucleotide polymorphism (SNP) genotype information from genome-wide association studies (GWAS) data was used for the test of association. The adjustment for hypertension treatment effect was done by the censored regression approach. Two different longitudinal data models, autoregressive model and latent growth curve model, were used to fit the longitudinal BP traits. The test of association for SNP was done using a novel score test within the SEM framework of strum. We found the 10 SNPs within the GWAS suggestive P value level, and among those 10, the most significant top 3 SNPs agreed in rank in both analysis models. The general SEM framework in strum is very useful to model and test for the association with massive genotype data and complex systems of multiple phenotypes with general pedigree data.

  17. Latent Structure of the Alexithymia Construct: A Taxometric Investigation

    Science.gov (United States)

    Parker, James D. A.; Keefer, Kateryna V.; Taylor, Graeme J.; Bagby, R. Michael

    2008-01-01

    Despite a wealth of research on the validity of alexithymia and its association with a number of common medical and psychiatric disorders, the fundamental question of whether alexithymia is best conceptualized as a dimensional or categorical construct remains unresolved. In the current investigation, taxometric analysis is used to examine the…

  18. Usage of a Responsible Gambling Tool: A Descriptive Analysis and Latent Class Analysis of User Behavior.

    Science.gov (United States)

    Forsström, David; Hesser, Hugo; Carlbring, Per

    2016-09-01

    Gambling is a common pastime around the world. Most gamblers can engage in gambling activities without negative consequences, but some run the risk of developing an excessive gambling pattern. Excessive gambling has severe negative economic and psychological consequences, which makes the development of responsible gambling strategies vital to protecting individuals from these risks. One such strategy is responsible gambling (RG) tools. These tools track an individual's gambling history and supplies personalized feedback and might be one way to decrease excessive gambling behavior. However, research is lacking in this area and little is known about the usage of these tools. The aim of this article is to describe user behavior and to investigate if there are different subclasses of users by conducting a latent class analysis. The user behaviour of 9528 online gamblers who voluntarily used a RG tool was analysed. Number of visits to the site, self-tests made, and advice used were the observed variables included in the latent class analysis. Descriptive statistics show that overall the functions of the tool had a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.

  19. Latent factor structure of a behavioral economic cigarette demand curve in adolescent smokers.

    Science.gov (United States)

    Bidwell, L Cinnamon; MacKillop, James; Murphy, James G; Tidey, Jennifer W; Colby, Suzanne M

    2012-11-01

    Behavioral economic demand curves, or quantitative representations of drug consumption across a range of prices, have been used to assess motivation for a variety of drugs. Such curves generate multiple measures of drug demand that are associated with cigarette consumption and nicotine dependence. However, little is known about the relationships among these facets of demand. The aim of the study was to quantify these relationships in adolescent smokers by using exploratory factor analysis to examine the underlying structure of the facets of nicotine incentive value generated from a demand curve measure. Participants were 138 adolescent smokers who completed a hypothetical cigarette purchase task, which assessed estimated cigarette consumption at escalating levels of price/cigarette. Demand curves and five facets of demand were generated from the measure: Elasticity (i.e., 1/α or proportionate price sensitivity); Intensity (i.e., consumption at zero price); O(max) (i.e., maximum financial expenditure on cigarettes); P(max) (i.e., price at which expenditure is maximized); and Breakpoint (i.e., the price that suppresses consumption to zero). Principal components analysis was used to examine the latent structure among the variables. The results revealed a two-factor solution, which were interpreted as "Persistence," reflecting insensitivity to escalating price, and "Amplitude," reflecting the absolute levels of consumption and price. These findings suggest a two factor structure of nicotine incentive value as measured via a demand curve. If supported, these findings have implications for understanding the relationships among individual demand indices in future behavioral economic studies and may further contribute to understanding of the nature of cigarette reinforcement.

  20. The Latent Factor Structure of Acute Stress Disorder following Bank Robbery

    DEFF Research Database (Denmark)

    Hansen, M.; Lasgaard, M.; Elklit, A.

    2013-01-01

    OBJECTIVE: 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...... 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. DESIGN: 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. 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...

  1. Classifying life course trajectories : a comparison of latent class and sequence analysis

    NARCIS (Netherlands)

    Barban, Nicola; Billari, Francesco C.

    2012-01-01

    . We compare two techniques that are widely used in the analysis of life course trajectories: latent class analysis and sequence analysis. In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of t

  2. Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks.

    Science.gov (United States)

    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.

  3. [The hierarchical clustering analysis of hyperspectral image based on probabilistic latent semantic analysis].

    Science.gov (United States)

    Yi, Wen-Bin; Shen, Li; Qi, Yin-Feng; Tang, Hong

    2011-09-01

    The paper introduces the Probabilistic Latent Semantic Analysis (PLSA) to the image clustering and an effective image clustering algorithm using the semantic information from PLSA is proposed which is used for hyperspectral images. Firstly, the ISODATA algorithm is used to obtain the initial clustering result of hyperspectral image and the clusters of the initial clustering result are considered as the visual words of the PLSA. Secondly, the object-oriented image segmentation algorithm is used to partition the hyperspectral image and segments with relatively pure pixels are regarded as documents in PLSA. Thirdly, a variety of identification methods which can estimate the best number of cluster centers is combined to get the number of latent semantic topics. Then the conditional distributions of visual words in topics and the mixtures of topics in different documents are estimated by using PLSA. Finally, the conditional probabilistic of latent semantic topics are distinguished using statistical pattern recognition method, the topic type for each visual in each document will be given and the clustering result of hyperspectral image are then achieved. Experimental results show the clusters of the proposed algorithm are better than K-MEANS and ISODATA in terms of object-oriented property and the clustering result is closer to the distribution of real spatial distribution of surface.

  4. Individuation, peers, and adolescent alcohol use: a latent growth analysis.

    Science.gov (United States)

    Bray, James H; Adams, Gerald J; Getz, J Greg; McQueen, Amy

    2003-06-01

    The study used latent growth modeling to investigate longitudinal relationships between individuation, peer alcohol use, and adolescent alcohol use among African American, Mexican American, and non-Hispanic White adolescents (N = 6,048) from 7th, 8th, and 9th grades over a 3-year period. Initial levels of peer alcohol use were significantly related to changes in adolescents' alcohol use, whereas initial adolescent alcohol use also significantly related to changes in peers' alcohol use, suggesting a bidirectional relationship. Higher levels of intergenerational individuation were related to smaller increases in adolescent alcohol use and higher levels of separation were related to larger increases in youth drinking. The findings were similar across ethnic groups. Implications for development of prevention and intervention programs are discussed.

  5. Examining Combinations of Social Physique Anxiety and Motivation Regulations Using Latent Profile Analysis

    Science.gov (United States)

    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…

  6. Latent vs. Observed Variables : Analysis of Irrigation Water Efficiency Using SEM and SUR

    NARCIS (Netherlands)

    Tang, Jianjun; Folmer, Henk

    2016-01-01

    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

  7. Latent structure of the social anxiety scale and relations between social anxiety and irrational beliefs

    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.

  8. The Stability of Social Desirability: A Latent Change Analysis.

    Science.gov (United States)

    Haberecht, Katja; Schnuerer, Inga; Gaertner, Beate; John, Ulrich; Freyer-Adam, Jennis

    2015-08-01

    Social desirability has been shown to be stable in samples with higher school education. However, little is known about the stability of social desirability in more heterogeneous samples differing in school education. This study aimed to investigate the stability of social desirability and which factors predict interindividual differences in intraindividual change. As part of a randomized controlled trial, 1,243 job seekers with unhealthy alcohol use were systematically recruited at three job agencies. A total of 1,094 individuals (87.8%) participated in at least one of two follow-ups (6 and 15 months after baseline) and constitute this study's sample. The Social Desirability Scale-17 was applied. Two latent change models were conducted: Model 1 tested for interindividual differences in intraindividual change of social desirability between both follow-ups; Model 2 included possible predictors (age, sex, education, current employment status) of interindividual differences in intraindividual change. Model 1 revealed a significant decrease of social desirability over time. Model 2 revealed school education to be the only significant predictor of change. These findings indicate that stability of social desirability may depend on school education. It may not be as stable in individuals with higher school education as in individuals with lower education. © 2014 Wiley Periodicals, Inc.

  9. On matrices with low-rank-plus-shift structure: Partial SVD and latent semantic indexing

    Energy Technology Data Exchange (ETDEWEB)

    Zha, H.; Zhang, Z.

    1998-08-01

    The authors present a detailed analysis of matrices satisfying the so-called low-rank-plus-shift property in connection with the computation of their partial singular value decomposition. The application they have in mind is Latent Semantic Indexing for information retrieval where the term-document matrices generated from a text corpus approximately satisfy this property. The analysis is motivated by developing more efficient methods for computing and updating partial SVD of large term-document matrices and gaining deeper understanding of the behavior of the methods in the presence of noise.

  10. Substance Use Profiles of Urban American Indian Adolescents: A Latent Class Analysis.

    Science.gov (United States)

    Kulis, Stephen S; Jager, Justin; Ayers, Stephanie L; Lateef, Husain; Kiehne, Elizabeth

    2016-07-28

    A growing majority of American Indian adolescents now live in cities and are at high risk of early and problematic substance use and its negative health effects. This study used latent class analysis to empirically derive heterogeneous patterns of substance use among urban American Indian adolescents, examined demographic correlates of the resulting latent classes, and tested for differences among the latent classes in other risk behavior and prosocial outcomes. The study employed a representative sample of 8th, 10th, and 12th grade American Indian adolescents (n = 2,407) in public or charter schools in metropolitan areas of Arizona in 2012. Latent class analysis examined eight types of last 30 day substance use. Four latent classes emerged: a large group of "nonusers" (69%); a substantial minority using alcohol, tobacco, and/or marijuana [ATM] (17%); a smaller group of polysubstance users consuming, alcohol, tobacco, marijuana, other illicit drugs, and prescription or OTC drugs in combination (6%); and a "not alcohol" group reporting combinations of tobacco, marijuana, and prescription drug use, but rarely alcohol use (4%). The latent classes varied by age and grade level, but not by other demographic characteristics, and aligned in highly consistent patterns on other non-substance use outcomes. Polysubstance users reported the most problematic and nonusers the least problematic outcomes, with ATM and "not alcohol" users in the middle. Urban AI adolescent substance use occurs in three somewhat distinctive patterns of combinations of recent alcohol and drug consumption, covarying in systematic ways with other problematic risk behaviors and attitudes.

  11. Refining the Classification of Children with Selective Mutism: A Latent Profile Analysis

    Science.gov (United States)

    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…

  12. Further Examining Berry's Model: The Applicability of Latent Profile Analysis to Acculturation

    Science.gov (United States)

    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…

  13. Latent Profile Analysis to Determine the Typology of Disinhibited Eating Behaviors in Children and Adolescents

    Science.gov (United States)

    Vannucci, Anna; Tanofsky-Kraff, Marian; Crosby, Ross D.; Ranzenhofer, Lisa M.; Shomaker, Lauren B.; Field, Sara E.; Mooreville, Mira; Reina, Samantha A.; Kozlosky, Merel; Yanovski, Susan Z.; Yanovski, Jack A.

    2013-01-01

    Objective: We used latent profile analysis (LPA) to classify children and adolescents into subtypes based on the overlap of disinhibited eating behaviors--eating in the absence of hunger, emotional eating, and subjective and objective binge eating. Method: Participants were 411 youths (8-18 years) from the community who reported on their…

  14. Further Examining Berry's Model: The Applicability of Latent Profile Analysis to Acculturation

    Science.gov (United States)

    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…

  15. A Latent Profile Analysis of Math Achievement, Numerosity, and Math Anxiety in Twins

    Science.gov (United States)

    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…

  16. Occurence of internet addiction in a general population sample: A latent class analysis

    NARCIS (Netherlands)

    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

  17. Latent Class Analysis of Peer Conformity: Who Is Yielding to Pressure and Why?

    Science.gov (United States)

    Kosten, Paul A.; Scheier, Lawrence M.; Grenard, Jerry L.

    2013-01-01

    This study used latent class analysis to examine typologies of peer conformity in a community sample of middle school students. Students responded to 31 items assessing diverse facets of conformity dispositions. The most parsimonious model produced three qualitatively distinct classes that differed on the basis of conformity to recreational…

  18. Further Examining Berry's Model: The Applicability of Latent Profile Analysis to Acculturation

    Science.gov (United States)

    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…

  19. Latent Class Analysis of Peer Conformity: Who Is Yielding to Pressure and Why?

    Science.gov (United States)

    Kosten, Paul A.; Scheier, Lawrence M.; Grenard, Jerry L.

    2013-01-01

    This study used latent class analysis to examine typologies of peer conformity in a community sample of middle school students. Students responded to 31 items assessing diverse facets of conformity dispositions. The most parsimonious model produced three qualitatively distinct classes that differed on the basis of conformity to recreational…

  20. An Introduction to Latent Growth Models: Analysis of Repeated Measures Physical Performance Data

    Science.gov (United States)

    Park, Ilhyeok; Schutz, Robert W.

    2005-01-01

    The purpose of this paper is to introduce the Latent Growth Model (LGM) to researchers in exercise and sport science. Although the LGM has several merits over traditional analysis techniques in analyzing change and was first introduced almost 20 years ago, it is still underused in exercise and sport science research. This statistical model can be…

  1. Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

    Science.gov (United States)

    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.

  2. Exploring the Relationship between Autism Spectrum Disorder and Epilepsy Using Latent Class Cluster Analysis

    Science.gov (United States)

    Cuccaro, Michael L.; Tuchman, Roberto F.; Hamilton, Kara L.; Wright, Harry H.; Abramson, Ruth K.; Haines, Jonathan L.; Gilbert, John R.; Pericak-Vance, Margaret

    2012-01-01

    Epilepsy co-occurs frequently in autism spectrum disorders (ASD). Understanding this co-occurrence requires a better understanding of the ASD-epilepsy phenotype (or phenotypes). To address this, we conducted latent class cluster analysis (LCCA) on an ASD dataset (N = 577) which included 64 individuals with epilepsy. We identified a 5-cluster…

  3. Using Latent Class Analysis to Identify Academic and Behavioral Risk Status in Elementary Students

    Science.gov (United States)

    King, Kathleen R.; Lembke, Erica S.; Reinke, Wendy M.

    2016-01-01

    Identifying classes of children on the basis of academic and behavior risk may have important implications for the allocation of intervention resources within Response to Intervention (RTI) and Multi-Tiered System of Support (MTSS) models. Latent class analysis (LCA) was conducted with a sample of 517 third grade students. Fall screening scores in…

  4. Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

    Science.gov (United States)

    Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

    2016-12-27

    Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

  5. Remote sensing image segmentation using local sparse structure constrained latent low rank representation

    Science.gov (United States)

    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.

  6. A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

    Science.gov (United States)

    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.

  7. Comparing Latent Means Without Mean Structure Models: A Projection-Based Approach.

    Science.gov (United States)

    Deng, Lifang; Yuan, Ke-Hai

    2016-09-01

    The conventional setup for multi-group structural equation modeling requires a stringent condition of cross-group equality of intercepts before mean comparison with latent variables can be conducted. This article proposes a new setup that allows mean comparison without the need to estimate any mean structural model. By projecting the observed sample means onto the space of the common scores and the space orthogonal to that of the common scores, the new setup allows identifying and estimating the means of the common and specific factors, although, without replicate measures, variances of specific factors cannot be distinguished from those of measurement errors. Under the new setup, testing cross-group mean differences of the common scores is done independently from that of the specific factors. Such independent testing eliminates the requirement for cross-group equality of intercepts by the conventional setup in order to test cross-group equality of means of latent variables using chi-square-difference statistics. The most appealing piece of the new setup is a validity index for mean differences, defined as the percentage of the sum of the squared observed mean differences that is due to that of the mean differences of the common scores. By analyzing real data with two groups, the new setup is shown to offer more information than what is obtained under the conventional setup.

  8. Kraepelin Was Right: A Latent Class Analysis of Symptom Dimensions in Patients and Controls

    OpenAIRE

    Derks, Eske M.; Allardyce, Judith; Boks, Marco P; Vermunt, Jeroen K.; Hijman, Ron; Ophoff, Roel A

    2010-01-01

    Phenotypic heterogeneity within patients and controls may explain why the genetic variants contributing to schizophrenia risk explain only a fraction of the heritability. The aim of this study is to investigate quantitative and qualitative differences in psychosis symptoms in a sample including psychosis patients, their relatives, and community controls. We combined factor analysis and latent class analysis to analyze variation in Comprehensive Assessment of Symptoms and History lifetime-rate...

  9. Market segmentation through conjoint analysis using latent class models

    OpenAIRE

    Camilleri, Liberato; Azzopardi, Lara Marie; 29th European Simulation and Modelling Conference

    2011-01-01

    Conjoint Analysis is accepted by market researchers as a reliable and suitable instrument for measuring consumer preferences. The popularity of conjoint analysis hinges on the belief that it produces valid measurements of consumer preferences for the features of a product or service. It is the marketers’ methodology for assessing the impact of proposed actions on the market and finding out how buyers trade-off among competing products and suppliers. A popular application of conjoint analysis ...

  10. Mind Wandering and Online Learning: A Latent Variable Analysis

    Science.gov (United States)

    Hollis, R. Benjamin

    2013-01-01

    Thoughts drift in everyday life and in the classroom. The goal of this study was to investigate how often students reported off-task thinking while watching online lectures. These findings were related to working memory capacity, topic interest, and achievement goal orientations. Structural equation modeling was used to evaluate how all of these…

  11. The adolescent behavioral repertoire: its latent structure in the PACARDO region of Latin America.

    Science.gov (United States)

    Chen, Chuan-Yu; Dormitzer, Catherine M; Bejarano, Julio; Caris, Luis H; Bolivar Diaz, Jorge; Sanchez, Mauricio; Vittetoe, Kenneth; Anthony, James C

    2004-01-01

    In this study, the authors probed the latent structure of the adolescent behavioral repertoire (ABR) and estimated its sociodemographic correlates. The authors drew a nationally representative sample of 12,797 school-attending youth from the 7 countries in the PACARDO region of Latin America: Panama, Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, and the Dominican Republic. On the basis of the Behavioral Repertoire Self Report scale (Johanson, Duffy, and Anthony, 1996), the authors identified 5 primary dimensions, including religious behaviors, socializing, sports, home-based activities, and gender socialization activities. The authors found that the levels of involvement in these dimensions of the ABR varied across sociodemographic characteristics. The observed multidimensional structure of the ABR sets the stage for future research on adolescent health in relation to these behaviors and activities.

  12. A New Model of Urban Population Density Indicating Latent Fractal Structure

    CERN Document Server

    Chen, Yanguang

    2016-01-01

    Fractal structure of a system suggests the optimal way in which parts arranged or put together to form a whole. The ideas from fractals have a potential application to the researches on urban sustainable development. To characterize fractal cities, we need the measure of fractional dimension. However, if the fractal organization is concealed in the complex spatial distributions of geographical phenomena, the common methods of evaluating fractal parameter will be disabled. In this article, a new model is proposed to describe urban density and estimate fractal dimension of urban form. If urban density takes on quasi-fractal pattern or the self-similar pattern is hidden in the negative exponential distribution, the generalized gamma function may be employed to model the urban landscape and estimate its latent fractal dimension. As a case study, the method is applied to the city of Hangzhou, China. The results show that urban form evolves from simple to complex structure with time.

  13. Men and women are from Earth: examining the latent structure of gender.

    Science.gov (United States)

    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.

  14. Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

    Science.gov (United States)

    DiStefano, Christine; Kamphaus, R. W.

    2006-01-01

    Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

  15. Subtypes of physical frailty: Latent class analysis and associations with clinical characteristics and outcomes

    Science.gov (United States)

    Liu, Li-Kuo; Guo, Chao-Yu; Lee, Wei-Ju; Chen, Liang-Yu; Hwang, An-Chun; Lin, Ming-Hsien; Peng, Li-Ning; Chen, Liang-Kung; Liang, Kung-Yee

    2017-01-01

    Frailty is a well-recognized geriatric syndrome with various definitions and conceptual frameworks. This study aimed to use latent class analysis to discover potential subtypes of pre-frail and frail older people. Data from the I-Lan Longitudinal Aging Study (ILAS), a community-based cohort study was used for analysis. Latent class analysis was applied to characterize classes or subgroups with different frailty phenotypes among ILAS participants targeting older adults aged 65 and above, capable of completing a 6-meter walk, without severe major or life threatening diseases, and not institutionalized. Latent class analysis identified three distinct subgroups with different frailty phenotypes: non-mobility-type (weight loss and exhaustion), mobility-type frailty (slowness and weakness), and low physical activity. Comparing these groups with the robust group, people with mobility-type frailty had poorer body composition, worse bone health, poorer cognitive function, lower survival (hazard ratio: 6.82, p = 0.019), and poorer overall health outcomes (hazard ratio: 1.67, p = 0.040). People in the non-mobility-type group had poorer bone health and more metabolic serum abnormalities. In conclusion, mobility-type frailty was a better predictor of adverse outcomes. However, further investigation is needed to evaluate how these phenotypic subgroups may help in predicting prognosis or in developing interventions. PMID:28397814

  16. A latent profile analysis of the Five Factor Model of personality: Modeling trait interactions.

    Science.gov (United States)

    Merz, Erin L; Roesch, Scott C

    2011-12-01

    Interactions among the dimensions of the Five Factor Model (FFM) have not typically been evaluated in mental health research, with the extant literature focusing on bivariate relationships with psychological constructs of interest. This study used latent profile analysis to mimic higher-order interactions to identify homogenous personality profiles using the FFM, and also examined relationships between resultant profiles and affect, self-esteem, depression, anxiety, and coping efficacy. Participants (N = 371) completed self-report and daily diary questionnaires. A 3-profile solution provided the best fit to the data; the profiles were characterized as well-adjusted, reserved, and excitable. The well-adjusted group reported better psychological functioning in validation analyses. The reserved and excitable groups differed on anxiety, with the excitable group reporting generally higher anxiety than the reserved group. Latent profile analysis may be a parsimonious way to model personality heterogeneity.

  17. Latent morpho-semantic analysis : multilingual information retrieval with character n-grams and mutual information.

    Energy Technology Data Exchange (ETDEWEB)

    Bader, Brett William; Chew, Peter A.; Abdelali, Ahmed (New Mexico State University)

    2008-08-01

    We describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related previous approaches such as Latent Semantic Analysis (LSA). LMSA has an important theoretical advantage over LSA: it combines well-known techniques in a novel way to break the terms of LSA down into units which correspond more closely to morphemes. Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. We show through empirical results that the theoretical advantages of LMSA can translate into significant gains in precision in multilingual information retrieval tests. These gains are not matched either when a standard stemmer is used with LSA, or when terms are indiscriminately broken down into n-grams.

  18. Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

    OpenAIRE

    Rita Ismayilova; Emilya Nasirova; Colleen Hanou; Rivard, Robert G.; Bautista, Christian T.

    2014-01-01

    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 mo...

  19. Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

    Science.gov (United States)

    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.

  20. Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining

    Science.gov (United States)

    De Angelis, Marco; Marín Puchades, Víctor; Fraboni, Federico; Pietrantoni, Luca

    2017-01-01

    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. PMID:28158296

  1. Primary Energy Efficiency Analysis of Different Separate Sensible and Latent Cooling Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Abdelaziz, Omar [ORNL

    2015-01-01

    Separate Sensible and Latent cooling (SSLC) has been discussed in open literature as means to improve air conditioning system efficiency. The main benefit of SSLC is that it enables heat source optimization for the different forms of loads, sensible vs. latent, and as such maximizes the cycle efficiency. In this paper I use a thermodynamic analysis tool in order to analyse the performance of various SSLC technologies including: multi-evaporators two stage compression system, vapour compression system with heat activated desiccant dehumidification, and integrated vapour compression with desiccant dehumidification. A primary coefficient of performance is defined and used to judge the performance of the different SSLC technologies at the design conditions. Results showed the trade-off in performance for different sensible heat factor and regeneration temperatures.

  2. Primary Energy Efficiency Analysis of Different Separate Sensible and Latent Cooling Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Abdelaziz, Omar [ORNL

    2015-01-01

    Separate Sensible and Latent cooling (SSLC) has been discussed in open literature as means to improve air conditioning system efficiency. The main benefit of SSLC is that it enables heat source optimization for the different forms of loads, sensible vs. latent, and as such maximizes the cycle efficiency. In this paper I use a thermodynamic analysis tool in order to analyse the performance of various SSLC technologies including: multi-evaporators two stage compression system, vapour compression system with heat activated desiccant dehumidification, and integrated vapour compression with desiccant dehumidification. A primary coefficient of performance is defined and used to judge the performance of the different SSLC technologies at the design conditions. Results showed the trade-off in performance for different sensible heat factor and regeneration temperatures.

  3. The impact of latent confounders in directed network analysis in neuroscience.

    Science.gov (United States)

    Ramb, Rebecca; Eichler, Michael; Ing, Alex; Thiel, Marco; Weiller, Cornelius; Grebogi, Celso; Schwarzbauer, Christian; Timmer, Jens; Schelter, Björn

    2013-08-28

    In the analysis of neuroscience data, the identification of task-related causal relationships between various areas of the brain gives insights about the network of physiological pathways that are active during the task. One increasingly used approach to identify causal connectivity uses the concept of Granger causality that exploits predictability of activity in one region by past activity in other regions of the brain. Owing to the complexity of the data, selecting components for the analysis of causality as a preprocessing step has to be performed. This includes predetermined-and often arbitrary-exclusion of information. Therefore, the system is confounded by latent sources. In this paper, the effect of latent confounders is demonstrated, and paths of influence among three components are studied. While methods for analysing Granger causality are commonly based on linear vector autoregressive models, the effects of latent confounders are expected to be present also in nonlinear systems. Therefore, all analyses are also performed for a simulated nonlinear system and discussed with regard to applications in neuroscience.

  4. Age-related change in executive function: developmental trends and a latent variable analysis.

    Science.gov (United States)

    Huizinga, Mariëtte; Dolan, Conor V; van der Molen, Maurits W

    2006-01-01

    This study examined the developmental trajectories of three frequently postulated executive function (EF) components, Working Memory, Shifting, and Inhibition of responses, and their relation to performance on standard, but complex, neuropsychological EF tasks, the Wisconsin Card Sorting Task (WCST), and the Tower of London (ToL). Participants in four age groups (7-, 11-, 15-, and 21-year olds) carried out nine basic experimental tasks (three tasks for each EF), the WCST, and the ToL. Analyses were done in two steps: (1) analyses of (co)variance to examine developmental trends in individual EF tasks while correcting for basic processing speed, (2) confirmatory factor analysis to extract latent variables from the nine basic EF tasks, and to explain variance in the performance on WCST and ToL, using these latent variables. Analyses of (co)variance revealed a continuation of EF development into adolescence. Confirmatory factor analysis yielded two common factors: Working Memory and Shifting. However, the variables assumed to tap Inhibition proved unrelated. At a latent level, again correcting for basic processing speed, the development of Shifting was seen to continue into adolescence, while Working Memory continued to develop into young-adulthood. Regression analyses revealed that Working Memory contributed most strongly to WCST performance in all age groups. These results suggest that EF component processes develop at different rates, and that it is important to recognize both the unity and diversity of EF component processes in studying the development of EF.

  5. Multi-view methods for protein structure comparison using latent dirichlet allocation.

    Science.gov (United States)

    Shivashankar, S; Srivathsan, S; Ravindran, B; Tendulkar, Ashish V

    2011-07-01

    With rapidly expanding protein structure databases, efficiently retrieving structures similar to a given protein is an important problem. It involves two major issues: (i) effective protein structure representation that captures inherent relationship between fragments and facilitates efficient comparison between the structures and (ii) effective framework to address different retrieval requirements. Recently, researchers proposed vector space model of proteins using bag of fragments representation (FragBag), which corresponds to the basic information retrieval model. In this article, we propose an improved representation of protein structures using latent dirichlet allocation topic model. Another important requirement is to retrieve proteins, whether they are either close or remote homologs. In order to meet diverse objectives, we propose multi-viewpoint based framework that combines multiple representations and retrieval techniques. We compare the proposed representation and retrieval framework on the benchmark dataset developed by Kolodny and co-workers. The results indicate that the proposed techniques outperform state-of-the-art methods. http://www.cse.iitm.ac.in/~ashishvt/research/protein-lda/. ashishvt@cse.iitm.ac.in.

  6. Peculiarities of latent track etching in SiO2/Si structures irradiated with Ar, Kr and Xe ions

    Science.gov (United States)

    Al'zhanova, A.; Dauletbekova, A.; Komarov, F.; Vlasukova, L.; Yuvchenko, V.; Akilbekov, A.; Zdorovets, M.

    2016-05-01

    The process of latent track etching in SiO2/Si structures irradiated with 40Ar (38 MeV), 84Kr (59 MeV) and 132Xe (133 and 200 MeV) ions has been investigated. The experimental results of SiO2 etching in a hydrofluoric acid solution have been compared with the results of computer simulation based on the thermal spike model. It has been confirmed that the formation of a molten region along the swift ion trajectory with minimum radius of 3 nm can serve as a theoretical criterion for the reproducible latent track etching tracks in SiO2.

  7. A Personality-Based Latent Class Analysis of Emerging Adult Gamblers.

    Science.gov (United States)

    Tackett, Jennifer L; Rodriguez, Lindsey M; Rinker, Dipali V; Neighbors, Clayton

    2015-12-01

    Increases in access to gambling venues have been accompanied by increased gambling behavior among young adults. The present research examined associations among Five Factor Model personality traits, motives for gambling, and gambling behavior and problems using latent class analysis. College students (N = 220) completed online measures of personality and gambling behavior as part of a larger intervention trial. Agreeableness and conscientiousness were negatively associated with indicators of gambling behavior. Low agreeableness and high neuroticism were associated with gambling-specific motives, particularly for less frequently endorsed motives. Personality-based latent class analyses of emerging adult gamblers revealed support for three distinct groups reflecting a resilient personality group, a normative personality group, and a vulnerable personality group, which were further differentiated by gambling behaviors and gambling-specific motives. Associations between personality traits and gambling-specific motives highlight potential heterogeneity among college students who gamble. Together, findings suggest that the correlational and latent class-based analyses, as well as the personality and motivation analyses, present complementary information with respect to the attributes of college student gamblers. Implications and future research directions are discussed.

  8. A Taxometric Investigation of the Latent Structure of Worry: Dimensionality and Associations with Depression, Anxiety, and Stress

    Science.gov (United States)

    Olatunji, Bunmi O.; Broman-Fulks, Joshua J.; Bergman, Shawn M.; Green, Bradley A.; Zlomke, Kimberly R.

    2010-01-01

    Worry has been described as a core feature of several disorders, particularly generalized anxiety disorder (GAD). The present study examined the latent structure of worry by applying 3 taxometric procedures (MAXEIG, MAMBAC, and L-Mode) to data collected from 2 large samples. Worry in the first sample (Study 1) of community participants (n = 1,355)…

  9. A Taxometric Investigation of the Latent Structure of Worry: Dimensionality and Associations with Depression, Anxiety, and Stress

    Science.gov (United States)

    Olatunji, Bunmi O.; Broman-Fulks, Joshua J.; Bergman, Shawn M.; Green, Bradley A.; Zlomke, Kimberly R.

    2010-01-01

    Worry has been described as a core feature of several disorders, particularly generalized anxiety disorder (GAD). The present study examined the latent structure of worry by applying 3 taxometric procedures (MAXEIG, MAMBAC, and L-Mode) to data collected from 2 large samples. Worry in the first sample (Study 1) of community participants (n = 1,355)…

  10. Doubly-Latent Models of School Contextual Effects: Integrating Multilevel and Structural Equation Approaches to Control Measurement and Sampling Error

    Science.gov (United States)

    Marsh, Herbert W.; Ludtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthen, Bengt; Nagengast, Benjamin

    2009-01-01

    This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2)…

  11. Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

    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...... 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...

  12. Structured Functional Principal Component Analysis

    Science.gov (United States)

    Shou, Haochang; Zipunnikov, Vadim; Crainiceanu, Ciprian M.; Greven, Sonja

    2015-01-01

    Summary Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for high-dimensional data. Methods are used in applications including high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity during sleep. PMID:25327216

  13. Longitudinal analysis of latent classes of psychopathology and patterns of class migration in survivors of severe injury.

    Science.gov (United States)

    Forbes, David; Nickerson, Angela; Alkemade, Nathan; Bryant, Richard A; Creamer, Mark; Silove, Derrick; McFarlane, Alexander C; Van Hooff, Miranda; Fletcher, Susan L; O'Donnell, Meaghan

    2015-09-01

    Little research to date has explored the typologies of psychopathology following trauma, beyond development of particular diagnoses such as posttraumatic stress disorder (PTSD). The objective of this study was to determine the longitudinal patterns of these typologies, especially the movement of persons across clusters of psychopathology. In this 6-year longitudinal study, 1,167 hospitalized severe injury patients who were recruited between April 2004-February 2006 were analyzed, with repeated measures at baseline, 3 months, 12 months, and 72 months after injury. All patients met the DSM-IV criterion A1 for PTSD. Structured clinical interviews were used to assess psychiatric disorders at each follow-up point. Latent class analysis and latent transition analysis were applied to assess clusters of individuals determined by psychopathology. The Mini International Neuropsychiatric Interview (MINI) and Clinician-Administered PTSD Scale (CAPS) were employed to complete diagnoses. Four latent classes were identified at each time point: (1) Alcohol/Depression class (3 months, 2.1%; 12 months, 1.3%; and 72 months, 1.1%), (2) Alcohol class (3 months, 3.3%; 12 months, 3.7%; and 72 months, 5.4%), (3) PTSD/Depression class (3 months, 10.3%; 12 months, 11.5%; and 72 months, 6.4%), and (4) No Disorder class (3 months, 84.2%; 12 months, 83.5%; and 72 months, 87.1%). Latent transition analyses conducted across the 2 transition points (12 months and 72 months) found consistently high levels of stability in the No Disorder class (90.9%, 93.0%, respectively) but lower and reducing levels of consistency in the PTSD/Depression class (81.3%, 46.6%), the Alcohol/Depression class (59.7%, 21.5%), and the Alcohol class (61.0%, 36.5%), demonstrating high levels of between-class migration. Despite the array of psychiatric disorders that may develop following severe injury, a 4-class model best described the data with excellent classification certainty. The high levels of migration across

  14. Experimental analysis on classification of unmanned aerial vehicle images using the probabilistic latent semantic analysis

    Science.gov (United States)

    Yi, Wenbin; Tang, Hong

    2009-10-01

    In this paper, we present a novel algorithm to classify UAV images through the image annotation which is a semi-supervised method. During the annotation process, we first divide whole image into different sizes of blocks and generate suitable visual words which are the K-means clustering centers or just pixels in small size image block. Then, given a set of image blocks for each semantic concept as training data, learning is based on the Probabilistic Latent Semantic Analysis (PLSA). The probability distributions of visual words in every document can be learned through the PLSA model. The labeling of every document (image block) is done by computing the similarity of its feature distribution to the distribution of the training documents with the Kullback-Leibler (K-L) divergence. Finally, the classification of the UAV images will be done by combining all the image blocks in every block size. The UAV images using in our experiments was acquired during Sichuan earthquake in 2008. The results show that smaller size block image will get better classification results.

  15. Oral health status in older adults with social security in Mexico City: Latent class analysis.

    Science.gov (United States)

    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.

  16. Oral health status in older adults with social security in Mexico City: Latent class analysis

    Science.gov (United States)

    Heredia-Ponce, Erika; Cruz-Hervert, Pablo; Juárez-Cedillo, Teresa; Cárdenas-Bahena, Ángel; García-Peña, Carmen

    2014-01-01

    Objective: To explore the oral health status through a latent class analysis in elderly social security beneficiaries from Southwest Mexico City. Material and Methods: 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. Results: 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. Conclusion: 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. PMID:24596632

  17. A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.

    Science.gov (United States)

    Yu, Rongjie; Wang, Xuesong; Abdel-Aty, Mohamed

    2017-02-07

    Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed.

  18. 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

  19. 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.

  20. 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.

  1. Latent Class Analysis of Incomplete Data via an Entropy-Based Criterion.

    Science.gov (United States)

    Larose, Chantal; Harel, Ofer; Kordas, Katarzyna; Dey, Dipak K

    2016-09-01

    Latent class analysis is used to group categorical data into classes via a probability model. Model selection criteria then judge how well the model fits the data. When addressing incomplete data, the current methodology restricts the imputation to a single, pre-specified number of classes. We seek to develop an entropy-based model selection criterion that does not restrict the imputation to one number of clusters. Simulations show the new criterion performing well against the current standards of AIC and BIC, while a family studies application demonstrates how the criterion provides more detailed and useful results than AIC and BIC.

  2. 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.

  3. 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

  4. Rasch analysis of the orientation log and reconsideration of the latent construct during inpatient rehabilitation.

    Science.gov (United States)

    Kean, Jacob; Abell, Malene; Malec, James F; Trzepacz, Paula T

    2011-01-01

    To investigate the measurement properties of the Orientation Log (O-Log) and a hybrid scale using Rasch analysis techniques and to explore the relations between the items of the 2 scales and the latent linear construct modeled in the Rasch analysis. Calibration of data collected weekly during inpatient rehabilitation. Ninety patients admitted for rehabilitation after traumatic brain injury. Measure reliability/construct validity of the O-Log was too low to justify restructuring of disordered rating scales, but the broader set of items in the hybrid scale demonstrated good measure reliability/construct validity prior to and following rating scale restructuring. Both O-Log and hybrid measures demonstrated statistical fit with the linear latent construct, suggesting that orientation and memory are only a subset of symptoms in a broader syndrome. Posttraumatic amnesia is by definition a proxy measure of a broader syndrome during early recovery and not a measure of the syndrome itself. The results suggest that the O-Log cannot reliably measure progress during early recovery. Furthermore, the analysis suggests that the construct of posttraumatic amnesia is too narrow and should be revisited to improve monitoring of recovery and prognostic estimation after brain injury.

  5. Estimating Patient’s Health State Using Latent Structure Inferred from Clinical Time Series and Text

    Science.gov (United States)

    Zalewski, Aaron; Long, William; Johnson, Alistair E. W.; Mark, Roger G.; Lehman, Li-wei H.

    2017-01-01

    Modern intensive care units (ICUs) collect large volumes of data in monitoring critically ill patients. Clinicians in the ICUs face the challenge of interpreting large volumes of high-dimensional data to diagnose and treat patients. In this work, we explore the use of Hierarchical Dirichlet Processes (HDP) as a Bayesian nonparametric framework to infer patients’ states of health by combining multiple sources of data. In particular, we employ HDP to combine clinical time series and text from the nursing progress notes in a probabilistic topic modeling framework for patient risk stratification. Given a patient cohort, we use HDP to infer latent “topics” shared across multimodal patient data from the entire cohort. Each topic is modeled as a multinomial distribution over a vocabulary of codewords, defined over heterogeneous data sources. We evaluate the clinical utility of the learned topic structure using the first 24-hour ICU data from over 17,000 adult patients in the MIMIC-II database to estimate patients’ risks of in-hospital mortality. Our results demonstrate that our approach provides a viable framework for combining different data modalities to model patient’s states of health, and can potentially be used to generate alerts to identify patients at high risk of hospital mortality. PMID:28630952

  6. Pharmacoepidemiological characterization of psychotropic drugs consumption using a latent class analysis.

    Science.gov (United States)

    Wainstein, Laura; Victorri-Vigneau, Caroline; Sébille, Véronique; Hardouin, Jean-Benoît; Feuillet, Fanny; Pivette, Jacques; Chaslerie, Anicet; Jolliet, Pascale

    2011-01-01

    France has one of the highest recorded rates of psychotropic use of drugs compared with other European countries, especially for anxiolytics, hypnotics and antidepressants. The aim of this study was to characterize the use of three psychotropic drugs among the most prescribed in France (bromazepam, paroxetine, zolpidem) using reimbursement databases in real-life conditions. Individuals from a region affiliated to the French General Health Insurance Scheme, who had received at least two dispensings of bromazepam, paroxetine or zolpidem reimbursed between 1 January and 30 June 2008, were included. We used a latent class analysis to identify different subgroups of users for these three psychotropic drugs. A total of 40,644 patients were included for bromazepam, 36,264 for zolpidem and 31,235 for paroxetine. Using latent class analysis, four clinical subtypes of users of bromazepam and zolpidem were identified: nonproblematic users, at-risk users, users with a probable mental disorder and compulsive users. Three subgroups were identified for paroxetine that differed rather by the prescription patterns. Users of anxiolytics and hypnotics with at-risk behaviours represented a significant proportion in the studied population. This original method could be extended to other prescription databases to identify populations at risk of abuse or dependence to psychotropic drugs.

  7. Latent profile analysis and comorbidity in a sample of individuals with compulsive buying disorder.

    Science.gov (United States)

    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.

  8. Staff nurse commitment, work relationships, and turnover intentions: a latent profile analysis.

    Science.gov (United States)

    Gellatly, Ian R; Cowden, Tracy L; Cummings, Greta G

    2014-01-01

    The three-component model of organization commitment has typically been studied using a variable-centered rather than a person-centered approach, preventing a more complete understanding of how these forms of commitment are felt and expressed as a whole. Latent profile analysis was used to identify qualitatively distinct categories or profiles of staff nurses' commitment. Then, associations of the profiles with perceived work unit relations and turnover intentions were examined. Three hundred thirty-six registered nurses provided data on affective, normative, and continuance commitment, perceived work unit relations, and turnover intentions. Latent profile analysis of the nurses' commitment scores revealed six distinct profile groups. Work unit relations and turnover intentions were compared in the six profile-defined groups. Staff nurses with profiles characterized by high affective commitment and/or high normative commitment in relation to other components experienced stronger work unit relations and reported lower turnover intentions. Profiles characterized by high continuance commitment relative to other components or by low overall commitment experienced poorer work unit relations, and the turnover risk was higher. High continuance commitment in combination with high affective and normative commitment was experienced differently than high continuance commitment in combination with low affective and normative commitment. Healthcare organizations often foster commitment by using continuance commitment-enhancing strategies (e.g., offer high salaries and attractive benefits) that may inadvertently introduce behavioral risk. This work suggests the importance of changing the context in which continuance commitment occurs by strengthening the other two components.

  9. Modeling Subducting Slabs: Structural Variations due to Thermal Models, Latent Heat Feedback, and Thermal Parameter

    Science.gov (United States)

    Marton, F. C.

    2001-12-01

    The thermal, mineralogical, and buoyancy structures of thermal-kinetic models of subducting slabs are highly dependent upon a number of parameters, especially if the metastable persistence of olivine in the transition zone is investigated. The choice of starting thermal model for the lithosphere, whether a cooling halfspace (HS) or plate model, can have a significant effect, resulting in metastable wedges of olivine that differ in size by up to two to three times for high values of the thermal parameter (ǎrphi). Moreover, as ǎrphi is the product of the age of the lithosphere at the trench, convergence rate, and dip angle, slabs with similar ǎrphis can show great variations in structures as these constituents change. This is especially true for old lithosphere, as the lithosphere continually cools and thickens with age for HS models, but plate models, with parameters from Parson and Sclater [1977] (PS) or Stein and Stein [1992] (GDH1), achieve a thermal steady-state and constant thickness in about 70 My. In addition, the latent heats (q) of the phase transformations of the Mg2SiO4 polymorphs can also have significant effects in the slabs. Including q feedback in models raises the temperature and reduces the extent of metastable olivine, causing the sizes of the metastable wedges to vary by factors of up to two times. The effects of the choice of thermal model, inclusion and non-inclusion of q feedback, and variations in the constituents of ǎrphi are investigated for several model slabs.

  10. A Latent Class Analysis of Behavioral and Psychosocial Dimensions of Adolescent Sexuality: Exploring Race Differences.

    Science.gov (United States)

    Thorsen, Maggie L

    2016-12-16

    Adolescent sexuality is a multidimensional concept involving sexual behavior as well as aspects of youth's sexual self-concept and sexual socialization. The current study used latent class analysis (LCA) to examine patterns of adolescent sexuality, with data from a nationally representative sample of youth (Add Health; n = 13,447), incorporating information on behavioral and psychosocial dimensions of adolescent sexual experiences. LCA results highlighted that youth may exhibit similar sexual behaviors but vary on psychosocial dimensions, including sexual self-efficacy, knowledge, and views about sex. Sociodemographic characteristics, family factors, mental health, and substance use emerged as predictors of membership into different latent classes of sexuality. Given persistent racial differences in sexual outcomes and sexually transmitted infection (STI) rates, the current study also examined how adolescent patterns of sexuality may help mediate racial differences in sexual outcomes by young adulthood. Results suggested that racial differences in adolescent patterns of sexuality help mediate racial differences in the number of sexual partners by young adulthood but not differences in STI diagnosis. Findings highlight the need for research on multiple aspects of adolescent sexuality to understand linkages with later outcomes and group differences.

  11. A Person-Centered Examination of Adolescent Religiosity Using Latent Class Analysis

    Science.gov (United States)

    Pearce, Lisa D.; Foster, E. Michael; Hardie, Jessica Halliday

    2013-01-01

    Empirical studies of religion’s role in society, especially those focused on individuals and analyzing survey data, conceptualize and measure religiosity on a single measure or a summary index of multiple measures. Other concepts, such as “lived religion,” “believing without belonging,” or “fuzzy fidelity,” emphasize what scholars have noted for decades: humans are rarely consistently low, medium, or high across dimensions of religiosity including institutional involvement, private practice, salience, or belief. A method with great promise for identifying population patterns in how individuals combine types and levels of belief, practice, and personal religious salience is latent class analysis. In this paper, we use data from the first wave of the National Study of Youth and Religion’s telephone survey to discuss how to select indicators of religiosity in an informed manner, as well as the implications of the number and types of indicators used for model fit. We identify five latent classes of religiosity among adolescents in the United States and their socio-demographic correlates. Our findings highlight the value of a person-centered approach to understanding how religion is lived by American adolescents. PMID:24043905

  12. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

    Science.gov (United States)

    Han, Fang; Liu, Han

    2016-01-01

    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.

  13. Job satisfaction among Australian doctors: the use of latent class analysis.

    Science.gov (United States)

    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.

  14. Use of Individual-level Covariates to Improve Latent Class Analysis of Trypanosoma Cruzi Diagnostic Tests.

    Science.gov (United States)

    Tustin, Aaron W; Small, Dylan S; Delgado, Stephen; Neyra, Ricardo Castillo; Verastegui, Manuela R; Ancca Juárez, Jenny M; Quispe Machaca, Víctor R; Gilman, Robert H; Bern, Caryn; Levy, Michael Z

    2012-08-01

    Statistical methods such as latent class analysis can estimate the sensitivity and specificity of diagnostic tests when no perfect reference test exists. Traditional latent class methods assume a constant disease prevalence in one or more tested populations. When the risk of disease varies in a known way, these models fail to take advantage of additional information that can be obtained by measuring risk factors at the level of the individual. We show that by incorporating complex field-based epidemiologic data, in which the disease prevalence varies as a continuous function of individual-level covariates, our model produces more accurate sensitivity and specificity estimates than previous methods. We apply this technique to a simulated population and to actual Chagas disease test data from a community near Arequipa, Peru. Results from our model estimate that the first-line enzyme-linked immunosorbent assay has a sensitivity of 78% (95% CI: 62-100%) and a specificity of 100% (95% CI: 99-100%). The confirmatory immunofluorescence assay is estimated to be 73% sensitive (95% CI: 65-81%) and 99% specific (95% CI: 96-100%).

  15. The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

    Science.gov (United States)

    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.

  16. A Latent Class Analysis of Smokeless Tobacco Use in the United States.

    Science.gov (United States)

    Fu, Qiang; Vaughn, Michael G

    2016-08-01

    While there has been an escalating trend in the number of smokeless tobacco uses, mainly snuff, in the United States, it is unclear whether smokeless tobacco users are a homogenous class. The present investigation examines this question and identifies subtypes of smokeless tobacco users in order to better understand the characteristics of these individuals and guide appropriate intervention. Data on smokeless tobacco users (N = 2504) derived from the National Epidemiologic Survey on Alcohol and Related Conditions was employed. A range of antisocial behaviors, from reflecting non-violent deviant acts, irresponsibility, and a disengaged lifestyle, to aggression and violence were used to estimate the number of subtypes of smokeless tobacco users using latent class analysis. Four latent classes emerged: Normative Class (50.2 %), Deviant Class (21.9 %), Disengaging Class (17.2 %), and Antisocial Class (10.5 %). Logistic regression shows that major depression, alcohol use disorder, and marijuana use disorder were associated with Deviant Class (OR's from 2.0 to 10.5). The same array of psychiatric disorders and general anxiety disorder were associated with greater odds of membership in the Disengaging Class (OR's from 2.6 to 7.4). Aforementioned psychiatric disorders and illicit drug use disorder were associated with the Antisocial Class (OR's from 3.8 to 38.1). Findings indicate that smokeless tobacco users are a heterogeneous population that may benefit from differential intervention strategies.

  17. Clustering and combining pattern of metabolic syndrome components among Iranian population with latent class analysis

    Science.gov (United States)

    Abbasi-Ghahramanloo, Abbas; Soltani, Sepideh; Gholami, Ali; Erfani, Mohammadreza; Yosaee, Somayeh

    2016-01-01

    Background: Metabolic syndrome (MetS), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. The aim of this study was to identify the subgroups of participants in a study on the basis of MetS components. Methods: The cross-sectional study took place in the districts related to Tehran University of Medical Sciences. The randomly selected sample consists of 415 subjects. All participants provided written informed consent. Latent class analysis was performed to achieve the study’s objectives. Analyses were conducted by using proc LCA in SAS 9.2 software. Results: Except systolic and diastolic blood pressure, the prevalence of all MetS components is common in female than male. Four latent classes were identified: (a) non MetS, (b) low risk, (c) high risk, and (d) MetS. Notably, 24.2% and 1.3% of the subjects were in the high risk and MetS classes respectively. Conclusion: Most of the study participants were identified as high risk and MetS. Design and implementation of preventive interventions for this segment of the population are necessary. PMID:28210610

  18. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

    Science.gov (United States)

    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.

  19. Risk-taking behaviors and subgrouping of college students: a latent class analysis.

    Science.gov (United States)

    Mohammadpoorasl, Asghar; Ghahramanloo, Abbas Abbasi; Allahverdipour, Hamid

    2013-11-01

    Risk-taking behaviors have negative consequences on adolescent and young adult's health. The aim of this study was to identify the subgroups of college students on the basis of risk-taking behaviors and to assess the role of demographic characteristics, religious beliefs, and parental support on membership of specific subgroup. The cross-sectional study took place in Tabriz (northwest of Iran) in April and May of 2011. The randomly selected sample consisted of 1,837 college students. A survey questionnaire was used to collect data. Latent class analysis was performed to achieve the study's objectives. Four latent classes were identified: (a) low risk, (b) cigarette and hookah smoker, (c) sexual and drinking risk-takers (for males)/sexual risk takers (for females), and (d) high risk. Notably, 13.3% of the males and 4.3% of the females were in the high-risk class. The results identified evidence of protective influence of familial support and religiosity on risky behaviors. A fair number of college students, males in particular, were identified as high risk-takers. Design and implementation of preventive interventions for this segment of the population are necessary. Higher level of familial support and religiosity may serve as preventive factors in risk-taking behaviors.

  20. Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis

    DEFF Research Database (Denmark)

    Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena

    2014-01-01

    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...

  1. Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis

    Science.gov (United States)

    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.

  2. Dissociative Experiences are Associated with Obsessive-Compulsive Symptoms in a Non-clinical Sample: A Latent Profile Analysis

    Science.gov (United States)

    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

  3. Structural Equation Models of Latent Interactions: Evaluation of Alternative Estimation Strategies and Indicator Construction

    Science.gov (United States)

    Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai

    2004-01-01

    Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches-unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The…

  4. Investigation of the Latent Structure for the Learning and Study Strategies Inventory

    Science.gov (United States)

    Finch, W. Holmes; Cassady, Jerrell C.; Jones, James A.

    2016-01-01

    The Learning and Study Strategies Inventory (LASSI) is a very popular tool for measuring the learning and study strategies of high school and college students. Prior research with the LASSI has supported the originally proposed model with three latent traits, with minor variations among the contributing subtests contributing to those traits.…

  5. 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.

  6. Discrete subgroups of adolescents diagnosed with borderline personality disorder: a latent class analysis of personality features.

    Science.gov (United States)

    Ramos, Vera; Canta, Guilherme; de Castro, Filipa; Leal, Isabel

    2014-08-01

    Research suggests that borderline personality disorder (BPD) can be diagnosed in adolescents and is marked by considerable heterogeneity. This study aimed to identify personality features characterizing adolescents with BPD and possible meaningful patterns of heterogeneity that could lead to personality subgroups. The authors analyzed data on 60 adolescents, ages 15 to 18 years, who met DSM criteria for a BPD diagnosis. The authors used latent class analysis (LCA) to identify subgroups based on the personality pattern scales from the Millon Adolescent Clinical Inventory (MACI). LCA indicated that the best-fitting solution was a two-class model, identifying two discrete subgroups of BPD adolescents that were described as internalizing and externalizing. The subgroups were then compared on clinical and sociodemographic variables, measures of personality dimensions, DSM BPD criteria, and perception of attachment styles. Adolescents with a BPD diagnosis constitute a heterogeneous group and vary meaningfully on personality features that can have clinical implications for treatment.

  7. Identifying classes of persons with mild intellectual disability or borderline intellectual functioning: a latent class analysis.

    Science.gov (United States)

    Nouwens, Peter J G; Lucas, Rosanne; Smulders, Nienke B M; Embregts, Petri J C M; van Nieuwenhuizen, Chijs

    2017-07-17

    Persons with mild intellectual disability or borderline intellectual functioning are often studied as a single group with similar characteristics. However, there are indications that differences exist within this population. Therefore, the aim of this study was to identify classes of persons with mild intellectual disability or borderline intellectual functioning and to examine whether these classes are related to individual and/or environmental characteristics. Latent class analysis was performed using file data of 250 eligible participants with a mean age of 26.1 (SD 13.8, range 3-70) years. Five distinct classes of persons with mild intellectual disability or borderline intellectual functioning were found. These classes significantly differed in individual and environmental characteristics. For example, persons with a mild intellectual disability experienced fewer problems than those with borderline intellectual disability. The identification of five classes implies that a differentiated approach is required towards persons with mild intellectual disability or borderline intellectual functioning.

  8. Variation in verbal fluency: a latent variable analysis of clustering, switching, and overall performance.

    Science.gov (United States)

    Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A

    2011-03-01

    Verbal fluency tasks have long been used to assess and estimate group and individual differences in executive functioning in both cognitive and neuropsychological research domains. Despite their ubiquity, however, the specific component processes important for success in these tasks have remained elusive. The current work sought to reveal these various components and their respective roles in determining performance in fluency tasks using latent variable analysis. Two types of verbal fluency (semantic and letter) were compared along with several cognitive constructs of interest (working memory capacity, inhibition, vocabulary size, and processing speed) in order to determine which constructs are necessary for performance in these tasks. The results are discussed within the context of a two-stage cyclical search process in which participants first search for higher order categories and then search for specific items within these categories.

  9. Computerizing reading training: evaluation of a latent semantic analysis space for science text.

    Science.gov (United States)

    Kurby, Christopher A; Wiemer-Hastings, Katja; Ganduri, Nagasai; Magliano, Joseph P; Millis, Keith K; McNamara, Danielle S

    2003-05-01

    The effectiveness of a domain-specific latent semantic analysis (LSA) in assessing reading strategies was examined. Students were given self-explanation reading training (SERT) and asked to think aloud after each sentence in a science text. Novice and expert human raters and two LSA spaces (general reading, science) rated the similarity of each think-aloud protocol to benchmarks representing three different reading strategies (minimal, local, and global). The science LSA space correlated highly with human judgments, and more highly than did the general reading space. Also, cosines from the science LSA spaces can distinguish between different levels of semantic similarity, but may have trouble in distinguishing local processing protocols. Thus, a domain-specific LSA space is advantageous regardless of the size of the space. The results are discussed in the context of applying the science LSA to a computer-based version of SERT that gives online feedback based on LSA cosines.

  10. More data trumps smarter algorithms: comparing pointwise mutual information with latent semantic analysis.

    Science.gov (United States)

    Recchia, Gabriel; Jones, Michael N

    2009-08-01

    Computational models of lexical semantics, such as latent semantic analysis, can automatically generate semantic similarity measures between words from statistical redundancies in text. These measures are useful for experimental stimulus selection and for evaluating a model's cognitive plausibility as a mechanism that people might use to organize meaning in memory. Although humans are exposed to enormous quantities of speech, practical constraints limit the amount of data that many current computational models can learn from. We follow up on previous work evaluating a simple metric of pointwise mutual information. Controlling for confounds in previous work, we demonstrate that this metric benefits from training on extremely large amounts of data and correlates more closely with human semantic similarity ratings than do publicly available implementations of several more complex models. We also present a simple tool for building simple and scalable models from large corpora quickly and efficiently.

  11. Neighborhood socioeconomic status and food environment: a 20-year longitudinal latent class analysis among CARDIA participants.

    Science.gov (United States)

    Richardson, Andrea S; Meyer, Katie A; Howard, Annie Green; Boone-Heinonen, Janne; Popkin, Barry M; Evenson, Kelly R; Kiefe, Catarina I; Lewis, Cora E; Gordon-Larsen, Penny

    2014-11-01

    Cross-sectional studies suggest that neighborhood socioeconomic (SES) disadvantage is associated with obesogenic food environments. Yet, it is unknown how exposure to neighborhood SES patterning through adulthood corresponds to food environments that also change over time. We used latent class analysis (LCA) to classify participants in the U.S.-based Coronary Artery Risk Development in Young Adults study [n=5,114 at baseline 1985-1986 to 2005-2006] according to their longitudinal neighborhood SES residency patterns (upward, downward, stable high and stable low). For most classes of residents, the availability of fast food and non-fast food restaurants and supermarkets and convenience stores increased (prestaurants, more convenience stores, and the same number of supermarkets in their neighborhoods than the advantaged residents. In addition to targeting the pervasive fast food restaurant and convenient store retail growth, improving neighborhood restaurant options for disadvantaged residents may reduce food environment disparities.

  12. Factors responsible for mortality variation in the United States: A latent variable analysis

    Directory of Open Access Journals (Sweden)

    Christopher Tencza

    2014-07-01

    Full Text Available Background: Factors including smoking, drinking, substance abuse, obesity, and health care have all been shown to affect health and longevity. The relative importance of each of these factors is disputed in the literature, and has been assessed through a number of methods. Objective: This paper uses a novel approach to identify factors responsible for interstate mortality variation. It identifies factors through their imprint on mortality patterns and can therefore identify factors that are difficult or impossible to measure directly, such as sensitive health behaviors. Methods: The analysis calculates age-standardized death rates by cause of death from 2000-2009 for white men and women separately. Only premature deaths between ages 20-64 are included. Latent variables responsible for mortality variation are then identified through a factor analysis conducted on a death-rate-by-state matrix. These unobserved latent variables are inferred from observed mortality data and interpreted based on their correlations with individual causes of death. Results: Smoking and obesity, substance abuse, and rural/urban residence are the three factors that make the largest contributions to state-level mortality variation among males. The same factors are at work for women but are less vividly revealed. The identification of factors is supported by a review of epidemiologic studies and strengthened by correlations with observable behavioral variables. Results are not sensitive to the choice of factor-analytic method used. Conclusions: The majority of interstate variation in mortality among white working-age adults in the United States is associated with a combination of smoking and obesity, substance abuse and rural/urban residence.

  13. Performance analysis of digital cameras versus chromatic white light (CWL) sensors for the localization of latent fingerprints in crime scenes

    Science.gov (United States)

    Jankow, Mathias; Hildebrandt, Mario; Sturm, Jennifer; Kiltz, Stefan; Vielhauer, Claus

    2012-06-01

    In future applications of contactless acquisition techniques for latent fingerprints the automatic localization of potential fingerprint traces in crime scenes is required. Our goal is to study the application of a camera-based approach1 comparing with the performance of chromatic white light (CWL) techniques2 for the latent fingerprint localization in coarse and the resulting acquisition using detailed scans. Furthermore, we briefly evaluate the suitability of the camera-based acquisition for the detection of malicious fingerprint traces using an extended camera setup in comparison to Kiltz et al.3 Our experimental setup includes a Canon EOS 550D4 digital single-lens reflex (DSLR) camera and a FRT MicroProf2005 surface measurement device with CWL6002 sensor. We apply at least two fingerprints to each surface in our test set with 8 different either smooth, textured and structured surfaces to evaluate the detection performance of the two localization techniques using different pre-processing and feature extraction techniques. Printed fingerprint patterns as reproducible but potentially malicious traces3 are additionally acquired and analyzed on foil and compact discs. Our results indicate positive tendency towards a fast localization using the camera-based technique. All fingerprints that are located using the CWL sensor are found using the camera. However,the disadvantage of the camera-based technique is that the size of the region of interest for the detailed scan for each potential latent fingerprint is usually slightly larger compared to the CWL-based localization. Furthermore, this technique does not acquire 3D data and the resulting images are distorted due to the necessary angle between the camera and the surface. When applying the camera-based approach, it is required to optimize the feature extraction and classification. Furthermore, the required acquisition time for each potential fingerprint needs to be estimated to determine the time-savings of the

  14. Profiles of adolescent religiousness using latent profile analysis: Implications for psychopathology.

    Science.gov (United States)

    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

  15. Latent classification models

    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...... of the \\NB classifier. In theproposed model the continuous attributes are described by amixture of multivariate Gaussians, where the conditionaldependencies among the attributes are encoded using latentvariables. We present algorithms for learning both the parametersand the structure of a latent...

  16. Advancement of Latent Trait Theory.

    Science.gov (United States)

    1988-02-01

    Estimation with the Multiple-Choice Test Item. American Educational Research Association Meeting, New Orleans, 1984. (Coauthorship with Paul S. Changas...Chicago, 1985. U. S. A. (Coauthorship with Paul S. Changas) (10) Expansion of the General Model for the Homogeneous Case of the Continuous Response Level...17-20. [2] Lazarsfeld , P. F. Latent structure analysis. In S. Koch (Ed.), Psychology: a study of a science, Volume 3. McGraw-Hill, 1959, pages 476-542

  17. A Latent Transition Analysis of Academic Intrinsic Motivation from Childhood through Adolescence

    Science.gov (United States)

    Marcoulides, George A.; Gottfried, Adele Eskeles; Gottfried, Allen W.; Oliver, Pamella H.

    2008-01-01

    A longitudinal modeling approach was utilized to determine the existence of latent classes with regard to academic intrinsic motivation and the points of stability and transition of individuals between and within classes. A special type of latent Markov Chain model using "Mplus" was fit to data from the Fullerton Longitudinal Study, with…

  18. Longitudinal Data Analysis with Latent Growth Modeling: An Introduction and Illustration for Higher Education Researchers

    Science.gov (United States)

    Blanchard, Rebecca D.; Konold, Timothy R.

    2011-01-01

    This paper introduces latent growth modeling (LGM) as a statistical method for analyzing change over time in latent, or unobserved, variables, with particular emphasis of the application of this method in higher education research. While increasingly popular in other areas of education research and despite a wealth of publicly-available datasets…

  19. Extending dynamic segmentation with lead generation : A latent class Markov analysis of financial product portfolios

    NARCIS (Netherlands)

    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 M

  20. How to Classify the Diversity of Seventh Grade Students' Mathematical Process Skills: An Application of Latent Profile Analysis

    Science.gov (United States)

    Kaosa-ard, Chanapat; Erawan, Waraporn; Damrongpanit, Suntonrapot; Suksawang, Poonpong

    2015-01-01

    The researcher applied latent profile analysis to study the difference of the students' mathematical process skill. These skills are problem solving skills, reasoning skills, communication and presentation skills, connection knowledge skills, and creativity skills. Samples were 2,485 seventh-grade students obtained from Multi-stage Random…

  1. Enhancing the Psychological Well-Being of Elderly Individuals through Tai Chi Exercise: A Latent Growth Curve Analysis.

    Science.gov (United States)

    Li, Fuzhong; Duncan, Terry E.; Duncan, Susan C.; McAuley, Edward; Chaumeton, Nigel R.; Harmer, Peter

    2001-01-01

    Examined whether a Tai Chi exercise program enhanced the psychological well-being of 98 elderly individuals. Analyzed repeated measures data about participants using latent growth curve analysis. Results indicate the beneficial effects of participation in the Tai Chi program. Discusses implications related to the exercise-psychological health…

  2. A Latent Class Growth Analysis of School Bullying and Its Social Context: The Self-Determination Theory Perspective

    Science.gov (United States)

    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%),…

  3. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey: a latent class analysis

    NARCIS (Netherlands)

    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

  4. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey : a latent class analysis

    NARCIS (Netherlands)

    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

  5. Presentations and recorded keynotes of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

    NARCIS (Netherlands)

    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:

  6. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

    Science.gov (United States)

    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…

  7. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

    Science.gov (United States)

    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…

  8. How to Classify the Diversity of Seventh Grade Students' Mathematical Process Skills: An Application of Latent Profile Analysis

    Science.gov (United States)

    Kaosa-ard, Chanapat; Erawan, Waraporn; Damrongpanit, Suntonrapot; Suksawang, Poonpong

    2015-01-01

    The researcher applied latent profile analysis to study the difference of the students' mathematical process skill. These skills are problem solving skills, reasoning skills, communication and presentation skills, connection knowledge skills, and creativity skills. Samples were 2,485 seventh-grade students obtained from Multi-stage Random…

  9. Presentations and recorded keynotes of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

    NARCIS (Netherlands)

    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: http://homer.ou.nl/lsa-workshop0

  10. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey : a latent class analysis

    NARCIS (Netherlands)

    Padmadas, SS; Dias, JG; Willekens, FJ

    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 Fami

  11. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey: a latent class analysis

    NARCIS (Netherlands)

    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 Fami

  12. A Person-Centered Perspective on Multidimensional Perfectionism in Canadian and Chinese University Students: A Multigroup Latent Profile Analysis

    Science.gov (United States)

    Smith, Martin M.; Saklofske, Donald H.; Yan, Gonggu; Sherry, Simon B.

    2016-01-01

    This study investigated the generalizability of the tripartite model of perfectionism across Canadian and Chinese university students. Using latent profile analysis and indicators of perfectionistic strivings, perfectionistic concerns, and neuroticism in both groups, the authors derived a 3-profile solution: adaptive perfectionists, maladaptive…

  13. Stress, Mental Health, and Substance Abuse Problems in a Sample of Diversion Program Youths: An Exploratory Latent Class Analysis

    Science.gov (United States)

    Dembo, Richard; Briones, Rhissa; Gulledge, Laura; Karas, Lora; Winters, Ken C.; Belenko, Steven; Greenbaum, Paul E.

    2012-01-01

    Reflective of interest in mental health and substance abuse issues among youths involved with the justice system, we performed a latent class analysis on baseline information collected on 100 youths involved in two diversion programs. Results identified two groups of youths: Group 1: a majority of the youths, who had high levels of delinquency,…

  14. Enhancing the Psychological Well-Being of Elderly Individuals through Tai Chi Exercise: A Latent Growth Curve Analysis.

    Science.gov (United States)

    Li, Fuzhong; Duncan, Terry E.; Duncan, Susan C.; McAuley, Edward; Chaumeton, Nigel R.; Harmer, Peter

    2001-01-01

    Examined whether a Tai Chi exercise program enhanced the psychological well-being of 98 elderly individuals. Analyzed repeated measures data about participants using latent growth curve analysis. Results indicate the beneficial effects of participation in the Tai Chi program. Discusses implications related to the exercise-psychological health…

  15. A Person-Centered Perspective on Multidimensional Perfectionism in Canadian and Chinese University Students: A Multigroup Latent Profile Analysis

    Science.gov (United States)

    Smith, Martin M.; Saklofske, Donald H.; Yan, Gonggu; Sherry, Simon B.

    2016-01-01

    This study investigated the generalizability of the tripartite model of perfectionism across Canadian and Chinese university students. Using latent profile analysis and indicators of perfectionistic strivings, perfectionistic concerns, and neuroticism in both groups, the authors derived a 3-profile solution: adaptive perfectionists, maladaptive…

  16. Presentations and recorded keynotes of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

    NARCIS (Netherlands)

    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: http://homer.ou.nl/lsa-workshop0

  17. Latent class analysis of diagnostic science assessment data using Bayesian networks

    Science.gov (United States)

    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

  18. Subgrouping of risky behaviors among Iranian college students: a latent class analysis

    Science.gov (United States)

    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

  19. Latent Class Analysis of DSM-5 Alcohol Use Disorder Criteria Among Heavy-Drinking College Students.

    Science.gov (United States)

    Rinker, Dipali Venkataraman; Neighbors, Clayton

    2015-10-01

    The DSM-5 has created significant changes in the definition of alcohol use disorders (AUDs). Limited work has considered the impact of these changes in specific populations, such as heavy-drinking college students. Latent class analysis (LCA) is a person-centered approach that divides a population into mutually exclusive and exhaustive latent classes, based on observable indicator variables. The present research was designed to examine whether there were distinct classes of heavy-drinking college students who met DSM-5 criteria for an AUD and whether gender, perceived social norms, use of protective behavioral strategies (PBS), drinking refusal self-efficacy (DRSE), self-perceptions of drinking identity, psychological distress, and membership in a fraternity/sorority would be associated with class membership. Three-hundred and ninety-four college students who met DSM-5 criteria for an AUD were recruited from three different universities. Two distinct classes emerged: Less Severe (86%), the majority of whom endorsed both drinking more than intended and tolerance, as well as met criteria for a mild AUD; and More Severe (14%), the majority of whom endorsed at least half of the DSM-5 AUD criteria and met criteria for a severe AUD. Relative to the Less Severe class, membership in the More Severe class was negatively associated with DRSE and positively associated with self-identification as a drinker. There is a distinct class of heavy-drinking college students with a more severe AUD and for whom intervention content needs to be more focused and tailored. Clinical implications are discussed.

  20. Latent class analysis of eating and impulsive behavioral symptoms in Taiwanese women with bulimia nervosa.

    Science.gov (United States)

    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.

  1. Chronic medical conditions among jail detainees in residential psychiatric treatment: a latent class analysis.

    Science.gov (United States)

    Swartz, James A

    2011-08-01

    Studies of incarcerates with serious mental illnesses have found elevated rates of chronic medical conditions such as asthma and diabetes, and of infectious diseases such as tuberculosis compared with general population rates. This study explored the pattern of chronic medical conditions in a sample of adult detainees in psychiatric treatment in a large urban jail to develop a clinical profile encompassing the full range of medical conditions. A total of 431 male and female detainees were sampled with certainty from admissions to a residential psychiatric treatment program (overall recruitment rate = 67%). Interviews used the World Mental Health version of the Composite International Diagnostic Interview to assess psychiatric and substance use disorders per DSM-IV criteria and chronic medical conditions. Latent class analysis was conducted using 17 medical conditions as class indicators, yielding a 3-class model composed of: a latent class with a high to intermediate probability of multiple medical conditions (HMC; 12.5% of the sample); an intermediate class with a lower probability of having a smaller number of medical conditions (MMC; 43.2%); and a class with a low probability of any medical condition (44.3%). Those in the HMC class were more likely to report respiratory problems, severe headaches, musculoskeletal pain, hypertension, and arthritis, have greater functional impairment, and have a higher number of co-occurring psychiatric disorders. Being older (50+ years) and female were associated with higher odds of being in the HMC or MMC classes. The policy implications for providing medical care to incarcerates with complex mixtures of medical conditions and psychiatric disorders are considered.

  2. Longitudinal burnout-collaboration patterns in Japanese medical care workers at special needs schools: a latent class growth analysis

    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

  3. A Bayesian Approach to a Multiple-Group Latent Class-Profile Analysis: The Timing of Drinking Onset and Subsequent Drinking Behaviors among U.S. Adolescents

    Science.gov (United States)

    Chung, Hwan; Anthony, James C.

    2013-01-01

    This article presents a multiple-group latent class-profile analysis (LCPA) by taking a Bayesian approach in which a Markov chain Monte Carlo simulation is employed to achieve more robust estimates for latent growth patterns. This article describes and addresses a label-switching problem that involves the LCPA likelihood function, which has…

  4. 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

  5. Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks.

    Science.gov (United States)

    de Oña, Juan; López, Griselda; Mujalli, Randa; Calvo, Francisco J

    2013-03-01

    One of the principal objectives of traffic accident analyses is to identify key factors that affect the severity of an accident. However, with the presence of heterogeneity in the raw data used, the analysis of traffic accidents becomes difficult. In this paper, Latent Class Cluster (LCC) is used as a preliminary tool for segmentation of 3229 accidents on rural highways in Granada (Spain) between 2005 and 2008. Next, Bayesian Networks (BNs) are used to identify the main factors involved in accident severity for both, the entire database (EDB) and the clusters previously obtained by LCC. The results of these cluster-based analyses are compared with the results of a full-data analysis. The results show that the combined use of both techniques is very interesting as it reveals further information that would not have been obtained without prior segmentation of the data. BN inference is used to obtain the variables that best identify accidents with killed or seriously injured. Accident type and sight distance have been identify in all the cases analysed; other variables such as time, occupant involved or age are identified in EDB and only in one cluster; whereas variables vehicles involved, number of injuries, atmospheric factors, pavement markings and pavement width are identified only in one cluster. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Psychological features of North Korean female refugees on the MMPI-2: latent profile analysis.

    Science.gov (United States)

    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.

  7. Latent Dirichlet Allocation (LDA) for Sentiment Analysis Toward Tourism Review in Indonesia

    Science.gov (United States)

    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.

  8. Latent class analysis on internet and smartphone addiction in college students

    Science.gov (United States)

    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 internet usage, males were more addicted than females (Pinternet 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 (Paddiction severity levels (all Paddiction severity levels (all Pinternet 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

  9. Identifying differences in the experience of (in)authenticity: a latent class analysis approach.

    Science.gov (United States)

    Lenton, Alison P; Slabu, Letitia; Bruder, Martin; Sedikides, Constantine

    2014-01-01

    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 (in)authenticity than relatively more independent cultures. Understanding the many facets of (in)authenticity may enable researchers to connect different findings and explain why the attainment of authenticity can be difficult.

  10. Social stressors, coping behaviors, and depressive symptoms: A latent profile analysis of adolescents in military families.

    Science.gov (United States)

    Okafor, Ebony; Lucier-Greer, Mallory; Mancini, Jay A

    2016-08-01

    We investigated the relationship between context-specific social stressors, coping behaviors, and depressive symptoms among adolescents in active duty military families across seven installations (three of which were in Europe) (N = 1036) using a person-centered approach and a stress process theoretical framework. Results of the exploratory latent profile analysis revealed four distinct coping profiles: Disengaged Copers, Troubled Copers, Humor-intensive Copers, and Active Copers. Multinomial logistic regressions found no relationship between military-related stressors (parental separation, frequent relocations, and parental rank) and profile membership. Analysis of variance results revealed significant and meaningful differences between the coping profiles and depressive symptomology, specifically somatic symptoms, depressive affect, positive affect, and interpersonal problems. Post-hoc analyses revealed that Active Copers, the largest profile, reported the fewest depressive symptoms. Accordingly, frequent use of diverse, active coping behaviors was associated with enhanced resilience. Discussion is provided regarding the promotion of adaptive coping behaviors within this developmental period and the context of military family life.

  11. Variations in adolescents' motivational characteristics across gender and physical activity patterns: A latent class analysis approach.

    Science.gov (United States)

    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

  12. 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

  13. Extending dynamic segmentation with lead generation: A latent class Markov analysis of financial product portfolios

    OpenAIRE

    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 Markov model for these purposes using a database containing information on the ownership of twelve financial products and demographics for explaining (changes in) consumer product portfolios.Data we...

  14. Predominant typologies of psychopathology in the United States: a latent class analysis.

    Science.gov (United States)

    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

  15. Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

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    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.

  16. Assessing short summaries with human judgments procedure and latent semantic analysis in narrative and expository texts.

    Science.gov (United States)

    León, José A; Olmos, Ricardo; Escudero, Inmaculada; Cañas, José J; Salmerón, Lalo

    2006-11-01

    In the present study, we tested a computer-based procedure for assessing very concise summaries (50 words long) of two types of text (narrative and expository) using latent semantic analysis (LSA) in comparison with the judgments of four human experts. LSA was used to estimate semantic similarity using six different methods: four holistic (summary-text, summary-summaries, summary-expert summaries, and pregraded-ungraded summary) and two componential (summary-sentence text and summary-main sentence text). A total of 390 Spanish middle and high school students (14-16 years old) and six experts read a narrative or expository text and later summarized it. The results support the viability of developing a computerized assessment tool using human judgments and LSA, although the correlation between human judgments and LSA was higher in the narrative text than in the expository, and LSA correlated more with human content ratings thanwith hu mancoherence ratings. Finally, theholistic methods were found to be more reliable than the componential methods analyzed in this study.

  17. Thermal Analysis of Fluidized Bed and Fixed Bed Latent Heat Thermal Storage System

    Science.gov (United States)

    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.

  18. Distinguishing PTSD, Complex PTSD, and Borderline Personality Disorder: A latent class analysis

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    Marylène Cloitre

    2014-09-01

    Full Text Available Background: There has been debate regarding whether Complex Posttraumatic Stress Disorder (Complex PTSD is distinct from Borderline Personality Disorder (BPD when the latter is comorbid with PTSD. Objective: To determine whether the patterns of symptoms endorsed by women seeking treatment for childhood abuse form classes that are consistent with diagnostic criteria for PTSD, Complex PTSD, and BPD. Method: A latent class analysis (LCA was conducted on an archival dataset of 280 women with histories of childhood abuse assessed for enrollment in a clinical trial for PTSD. Results: The LCA revealed four distinct classes of individuals: a Low Symptom class characterized by low endorsements on all symptoms; a PTSD class characterized by elevated symptoms of PTSD but low endorsement of symptoms that define the Complex PTSD and BPD diagnoses; a Complex PTSD class characterized by elevated symptoms of PTSD and self-organization symptoms that defined the Complex PTSD diagnosis but low on the symptoms of BPD; and a BPD class characterized by symptoms of BPD. Four BPD symptoms were found to greatly increase the odds of being in the BPD compared to the Complex PTSD class: frantic efforts to avoid abandonment, unstable sense of self, unstable and intense interpersonal relationships, and impulsiveness. Conclusions: Findings supported the construct validity of Complex PTSD as distinguishable from BPD. Key symptoms that distinguished between the disorders were identified, which may aid in differential diagnosis and treatment planning.

  19. PTSD symptom severity and psychiatric comorbidity in recent motor vehicle accident victims: a latent class analysis.

    Science.gov (United States)

    Hruska, Bryce; Irish, Leah A; Pacella, Maria L; Sledjeski, Eve M; Delahanty, Douglas L

    2014-10-01

    We conducted a latent class analysis (LCA) on 249 recent motor vehicle accident (MVA) victims to examine subgroups that differed in posttraumatic stress disorder (PTSD) symptom severity, current major depressive disorder and alcohol/other drug use disorders (MDD/AoDs), gender, and interpersonal trauma history 6-weeks post-MVA. A 4-class model best fit the data with a resilient class displaying asymptomatic PTSD symptom levels/low levels of comorbid disorders; a mild psychopathology class displaying mild PTSD symptom severity and current MDD; a moderate psychopathology class displaying severe PTSD symptom severity and current MDD/AoDs; and a severe psychopathology class displaying extreme PTSD symptom severity and current MDD. Classes also differed with respect to gender composition and history of interpersonal trauma experience. These findings may aid in the development of targeted interventions for recent MVA victims through the identification of subgroups distinguished by different patterns of psychiatric problems experienced 6-weeks post-MVA. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Effect of intrinsic motivation on affective responses during and after exercise: latent curve model analysis.

    Science.gov (United States)

    Shin, Myoungjin; Kim, Inwoo; Kwon, Sungho

    2014-12-01

    Understanding the relationship between affect and exercise is helpful in predicting human behavior with respect to exercise participation. The goals of the present study were to investigate individual differences in affective response during and after exercise and to identify the role of intrinsic motivation in affective changes. 30 active male college students (M age = 21.4 yr.) who regularly participated in sports activities volunteered to answer a questionnaire measuring intrinsic motivation toward running activities and performed a 20-min. straight running protocol at heavy intensity (about 70% of VO2max). Participants' affective responses were measured every 5 min. from the beginning of the run to 10 min. after completing the run. Latent curve model analysis indicated that individuals experienced different changes in affective state during exercise, moderated by intrinsic motivation. Higher intrinsic motivation was associated with more positive affect during exercise. There were no significant individual differences in the positive tendency of the participants' affective responses after exercise over time. Intrinsic motivation seems to facilitate positive feelings during exercise and encourages participation in exercise.

  1. Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

    Science.gov (United States)

    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

  2. Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

    Directory of Open Access Journals (Sweden)

    Chen David P

    2010-10-01

    Full Text Available Abstract Background Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however, is limited to the types of clinical biomarkers collected, and is prone to overlooking dysfunctions in physiological factors not easily evident to medical practitioners. We used a vector-based representation of patient clinical biomarkers, or clinarrays, to search for latent physiological factors that underlie human diseases directly from clinical laboratory data. Knowledge of these factors could be used to improve assessment of disease severity and help to refine strategies for diagnosis and monitoring disease progression. Results Applying Independent Component Analysis on clinarrays built from patient laboratory measurements revealed both known and novel concomitant physiological factors for asthma, types 1 and 2 diabetes, cystic fibrosis, and Duchenne muscular dystrophy. Serum sodium was found to be the most significant factor for both type 1 and type 2 diabetes, and was also significant in asthma. TSH3, a measure of thyroid function, and blood urea nitrogen, indicative of kidney function, were factors unique to type 1 diabetes respective to type 2 diabetes. Platelet count was significant across all the diseases analyzed. Conclusions The results demonstrate that large-scale analyses of clinical biomarkers using unsupervised methods can offer novel insights into the pathophysiological basis of human disease, and suggest novel clinical utility of established laboratory measurements.

  3. Emotional labor actors: a latent profile analysis of emotional labor strategies.

    Science.gov (United States)

    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.

  4. Four subtypes of self-neglect in older adults: results of a latent class analysis.

    Science.gov (United States)

    Burnett, Jason; Dyer, Carmel B; Halphen, John M; Achenbaum, W A; Green, Charles E; Booker, James G; Diamond, Pamela M

    2014-06-01

    To determine whether there are subtypes of elder self-neglect (SN) with different risk factors that can be targeted using medical and social interventions. Cohort study using archived data of Adult Protective Services (APS) substantiated cases of elder SN between January 1, 2004, and December 31, 2008. Houston, Harris County, Texas. Adults aged 65 and older with APS region VI substantiated SN between January 1, 2004, and December 31, 2008 (N = 5,686). Adult Protective Services caseworkers used the Client Assessment and Risk Evaluation (CARE) tool during home investigations, assessing risk of harm in the domains of living conditions, financial status, physical and medical status, mental health, and social connectedness. Latent class analysis was used to identify unique subtypes of elder SN. Four unique subtypes of elder SN were identified, with approximately 50% of individuals manifesting physical and medical neglect problems. Other subtypes included environmental neglect (22%), global neglect (21%), and financial neglect (9%). Older age, Caucasian descent, and mental status problems were more strongly associated with global neglect behaviors. African Americans were more likely to experience financial and environmental neglect than Caucasians and non-white Hispanics. Elder SN consists of unique subtypes that may be amenable to customized multidisciplinary interventions. Future studies are needed to determine whether these subtypes impose differential mortality risks and whether multidisciplinary tailored interventions can reduce SN and prevent early mortality. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

  5. A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews.

    Science.gov (United States)

    Wallace, Byron C; Paul, Michael J; Sarkar, Urmimala; Trikalinos, Thomas A; Dredze, Mark

    2014-01-01

    Online physician reviews are a massive and potentially rich source of information capturing patient sentiment regarding healthcare. We analyze a corpus comprising nearly 60,000 such reviews with a state-of-the-art probabilistic model of text. We describe a probabilistic generative model that captures latent sentiment across aspects of care (eg, interpersonal manner). We target specific aspects by leveraging a small set of manually annotated reviews. We perform regression analysis to assess whether model output improves correlation with state-level measures of healthcare. We report both qualitative and quantitative results. Model output correlates with state-level measures of quality healthcare, including patient likelihood of visiting their primary care physician within 14 days of discharge (p=0.03), and using the proposed model better predicts this outcome (p=0.10). We find similar results for healthcare expenditure. Generative models of text can recover important information from online physician reviews, facilitating large-scale analyses of such reviews.

  6. Mental Health and Educational Experiences Among Black Youth: A Latent Class Analysis.

    Science.gov (United States)

    Rose, Theda; Lindsey, Michael A; Xiao, Yunyu; Finigan-Carr, Nadine M; Joe, Sean

    2017-07-28

    Disproportionately lower educational achievement, coupled with higher grade retention, suspensions, expulsions, and lower school bonding make educational success among Black adolescents a major public health concern. Mental health is a key developmental factor related to educational outcomes among adolescents; however, traditional models of mental health focus on absence of dysfunction as a way to conceptualize mental health. The dual-factor model of mental health incorporates indicators of both subjective wellbeing and psychopathology, supporting more recent research that both are needed to comprehensively assess mental health. This study applied the dual-factor model to measure mental health using the National Survey of American Life-Adolescent Supplement (NSAL-A), a representative cross-sectional survey. The sample included 1170 Black adolescents (52% female; mean age 15). Latent class analysis was conducted with positive indicators of subjective wellbeing (emotional, psychological, and social) as well as measures of psychopathology. Four mental health groups were identified, based on having high or low subjective wellbeing and high or low psychopathology. Accordingly, associations between mental health groups and educational outcomes were investigated. Significant associations were observed in school bonding, suspensions, and grade retention, with the positive mental health group (high subjective wellbeing, low psychopathology) experiencing more beneficial outcomes. The results support a strong association between school bonding and better mental health and have implications for a more comprehensive view of mental health in interventions targeting improved educational experiences and mental health among Black adolescents.

  7. Quality of life, functioning and cognition in bipolar disorder and major depression: A latent profile analysis.

    Science.gov (United States)

    Cotrena, Charles; Branco, Laura Damiani; Kochhann, Renata; Shansis, Flávio Milman; Fonseca, Rochele Paz

    2016-07-30

    This study aimed to identify profiles of functioning and quality of life (QOL) in depression (MDD), bipolar disorder (BD) and healthy adults, as well as the clinical, demographic and cognitive variables associated with each of these profiles. Participants completed the WHODAS 2.0 and WHOQOL-BREF, which were submitted to latent profile analysis. The four cluster solution provided the best fit for our data. Cluster 1 consisted mostly of healthy adults, and had the highest functioning and QOL. Clusters 2 contained older patients with subclinical depressive symptoms and psychiatric comorbidities, whose impairments in QOL and functioning were associated with mood symptoms and several cognitive abilities. Patients with MDD, BDI or BDII with mild to moderate depression, such as those in cluster 3, may benefit more significantly from interventions in cognitive flexibility, inhibition, planning, and sustained attention. Lastly, patients with mood disorders and clinically significant levels of depression, as well as a history of suicide attempts, like those in cluster 4, may benefit from interventions aimed at working memory, inhibitory control, and cognitive flexibility; that is, the three core executive functions. These findings should be further investigated, and used to guide treatments for patients with mood disorders and different patterns of functional impairment.

  8. Older adults who are at risk of driving under the influence: A latent class analysis.

    Science.gov (United States)

    Choi, Namkee G; DiNitto, Diana M; Marti, C Nathan

    2015-09-01

    Despite increasing rates of substance use among older adults, their risk of driving under the influence of alcohol and/or drugs (DUI) has received scant research attention. This study identified DUI risk profiles among individuals aged 50+ years based on their substance use patterns, previous DUI incidents, and previous arrests. This study's analytic sample of 11,188 individuals came from the public use data sets of the 2008 to 2012 National Survey on Drug Use and Health. Latent class analysis identified a 4-class model as the most parsimonious. Class 1 (63% of the analytic sample; lowest risk group) exhibited the lowest probabilities of substance use and trouble with law while Class 4 (9% of the sample; highest risk group) included binge/heavy drinkers who are also likely to use illicit drugs and had the highest probabilities of self-reported DUI and previous arrests. Class 2 (18.5%) and Class 3 (9.5%) exhibited low-to-medium DUI risks. Class 4 had the highest proportions of Blacks and divorced or never married persons and had lowest education and income, poorest self-rated health, and highest rates of mental health problems of all classes. Screening for substance abuse and comorbid mental health conditions should be included in protocols for assessing older adults' driving safety. More effort is also needed to improve access to substance abuse treatment and address mental health problems among older adults at high risk for DUI.

  9. ARABIC TEXT SUMMARIZATION BASED ON LATENT SEMANTIC ANALYSIS TO ENHANCE ARABIC DOCUMENTS CLUSTERING

    Directory of Open Access Journals (Sweden)

    Hanane Froud

    2013-01-01

    Full Text Available Arabic Documents Clustering is an important task for obtaining good results with the traditional Information Retrieval (IR systems especially with the rapid growth of the number of online documents present in Arabic language. Documents clustering aim to automatically group similar documents in one cluster using different similarity/distance measures. This task is often affected by the documents length, useful information on the documents is often accompanied by a large amount of noise, and therefore it is necessary to eliminate this noise while keeping useful information to boost the performance of Documents clustering. In this paper, we propose to evaluate the impact of text summarization using the Latent Semantic Analysis Model on Arabic Documents Clustering in order to solve problems cited above, using five similarity/distance measures: Euclidean Distance, Cosine Similarity, Jaccard Coefficient, Pearson Correlation Coefficient and Averaged Kullback-Leibler Divergence, for two times: without and with stemming. Our experimental results indicate that our proposed approach effectively solves the problems of noisy information and documents length, and thus significantly improve the clustering performance.

  10. Cross-Language Plagiarism Detection System Using Latent Semantic Analysis and Learning Vector Quantization

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    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.

  11. Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

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    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.

  12. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

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    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  13. Validating Quantitative Measurement Using Qualitative Data: Combining Rasch Scaling and Latent Semantic Analysis in Psychiatry

    Science.gov (United States)

    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.

  14. Risk Stratification for Major Postoperative Complications in Patients Undergoing Intra-abdominal General Surgery Using Latent Class Analysis.

    Science.gov (United States)

    Kim, Minjae; Wall, Melanie M; Li, Guohua

    2017-08-10

    Preoperative risk stratification is a critical element in assessing the risks and benefits of surgery. Prior work has demonstrated that intra-abdominal general surgery patients can be classified based on their comorbidities and risk factors using latent class analysis (LCA), a model-based clustering technique designed to find groups of patients that are similar with respect to characteristics entered into the model. Moreover, the latent risk classes were predictive of 30-day mortality. We evaluated the use of latent risk classes to predict the risk of major postoperative complications. An observational, retrospective cohort of patients undergoing intra-abdominal general surgery in the 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was obtained. Known preoperative comorbidity and risk factor data were entered into LCA models to identify the latent risk classes. Complications were defined as: acute kidney injury, acute respiratory failure, cardiac arrest, deep vein thrombosis, myocardial infarction, organ space infection, pneumonia, postoperative bleeding, pulmonary embolism, sepsis/septic shock, stroke, unplanned reintubation, and/or wound dehiscence. Relative risk regression determined the associations between the latent classes and the 30-day complication risks, with adjustments for the surgical procedure. The area under the curve (AUC) of the receiver operator characteristic curve assessed model performance. LCA fit a 9-class model on 466,177 observations. The composite complication risk was 18.4% but varied from 7.7% in the lowest risk class to 56.7% in the highest risk class. After adjusting for procedure, the latent risk classes were significantly associated with complications, with risk ratios (95% confidence intervals) (compared to the class with the average risk) varying from 0.56 (0.54-0.58) in the lowest risk class to 2.15 (2.11-2.20) in the highest risk class, a 4-fold difference. In models incorporating surgical

  15. Content Themes of Alcohol Advertising in US Television — Latent Class Analysis

    Science.gov (United States)

    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

  16. Content Themes of Alcohol Advertising in U.S. Television-Latent Class Analysis.

    Science.gov (United States)

    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.

  17. Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study

    OpenAIRE

    Silverwood, RJ; Nitsch, D.; Pierce, M; Kuh, D; Mishra, GD

    2011-01-01

    : The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31-53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council's 1946 National Survey of Health and Development. Three different types of physical activity-walking, cycling, and leisure-time physical activity-were analyzed separately using self-reported data collected from questionnaires between 1977 and 1999; 3,847 stu...

  18. A Latent Class Analysis of Heterosexual Young Men’s Masculinities

    Science.gov (United States)

    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

  19. Three subgroups of pain profiles identified in 227 women with arthritis: a latent class analysis.

    Science.gov (United States)

    de Luca, Katie; Parkinson, Lynne; Downie, Aron; Blyth, Fiona; Byles, Julie

    2017-03-01

    The objectives were to identify subgroups of women with arthritis based upon the multi-dimensional nature of their pain experience and to compare health and socio-demographic variables between subgroups. A latent class analysis of 227 women with self-reported arthritis was used to identify clusters of women based upon the sensory, affective, and cognitive dimensions of the pain experience. Multivariate multinomial logistic regression analysis was used to determine the relationship between cluster membership and health and sociodemographic characteristics. A three-class cluster model was most parsimonious. 39.5 % of women had a unidimensional pain profile; 38.6 % of women had moderate multidimensional pain profile that included additional pain symptomatology such as sensory qualities and pain catastrophizing; and 21.9 % of women had severe multidimensional pain profile that included prominent pain symptomatology such as sensory and affective qualities of pain, pain catastrophizing, and neuropathic pain. Women with severe multidimensional pain profile have a 30.5 % higher risk of poorer quality of life and a 7.3 % higher risk of suffering depression, and women with moderate multidimensional pain profile have a 6.4 % higher risk of poorer quality of life when compared to women with unidimensional pain. This study identified three distinct subgroups of pain profiles in older women with arthritis. Women had very different experiences of pain, and cluster membership impacted significantly on health-related quality of life. These preliminary findings provide a stronger understanding of profiles of pain and may contribute to the development of tailored treatment options in arthritis.

  20. Alcohol Use as Risk Factors for Older Adults’ Emergency Department Visits: A Latent Class Analysis

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    Namkee G. Choi, PhD

    2015-12-01

    Full Text Available Introduction: Late middle-aged and older adults’ share of emergency department (ED visits is increasing more than other age groups. ED visits by individuals with substance-related problems are also increasing. This paper was intended to identify subgroups of individuals aged 50+ by their risk for ED visits by examining their health/mental health status and alcohol use patterns. Methods: Data came from the 2013 National Health Interview Survey’s Sample Adult file (n=15,713. Following descriptive analysis of sample characteristics by alcohol use patterns, latent class analysis (LCA modeling was fit using alcohol use pattern (lifetime abstainers, ex-drinkers, current infrequent/light/ moderate drinkers, and current heavy drinkers, chronic health and mental health status, and past-year ED visits as indicators. Results: LCA identified a four-class model. All members of Class 1 (35% of the sample; lowest-risk group were infrequent/light/moderate drinkers and exhibited the lowest probabilities of chronic health/ mental health problems; Class 2 (21%; low-risk group consisted entirely of lifetime abstainers and, despite being the oldest group, exhibited low probabilities of health/mental health problems; Class 3 (37%; moderate-risk group was evenly divided between ex-drinkers and heavy drinkers; and Class 4 (7%; high-risk group included all four groups of drinkers but more ex-drinkers. In addition, Class 4 had the highest probabilities of chronic health/mental problems, unhealthy behaviors, and repeat ED visits, with the highest proportion of Blacks and the lowest proportions of college graduates and employed persons, indicating significant roles of these risk factors. Conclusion: Alcohol nonuse/use (and quantity of use and chronic health conditions are significant contributors to varying levels of ED visit risk. Clinicians need to help heavy-drinking older adults reduce unhealthy alcohol consumption and help both heavy drinkers and ex

  1. Impact of Incredible Years® on teacher perceptions of parental involvement: A latent transition analysis.

    Science.gov (United States)

    Thompson, Aaron M; Herman, Keith C; Stormont, Melissa A; Reinke, Wendy M; Webster-Stratton, Carolyn

    2017-06-01

    The purpose of the present study was to examine the impact of the Incredible Years® Teacher Classroom Management (IY TCM) training on teacher perceptions of parental involvement. A cluster randomized design was used to assign 42 classroom teachers to either an IY TCM training (n=19) or a control condition (n=23). Teachers rated parental involvement (i.e., bonding with teacher, parental involvement at school) for the families of 805 low income students (IY TCM=504, control=301). A latent profile transition analysis framework was used to model the effect of IY TCM on teacher perceptions of parental involvement from pre to posttest. Four profiles consisting of various patterns of high, medium, and low teacher perceptions of bonding with and involvement of parents emerged. Analyses of teacher profiles at baseline revealed teachers who felt parental involvement and bonding was low were also likely to rate students as having more externalizing behaviors, fewer social competencies, more attention deficit symptoms, and disruptive behaviors towards adults and peers compared to teachers with more adaptive profiles. Further analysis revealed that parents of teachers randomly assigned to IY TCM were more likely to transition to a more adaptive view of parental involvement at follow-up compared to teachers in the control condition. Because teacher perceptions of parental involvement may adversely impact teacher attitudes towards difficult students, findings from the present study support the promise of teacher training as an avenue for conferring protections for struggling students. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  2. Evidence for proposed ICD-11 PTSD and complex PTSD: a latent profile analysis

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    Marylène Cloitre

    2013-05-01

    Full Text Available Background: The WHO International Classification of Diseases, 11th version (ICD-11, has proposed two related diagnoses, posttraumatic stress disorder (PTSD and complex PTSD within the spectrum of trauma and stress-related disorders. Objective: To use latent profile analysis (LPA to determine whether there are classes of individuals that are distinguishable according to the PTSD and complex PTSD symptom profiles and to identify potential differences in the type of stressor and severity of impairment associated with each profile. Method: An LPA and related analyses were conducted on 302 individuals who had sought treatment for interpersonal traumas ranging from chronic trauma (e.g., childhood abuse to single-incident events (e.g., exposure to 9/11 attacks. Results: The LPA revealed three classes of individuals: (1 a complex PTSD class defined by elevated PTSD symptoms as well as disturbances in three domains of self-organization: affective dysregulation, negative self-concept, and interpersonal problems; (2 a PTSD class defined by elevated PTSD symptoms but low scores on the three self-organization symptom domains; and (3 a low symptom class defined by low scores on all symptoms and problems. Chronic trauma was more strongly predictive of complex PTSD than PTSD and, conversely, single-event trauma was more strongly predictive of PTSD. In addition, complex PTSD was associated with greater impairment than PTSD. The LPA analysis was completed both with and without individuals with borderline personality disorder (BPD yielding identical results, suggesting the stability of these classes regardless of BPD comorbidity. Conclusion: Preliminary data support the proposed ICD-11 distinction between PTSD and complex PTSD and support the value of testing the clinical utility of this distinction in field trials. Replication of results is necessary.For the abstract or full text in other languages, please see Supplementary files under Article Tools online

  3. Separate but correlated: The latent structure of space and mathematics across development.

    Science.gov (United States)

    Mix, Kelly S; Levine, Susan C; Cheng, Yi-Ling; Young, Chris; Hambrick, D Zachary; Ping, Raedy; Konstantopoulos, Spyros

    2016-09-01

    The relations among various spatial and mathematics skills were assessed in a cross-sectional study of 854 children from kindergarten, third, and sixth grades (i.e., 5 to 13 years of age). Children completed a battery of spatial mathematics tests and their scores were submitted to exploratory factor analyses both within and across domains. In the within domain analyses, all of the measures formed single factors at each age, suggesting consistent, unitary structures across this age range. Yet, as in previous work, the 2 domains were highly correlated, both in terms of overall composite score and pairwise comparisons of individual tasks. When both spatial and mathematics scores were submitted to the same factor analysis, the 2 domain specific factors again emerged, but there also were significant cross-domain factor loadings that varied with age. Multivariate regressions replicated the factor analysis and further revealed that mental rotation was the best predictor of mathematical performance in kindergarten, and visual-spatial working memory was the best predictor of mathematical performance in sixth grade. The mathematical tasks that predicted the most variance in spatial skill were place value (K, 3rd, 6th), word problems (3rd, 6th), calculation (K), fraction concepts (3rd), and algebra (6th). Thus, although spatial skill and mathematics each have strong internal structures, they also share significant overlap, and have particularly strong cross-domain relations for certain tasks. (PsycINFO Database Record

  4. Characteristics of Non-Opioid Substance Misusers Among Patients Enrolling in Opioid Treatment Programs: A Latent Class Analysis.

    Science.gov (United States)

    Fong, Chunki; Matusow, Harlan; Cleland, Charles M; Rosenblum, Andrew

    2015-01-01

    Using latent class analysis, this study examined the pattern of non-opioid substance misuse among 19,101 enrollees into 85 opioid treatment programs. The most frequent non-opioid drugs were cannabis, anti-anxiety medications, and cocaine. Four non-opioid drug use latent classes were identified: low-use (73%), prescription drug use (16%), marijuana and cocaine use (8.5%), and poly-drug use (2.5%). Compared to the low-use class, participants in the other classes were more likely to be female, Caucasian, use tobacco, have chronic pain, and use prescription opioids either with or without heroin. Recognition of characteristics derived from these classes can improve opioid treatment program services.

  5. Identifying Subgroups of Adult Superutilizers in an Urban Safety-Net System Using Latent Class Analysis: Implications for Clinical Practice.

    Science.gov (United States)

    Rinehart, Deborah J; Oronce, Carlos; Durfee, Michael J; Ranby, Krista W; Batal, Holly A; Hanratty, Rebecca; Vogel, Jody; Johnson, Tracy L

    2016-09-14

    Patients with repeated hospitalizations represent a group with potentially avoidable utilization. Recent publications have begun to highlight the heterogeneity of this group. Latent class analysis provides a novel methodological approach to utilizing administrative data to identify clinically meaningful subgroups of patients to inform tailored intervention efforts. The objective of the study was to identify clinically distinct subgroups of adult superutilizers. Retrospective cohort analysis. Adult patients who had an admission at an urban safety-net hospital in 2014 and 2 or more admissions within the preceding 12 months. Patient-level medical, mental health (MH) and substance use diagnoses, social characteristics, demographics, utilization and charges were obtained from administrative data. Latent class analyses were used to determine the number and characteristics of latent subgroups that best represented these data. In this cohort (N=1515), a 5-class model was preferred based on model fit indices, clinical interpretability and class size: class 1 (16%) characterized by alcohol use disorder and homelessness; class 2 (14%) characterized by medical conditions, MH/substance use disorders and homelessness; class 3 (25%) characterized primarily by medical conditions; class 4 (13%) characterized by more serious MH disorders, drug use disorder and homelessness; and class 5 (32%) characterized by medical conditions with some MH and substance use. Patient demographics, utilization, charges and mortality also varied by class. The overall cohort had high rates of multiple chronic medical conditions, MH, substance use disorders, and homelessness. However, the patterns of these conditions were different between subgroups, providing important information for tailoring interventions.

  6. Longitudinal burnout-collaboration patterns in Japanese medical care workers at special needs schools: a latent class growth analysis.

    Science.gov (United States)

    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.

  7. Latent profile analysis of regression-based norms demonstrates relationship of compounding MS symptom burden and negative work events.

    Science.gov (United States)

    Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B

    2016-10-01

    We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.

  8. Family income trajectory during childhood is associated with adiposity in adolescence: a latent class growth analysis

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    Kendzor Darla E

    2012-08-01

    Full Text Available Abstract Background Childhood socioeconomic disadvantage has been linked with obesity in cross-sectional research, although less is known about how changes in socioeconomic status influence the development of obesity. Researchers have hypothesized that upward socioeconomic mobility may attenuate the health effects of earlier socioeconomic disadvantage; while downward socioeconomic mobility might have a negative influence on health despite relative socioeconomic advantages at earlier stages. The purpose of the current study was to characterize trajectories of family income during childhood, and to evaluate the influence of these trajectories on adiposity at age 15. Methods Data were collected as part of the Study of Early Child Care and Youth Development (SECCYD between 1991 and 2007 at 10 sites across the United States. A latent class growth analysis (LCGA was conducted to identify trajectories of family income from birth to 15 years of age. Analyses of covariance (ANCOVAs were conducted to determine whether measures of adiposity differed by trajectory, while controlling for relevant covariates. Results The LCGA supported a 5-class trajectory model, which included two stable, one downward, and two upward trajectories. ANCOVAs indicated that BMI percentile, waist circumference, and skinfold thicknesses at age 15 differed significantly by trajectory, such that those who experienced downward mobility or stable low income had greater adiposity relative to the more advantaged trajectories. Conversely, upwardly mobile children and those with consistently adequate incomes had similar and more positive outcomes relative to the most disadvantaged trajectories. Conclusions Findings suggest that promoting upward socioeconomic mobility among disadvantaged families may have a positive impact on obesity-related outcomes in adolescence.

  9. Attachment typologies and posttraumatic stress disorder (PTSD, depression and anxiety: a latent profile analysis approach

    Directory of Open Access Journals (Sweden)

    Cherie Armour

    2011-12-01

    Full Text Available Bartholomew (1990 proposed a four category adult attachment model based on Bowlby's (1973 proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS. In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990. Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. A large sample of Danish trauma victims (N=1577 participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. The three class solution was considered optimal. Class one was termed Fearful (18.6%, Class two Preoccupied (34.5%, and Class three Secure (46.9%. The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display lower levels of psychopathology post

  10. Neuropsychological Subgroups in Non-Demented Parkinson's Disease: A Latent Class Analysis.

    Science.gov (United States)

    Brennan, Laura; Devlin, Kathryn M; Xie, Sharon X; Mechanic-Hamilton, Dawn; Tran, Baochan; Hurtig, Howard H; Chen-Plotkin, Alice; Chahine, Lama M; Morley, James F; Duda, John E; Roalf, David R; Dahodwala, Nabila; Rick, Jacqueline; Trojanowski, John Q; Moberg, Paul J; Weintraub, Daniel

    2017-01-01

    Methods to detect early cognitive decline and account for heterogeneity of deficits in Parkinson's disease (PD) are needed. Quantitative methods such as latent class analysis (LCA) offer an objective approach to delineate discrete phenotypes of impairment. To identify discrete neurocognitive phenotypes in PD patients without dementia. LCA was applied to a battery of 8 neuropsychological measures to identify cognitive subtypes in a cohort of 199 non-demented PD patients. Two measures were analyzed from each of four domains: executive functioning, memory, visuospatial abilities, and language. Additional analyses compared groups on clinical characteristics and cognitive diagnosis. LCA identified 3 distinct groups of PD patients: an intact cognition group (54.8%), an amnestic group (32.2%), and a mixed impairment group with dysexecutive, visuospatial and lexical retrieval deficits (13.1%). The two impairment groups had significantly lower instrumental activities of daily living ratings and greater motor symptoms than the intact group. Of those diagnosed as cognitively normal according to MDS criteria, LCA classified 23.2% patients as amnestic and 9.9% as mixed cognitive impairment. Non-demented PD patients exhibit distinct neuropsychological profiles. One-third of patients with LCA-determined impairment were diagnosed as cognitively intact by expert consensus, indicating that classification using a statistical algorithm may improve detection of initial and subtle cognitive decline. This study also demonstrates that memory impairment is common in non-demented PD even when cognitive impairment is not clinically apparent. This study has implications for predicting eventual emergence of significant cognitive decline, and treatment trials for cognitive dysfunction in PD.

  11. Diagnostic performance of various tests and criteria employed in allergic bronchopulmonary aspergillosis: a latent class analysis.

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    Ritesh Agarwal

    Full Text Available AIM: The efficiency of various investigations and diagnostic criteria used in diagnosis of allergic bronchopulmonary aspergillosis (ABPA remain unknown, primarily because of the lack of a gold standard. Latent class analysis (LCA can provide estimates of sensitivity and specificity in absence of gold standard. Herein, we report the performance of various investigations and criteria employed in diagnosis of ABPA. METHODS: Consecutive subjects with asthma underwent all the following investigations Aspergillus skin test, IgE levels (total and A.fumigatus specific, Aspergillus precipitins, eosinophil count, chest radiograph, and high-resolution computed tomography (HRCT of the chest. We used LCA to estimate the performance of various diagnostic tests and criteria in identification of ABPA. RESULTS: There were 372 asthmatics with a mean age of 35.9 years. The prevalence of Aspergillus sensitization was 53.2%. The sensitivity and specificity of various tests were Aspergillus skin test positivity (94.7%, 79.7%; IgE levels>1000 IU/mL (97.1%, 37.7%; A.fumigatus specific IgE levels>0.35 kUA/L (100%, 69.3%; Aspergillus precipitins (42.7%, 97.1%; eosinophil count>1000 cells/µL (29.5%, 93.1%; chest radiographic opacities (36.1%, 92.5%; bronchiectasis (91.9%, 80.9%; and, high-attenuation mucus (39.7%, 100%. The most accurate criteria was the Patterson criteria using six components followed by the Agarwal criteria. However, there was substantial decline in accuracy of the Patterson criteria if components of the criteria were either increased or decreased from six. CONCLUSIONS: A.fumigatus specific IgE levels and high-attenuation mucus were found to be the most sensitive and specific test respectively in diagnosis of ABPA. The Patterson criteria remain the best diagnostic criteria however they have good veridicality only if six criteria are used.

  12. Attachment typologies and posttraumatic stress disorder (PTSD), depression and anxiety: a latent profile analysis approach

    Science.gov (United States)

    Armour, Cherie; Elklit, Ask; Shevlin, Mark

    2011-01-01

    Background Bartholomew (1990) proposed a four category adult attachment model based on Bowlby's (1973) proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS). In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. Objective The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990). Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. Method A large sample of Danish trauma victims (N=1577) participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. Results The three class solution was considered optimal. Class one was termed Fearful (18.6%), Class two Preoccupied (34.5%), and Class three Secure (46.9%). The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. Conclusions The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display

  13. Treatment engagement in adolescents with severe psychiatric problems: a latent class analysis.

    Science.gov (United States)

    Roedelof, A J M; Bongers, Ilja L; van Nieuwenhuizen, Chijs

    2013-08-01

    Motivation is considered a pivotal factor in treatment, but a better understanding of this topic is needed. Drieschner et al. (Clin Psychol Rev 23:1115-1137, 2004) proposed to distinguish treatment motivation and treatment engagement. This study aimed to discover whether it is possible to identify classes of adolescents with severe psychiatric problems having comparable profiles of treatment engagement. To this end, professionals filled out the Treatment Engagement Rating Scale 5 times for 49 adolescents (mean age 18.3 years; SD = 1.6) during the first year of case management treatment. Using a longitudinal latent class analysis, the number of profiles of treatment engagement was investigated and described. Results identified three profiles: high (19 clients, 39%), medium (20 clients, 41%) and low (10 clients, 20%). Adolescents with a high engagement profile were at first equally, and later on more engaged in treatment than clients with a medium engagement profile. Adolescents with a low engagement profile made the least effort to engage, except after 30 weeks. Adolescents with a low engagement profile were often substance-dependent males with the lowest scores on the Global Assessment of Functioning Scale after a year. Only adolescents with a high engagement profile improved on global functioning. In conclusion, it is possible to identify different treatment engagement profiles by asking one question about level of global treatment engagement. Frequent assessment of engagement of the individual client as well as including a behavioural component into assessment and treatment may help to improve case management treatment for adolescents with medium and low engagement profiles.

  14. Polytobacco, marijuana, and alcohol use patterns in college students: A latent class analysis.

    Science.gov (United States)

    Haardörfer, Regine; Berg, Carla J; Lewis, Michael; Payne, Jackelyn; Pillai, Drishti; McDonald, Bennett; Windle, Michael

    2016-08-01

    Limited research has examined polysubstance use profiles among young adults focusing on the various tobacco products currently available. We examined use patterns of various tobacco products, marijuana, and alcohol using data from the baseline survey of a multiwave longitudinal study of 3418 students aged 18-25 recruited from seven U.S. college campuses. We assessed sociodemographics, individual-level factors (depression; perceptions of harm and addictiveness,), and sociocontextual factors (parental/friend use). We conducted a latent class analysis and multivariable logistic regression to examine correlates of class membership (Abstainers were referent group). Results indicated five classes: Abstainers (26.1% per past 4-month use), Alcohol only users (38.9%), Heavy polytobacco users (7.3%), Light polytobacco users (17.3%), and little cigar and cigarillo (LCC)/hookah/marijuana co-users (10.4%). The most stable was LCC/hookah/marijuana co-users (77.3% classified as such in past 30-day and 4-month timeframes), followed by Heavy polytobacco users (53.2% classified consistently). Relative to Abstainers, Heavy polytobacco users were less likely to be Black and have no friends using alcohol and perceived harm of tobacco and marijuana use lower. Light polytobacco users were older, more likely to have parents using tobacco, and less likely to have friends using tobacco. LCC/hookah/marijuana co-users were older and more likely to have parents using tobacco. Alcohol only users perceived tobacco and marijuana use to be less socially acceptable, were more likely to have parents using alcohol and friends using marijuana, but less likely to have friends using tobacco. These findings may inform substance use prevention and recovery programs by better characterizing polysubstance use patterns.

  15. Concurrent Associations of Physical Activity and Screen-Based Sedentary Behavior on Obesity Among US Adolescents: A Latent Class Analysis

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    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.

  16. Group Lasso with Overlaps: the Latent Group Lasso approach

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    Obozinski, Guillaume; Vert, Jean-Philippe

    2011-01-01

    We study a norm for structured sparsity which leads to sparse linear predictors whose supports are unions of prede ned overlapping groups of variables. We call the obtained formulation latent group Lasso, since it is based on applying the usual group Lasso penalty on a set of latent variables. A detailed analysis of the norm and its properties is presented and we characterize conditions under which the set of groups associated with latent variables are correctly identi ed. We motivate and discuss the delicate choice of weights associated to each group, and illustrate this approach on simulated data and on the problem of breast cancer prognosis from gene expression data.

  17. A mixture model for the joint analysis of latent developmental trajectories and survival

    NARCIS (Netherlands)

    Klein Entink, R.H.; Fox, J.P.; Hout, A. van den

    2011-01-01

    A general joint modeling framework is proposed that includes a parametric stratified survival component for continuous time survival data, and a mixture multilevel item response component to model latent developmental trajectories given mixed discrete response data. The joint model is illustrated in

  18. A mixture model for the joint analysis of latent developmental trajectories and survival

    NARCIS (Netherlands)

    Klein Entink, R.H.; Fox, J.P.; Hout, A. van den

    2011-01-01

    A general joint modeling framework is proposed that includes a parametric stratified survival component for continuous time survival data, and a mixture multilevel item response component to model latent developmental trajectories given mixed discrete response data. The joint model is illustrated in

  19. Latent Profile Analysis of Good Citizenship of Rajabhat Universities' Students in the Northeast of Thailand

    Science.gov (United States)

    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…

  20. Capitalism and Crime in the Classroom: An Analysis of Academic Dishonesty and Latent Student Attitudes

    Science.gov (United States)

    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.…

  1. Measures of Reading Comprehension: A Latent Variable Analysis of the Diagnostic Assessment of Reading Comprehension

    Science.gov (United States)

    Francis, David J.; Snow, Catherine E.; August, Diane; Carlson, Coleen D.; Miller, Jon; Iglesias, Aquiles

    2006-01-01

    This study compares 2 measures of reading comprehension: (a) the Woodcock-Johnson Passage Comprehension test, a standard in reading research, and (b) the Diagnostic Assessment of Reading Comprehension (DARC), an innovative measure. Data from 192 Grade 3 Spanish-speaking English language learners (ELLs) were used to fit a series of latent variable…

  2. Parent Involvement and Science Achievement: A Cross-Classified Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    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…

  3. The Latent Curve ARMA (P, Q) Panel Model: Longitudinal Data Analysis in Educational Research and Evaluation

    Science.gov (United States)

    Sivo, Stephen; Fan, Xitao

    2008-01-01

    Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…

  4. Capitalism and Crime in the Classroom: An Analysis of Academic Dishonesty and Latent Student Attitudes

    Science.gov (United States)

    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.…

  5. The Relationship of Perfectionism, Depression, and Therapeutic Alliance during Treatment for Depression: Latent Difference Score Analysis

    Science.gov (United States)

    Hawley, Lance L.; Ho, Moon-Ho Ringo; Zuroff, David C.; Blatt, Sidney J.

    2006-01-01

    The authors examined the longitudinal relationship of patient-rated perfectionism, clinician-rated depression, and observer-rated therapeutic alliance using the latent difference score (LDS) analytic framework. Outpatients involved in the Treatment for Depression Collaborative Research Program completed measures of perfectionism and depression at…

  6. Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

    Science.gov (United States)

    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.

  7. Schizophrenia with prominent catatonic features ('catatonic schizophrenia') III. Latent class analysis of the catatonic syndrome.

    Science.gov (United States)

    Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Lee, Edwin; Gerevich, Jozsef

    2009-02-01

    No reports have yet been published on catatonia using latent class analysis (LCA). This study applied LCA to a large, diagnostically homogenous sample of patients with chronic schizophrenia who also presented with catatonic symptoms. A random sample of 225 Chinese inpatients with DSM-IV schizophrenia was selected from the long-stay wards of a psychiatric hospital. Their psychopathology, extrapyramidal motor status and level of functioning were evaluated with standardized rating scales. Catatonia was rated using a modified version of the Bush-Francis Catatonia Rating Scale. LCA was then applied to the 178 patients who presented with at least one catatonic sign. In LCA a four-class solution was found to fit best the statistical model. Classes 1, 2, 3 and 4 constituted 18%, 39.4%, 20.1% and 22.5% of the whole catatonic sample, respectively. Class 1 included patients with symptoms of 'automatic' phenomena (automatic obedience, Mitgehen, waxy flexibility). Class 2 comprised patients with 'repetitive/echo' phenomena (perseveration, stereotypy, verbigeration, mannerisms and grimacing). Class 3 contained patients with symptoms of 'withdrawal' (immobility, mutism, posturing, staring and withdrawal). Class 4 consisted of 'agitated/resistive' patients, who displayed symptoms of excitement, impulsivity, negativism and combativeness. The symptom composition of these 4 classes was nearly identical with that of the four factors identified by factor analysis in the same cohort of subjects in an earlier study. In multivariate regression analysis, the 'withdrawn' class was associated with higher scores on the Scale of Assessment of Negative Symptoms and lower and higher scores for negative and positive items respectively on the Nurses' Observation Scale for Inpatient Evaluation's (NOSIE). The 'automatic' class was associated with lower values on the Simpson-Angus Extrapyramidal Side Effects Scale, and the 'repetitive/echo' class with higher scores on the NOSIE positive items. These

  8. Structural equation modeling of latent growth curves of weight gain among treated tuberculosis patients.

    Directory of Open Access Journals (Sweden)

    Mahalingam Vasantha

    Full Text Available Tuberculosis still remains a major public health problem even though it is treatable and curable. Weight gain measurement during anti tuberculosis (TB treatment period is an important component to assess the progress of TB patients. In this study, Latent Growth Models (LGMs were implemented in a longitudinal design to predict the change in weight of TB patients who were given three different regimens under randomized controlled clinical trial for anti-TB treatment. Linear and Quadratic LGMs were fitted using Mplus software. The age, sex and treatment response of the TB patients were used as time invariant independent variables of the growth trajectories. The quadratic trend was found to be better in explaining the changes in weight without grouping than the quadratic model for three group comparisons. A significant increase in the change of weight over time was identified while a significant quadratic effect indicated that weights were sustained over time. The growth rate was similar in both the groups. The treatment response had significant association with the growth rate of weight scores of the patients.

  9. Retrieving latent heating vertical structure from cloud and precipitation Profiles—Part I: Warm rain processes

    Science.gov (United States)

    Min, Qilong; Li, Rui; Wu, Xiaoqing; Fu, Yunfei

    2013-06-01

    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.

  10. Job Satisfaction among Health-Care Staff in Township Health Centers in Rural China: Results from a Latent Class Analysis.

    Science.gov (United States)

    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.

  11. Latent class analysis of reading, decoding, and writing performance using the Academic Performance Test: concurrent and discriminating validity.

    Science.gov (United States)

    Cogo-Moreira, Hugo; Carvalho, Carolina Alves Ferreira; de Souza Batista Kida, Adriana; de Avila, Clara Regina Brandão; Salum, Giovanni Abrahão; Moriyama, Tais Silveira; Gadelha, Ary; Rohde, Luis Augusto; de Moura, Luciana Monteiro; Jackowski, Andrea Parolin; de Jesus Mari, Jair

    2013-01-01

    To explore and validate the best returned latent class solution for reading and writing subtests from the Academic Performance Test (TDE). 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). 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. A three-class solution was found to be the best model solution, revealing classes of children with good, not-so-good, or poor performance on TDE reading and writing tasks. The three-class solution has been shown to be correlated with estimated IQ and to ADHD diagnosis. No association was observed between the latent class and major depression. The three-class solution showed both concurrent and discriminant validity. This work provides initial evidence of validity for an empirically derived categorical classification of reading, decoding, and writing performance using the TDE. A valid classification encourages further research investing correlates of reading and writing performance using the TDE.

  12. Latent class analysis of reading, decoding, and writing performance using the Academic Performance Test: concurrent and discriminating validity

    Science.gov (United States)

    Cogo-Moreira, Hugo; Carvalho, Carolina Alves Ferreira; de Souza Batista Kida, Adriana; de Avila, Clara Regina Brandão; Salum, Giovanni Abrahão; Moriyama, Tais Silveira; Gadelha, Ary; Rohde, Luis Augusto; de Moura, Luciana Monteiro; Jackowski, Andrea Parolin; de Jesus Mari, Jair

    2013-01-01

    Aim 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-so-good, or poor performance on TDE reading and writing tasks. The three-class solution has been shown to be correlated with estimated IQ and to ADHD diagnosis. No association was observed between the latent class and major depression. Conclusion The three-class solution showed both concurrent and discriminant validity. This work provides initial evidence of validity for an empirically derived categorical classification of reading, decoding, and writing performance using the TDE. A valid classification encourages further research investing correlates of reading and writing performance using the TDE. PMID:23983466

  13. [Comparison of several expressions of two-way ANOVA for a latent factor: analysis of the relation between music and mood].

    Science.gov (United States)

    Ozaki, Koken; Toyoda, Hideki

    2005-06-01

    The purpose of this research is to provide a two-way analysis of variance (ANOVA) model for a latent factor. Typical psychological studies measure mental states with questionnaires and analyze the variance of the measures into the portions attributable to various sources. This type of research, when conducted under regular ANOVA designs, uses total score as the dependent measures. However, this method is based on the unrealistic presumption that every item on the questionnaire has the same factor loading on the attribute being measured. In this research, we incorporated factor analysis model, and used a latent factor instead of total score as the dependent measure, thereby applying ANOVA under a more realistic assumption. Structural Equation Modeling (SEM) was used to express statistical models. This paper also examined a relation between music and mood, which is a quite popular area of research in psychology of music. To study the possible effects of tonality and key-signature on mood, music was chosen to represent tonality and key-signature conditions.

  14. Anxiety, bulimia, drug and alcohol addiction, depression, and schizophrenia: what do you think about their aetiology, dangerousness, social distance, and treatment? A latent class analysis approach.

    Science.gov (United States)

    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.

  15. Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables.

    Science.gov (United States)

    Chen, Wenhui; Lei, Yalin

    2017-02-01

    Identifying the impact path on factors of CO2 emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO2 emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO2 emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO2 emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO2 emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO2 emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO2 emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO2 emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.

  16. Sequential Temporal Dependencies in Associations between Symptoms of Depression and Posttraumatic Stress Disorder: An Application of Bivariate Latent Difference Score Structural Equation Modeling

    Science.gov (United States)

    King, Daniel W.; King, Lynda A.; McArdle, John J.; Shalev, Arieh Y.; Doron-LaMarca, Susan

    2009-01-01

    Depression and posttraumatic stress disorder (PTSD) are highly comorbid conditions that may arise following exposure to psychological trauma. This study examined their temporal sequencing and mutual influence using bivariate latent difference score structural equation modeling. Longitudinal data from 182 emergency room patients revealed level of…

  17. SAXS investigation of latent track structure in HDPE irradiated with high energy Fe ions

    Energy Technology Data Exchange (ETDEWEB)

    Hai, Yang; Huang, Can [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Ma, Mingwang [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); Institute of Electronic Engineering, CAEP, Mianyang 621900 (China); Liu, Qi; Wang, Yuzhu; Liu, Yi; Tian, Feng; Lin, Jun [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); Zhu, Zhiyong, E-mail: zhuzhiyong@sinap.ac.cn [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China)

    2015-08-01

    Semi-crystalline high density polyethylene (HDPE) samples were irradiated with 1.157 GeV {sup 56}Fe ion beams to fluences ranging from 1 × 10{sup 11} to 6 × 10{sup 12} ions/cm{sup 2}. The radiation induced changes in nano/microstructure were investigated with small angle X-ray scattering (SAXS) technique. The scattering contributions from HDPE matrix and ion tracks are successfully separated and analyzed through tilted SAXS measurements with respect to the X-ray beam direction. Lorentz correction, one-dimensional correlation function calculation, fractal nature analysis of the isotropic scattering pattern reveal that HDPE long period polymeric structures are damaged and new materials, possibly clusters of carbon-rich materials, are formed inside the ion tracks. Least square curve fitting of the scattering contribution from the ion track reveals that the track is composed of a core of about 5.3 nm in radius, characterized by a significant density deficit compared to the virgin HDPE, surrounded by a shell of about 4.3 nm in thickness with less density reduction.

  18. Transitions in Smokers' Social Networks After Quit Attempts: A Latent Transition Analysis.

    Science.gov (United States)

    Bray, Bethany C; Smith, Rachel A; Piper, Megan E; Roberts, Linda J; Baker, Timothy B

    2016-12-01

    Smokers' social networks vary in size, composition, and amount of exposure to smoking. The extent to which smokers' social networks change after a quit attempt is unknown, as is the relation between quitting success and later network changes. Unique types of social networks for 691 smokers enrolled in a smoking-cessation trial were identified based on network size, new network members, members' smoking habits, within network smoking, smoking buddies, and romantic partners' smoking. Latent transition analysis was used to identify the network classes and to predict transitions in class membership across 3 years from biochemically assessed smoking abstinence. Five network classes were identified: Immersed (large network, extensive smoking exposure including smoking buddies), Low Smoking Exposure (large network, minimal smoking exposure), Smoking Partner (small network, smoking exposure primarily from partner), Isolated (small network, minimal smoking exposure), and Distant Smoking Exposure (small network, considerable nonpartner smoking exposure). Abstinence at years 1 and 2 was associated with shifts in participants' social networks to less contact with smokers and larger networks in years 2 and 3. In the years following a smoking-cessation attempt, smokers' social networks changed, and abstinence status predicted these changes. Networks defined by high levels of exposure to smokers were especially associated with continued smoking. Abstinence, however, predicted transitions to larger social networks comprising less smoking exposure. These results support treatments that aim to reduce exposure to smoking cues and smokers, including partners who smoke. Prior research has shown that social network features predict the likelihood of subsequent smoking cessation. The current research illustrates how successful quitting predicts social network change over 3 years following a quit attempt. Specifically, abstinence predicts transitions to networks that are larger and afford

  19. Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

    Science.gov (United States)

    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…

  20. 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...

  1. Latent class analysis of substance use and aggressive behavior in reservation-based American Indian youth who attempted suicide.

    Science.gov (United States)

    Ballard, Elizabeth D; Musci, Rashelle J; Tingey, Lauren; Goklish, Novalene; Larzelere-Hinton, Francene; Barlow, Allison; Cwik, Mary

    2015-01-01

    American Indian (AI) adolescents who attempt suicide are heterogeneous. A latent class analysis was used to identify subgroups of reservation-based AI adolescents with recent suicide attempts. Indicators of class membership were substance abuse and aggressive behaviors; clinical correlates of subgroup membership included risky sexual behavior and recent exposure to suicidal behavior. Three subgroups were identified, representing low, medium, and high substance use and aggressive behavior. Suicide exposure was associated with membership in the lowest risk behavior subgroup; risky sexual behavior was associated with membership the highest risk behaviors subgroup. Findings suggest a continuum of risk behaviors in reservation-based AI youth who attempt suicide.

  2. The Relations Among Inhibition and Interference Control Functions: A Latent-Variable Analysis

    Science.gov (United States)

    Friedman, Naomi P.; Miyake, Akira

    2004-01-01

    This study used data from 220 adults to examine the relations among 3 inhibition-related functions. Confirmatory factor analysis suggested that Prepotent Response Inhibition and Resistance to Distractor Interference were closely related, but both were unrelated to Resistance to Proactive Interference. Structural equation modeling, which combined…

  3. Understanding the Latent Structure of the Emotional Disorders in Children and Adolescents

    Science.gov (United States)

    Trosper, Sarah E.; Whitton, Sarah W.; Brown, Timothy A.; Pincus, Donna B.

    2012-01-01

    Investigators are persistently aiming to clarify structural relationships among the emotional disorders in efforts to improve diagnostic classification. The high co-occurrence of anxiety and mood disorders, however, has led investigators to portray the current structure of anxiety and depression in the "Diagnostic and Statistical Manual of Mental…

  4. Risk behaviors and drug use: a latent class analysis of heavy episodic drinking in first-year college students.

    Science.gov (United States)

    Chiauzzi, Emil; Dasmahapatra, Pronabesh; Black, Ryan A

    2013-12-01

    Examining individual characteristics may not yield an understanding of the complex array of factors that affect college student alcohol use. Utilizing a latent class analysis, the present study investigated an alcohol and drug use database of first-year college students at 89 U.S. colleges and universities (N = 21,945). These data were collected between December, 2010 and September, 2011. This study identified: (1) classes based on alcohol consumption, alcohol-related behaviors, and past-year use of illegal drugs and nonmedical use of prescriptions medications (NMUPM); (2) demographic covariates of these classes; and (3) differential social norms awareness, perceived harmfulness of illegal drugs and NMUPM, and protective strategies. Four classes were identified: (1) Low Risk Drinking/Low Prevalence Drug Use (Class 1); (2) Lower Intake Drinking/Moderate Prevalence Drug Use (Class 2); (3) Moderate Risk Drinking/Moderate Prevalence Drug Use (Class 3); and (4) High Risk Drinking/High Prevalence Drug Use (Class 4). Classes differed in self-reported typical week drinking, estimated peak blood alcohol content over the past 2 weeks, high-risk alcohol use, negative alcohol-related consequences, driving under the influence or riding with drinking drivers, alcohol-related protective behaviors, and past-year substance use. Of particular interest was the identification of a latent class (Class 2) composed primarily of females with a relatively low alcohol intake, but with a high probability of past-year other substance use. This group reported negative alcohol-related consequences despite their relatively low intake. To our knowledge, this is the first latent class analysis of college student alcohol use that includes a drug use indicator and compares social norms awareness, harmfulness perceptions, and alcohol-related protective behaviors between classes.

  5. Deep web站点查询界面的潜在语义分析%Latent semantic analysis for query interfaces of deep web sites

    Institute of Scientific and Technical Information of China (English)

    茅琴娇; 冯博琴; 潘善亮

    2008-01-01

    为了进一步提高搜索引擎的效率,实现对deep web中所蕴含的大量有用信息的检索、索引和定位,引入潜在语义分析理论是一种简单而有效的方法.通过对作为deep web站点入口的查询界面里的表单属性进行潜在语义分析,从表单属性中挖掘出潜在语义结构,并实现一定程度上的降维.利用这种潜在语义结构,推断对应站点的数据内容并改善不同站点的相似度计算.实验结果显示,潜在语义分析修正和改善了deep web站点的表单属性的语义理解,弥补了单纯的关键字匹配带来的一些不足.该方法可以被用来实现为某一站点查找网络上相似度高的站点及通过键入表单属性给出拥有相似表单的站点列表.%To further enhance the efficiencies of search engines, achieving capabilities of searching, indexing and locating the information in the deep web, latent semantic analysis is a simple and effective way. Through the latent semantic analysis of the attributes in the query interfaces and the unique entrances of the deep web sites, the hidden semantic structure information can be retrieved and dimension reduction can be achieved to a certain extent. Using this semantic structure information, the contents in the site can be inferred and the similarity measures among sites in deep web can be revised. Experimental results show that latent semantic analysis revises and improves the semantic understanding of the query form in the deep web, which overcomes the shortcomings of the keyword-based methods. This approach can be used to effectively search the most similar site for any given site and to obtain a site list which conforms to the restrictions one specifies.

  6. What Do Test Scores Really Mean? A Latent Class Analysis of Danish Test Score Performance

    DEFF Research Database (Denmark)

    Munk, Martin D.; McIntosh, James

    2014-01-01

    Latent class Poisson count models are used to analyze a sample of Danish test score results from a cohort of individuals born in 1954-55, tested in 1968, and followed until 2011. The procedure takes account of unobservable effects as well as excessive zeros in the data. We show that the test scores...... of intelligence explain a significant proportion of the variation in test scores. This adds to the complexity of interpreting test scores and suggests that school culture and possible incentive problems make it more di¢ cult to understand what the tests measure....

  7. A structural equation model to evaluate direct and indirect factors associated with a latent measure of mastitis in Belgian dairy herds.

    Science.gov (United States)

    Detilleux, J; Theron, L; Beduin, J-M; Hanzen, C

    2012-12-01

    In dairy cattle, many farming practices have been associated with occurrence of mastitis but it is often difficult to disentangle the causal threads. Structural equation models may reduce the complexity of such situations. Here, we applied the method to examine the links between mastitis (subclinical and clinical) and risk factors such as herd demographics, housing conditions, feeding procedures, milking practices, and strategies of mastitis prevention and treatment in 345 dairy herds from the Walloon region of Belgium. During the period January 2006 to October 2007, up to 110 different herd management variables were recorded by two surveyors using a questionnaire for the farm managers and during a farm visit. Monthly somatic cell counts of all lactating cows were collected by the local dairy herd improvement association. Structural equation models were created to obtain a latent measure of mastitis and to reduce the complexity of the relationships between farming practices, between indicators of herd mastitis and between both. Robust maximum likelihood estimates were obtained for the effects of the herd management variables on the latent measure of herd mastitis. Variables associated directly (pteat disinfection; the presence of cows with hyperkeratotic teats, of cubicles for housing and of dirty liners before milking; the treatment of subclinical cases of mastitis; and the age of the herd (latent variable for average age and parity of cows, and percentage of heifers in the herd). Treatment of subclinical mastitis was also an intermediate in the association between herd mastitis and post-milking teat disinfection. The study illustrates how structural equation model provides information regarding the linear relationships between risk factors and a latent measure of mastitis, distinguishes between direct relationships and relationships mediated through intermediate risk factors, allows the construction of latent variables and tests the directional hypotheses

  8. The latent structure of personality functioning: Investigating criterion a from the alternative model for personality disorders in DSM-5.

    Science.gov (United States)

    Zimmermann, Johannes; Böhnke, Jan R; Eschstruth, Rhea; Mathews, Alessa; Wenzel, Kristin; Leising, Daniel

    2015-08-01

    The alternative model for the classification of personality disorders (PD) in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) Section III comprises 2 major components: impairments in personality functioning (Criterion A) and maladaptive personality traits (Criterion B). In this study, we investigated the latent structure of Criterion A (a) within subdomains, (b) across subdomains, and (c) in conjunction with the Criterion B trait facets. Data were gathered as part of an online study that collected other-ratings by 515 laypersons and 145 therapists. Laypersons were asked to assess 1 of their personal acquaintances, whereas therapists were asked to assess 1 of their patients, using 135 items that captured features of Criteria A and B. We were able to show that (a) the structure within the Criterion A subdomains can be appropriately modeled using generalized graded unfolding models, with results suggesting that the items are indeed related to common underlying constructs but often deviate from their theoretically expected severity level; (b) the structure across subdomains is broadly in line with a model comprising 2 strongly correlated factors of self- and interpersonal functioning, with some notable deviations from the theoretical model; and (c) the joint structure of the Criterion A subdomains and the Criterion B facets broadly resembles the expected model of 2 plus 5 factors, albeit the loading pattern suggests that the distinction between Criteria A and B is somewhat blurry. Our findings provide support for several major assumptions of the alternative DSM-5 model for PD but also highlight aspects of the model that need to be further refined. (c) 2015 APA, all rights reserved).

  9. Bayesian latent variable models for the analysis of experimental psychology data.

    Science.gov (United States)

    Merkle, Edgar C; Wang, Ting

    2016-03-18

    In this paper, we address the use of Bayesian factor analysis and structural equation models to draw inferences from experimental psychology data. While such application is non-standard, the models are generally useful for the unified analysis of multivariate data that stem from, e.g., subjects' responses to multiple experimental stimuli. We first review the models and the parameter identification issues inherent in the models. We then provide details on model estimation via JAGS and on Bayes factor estimation. Finally, we use the models to re-analyze experimental data on risky choice, comparing the approach to simpler, alternative methods.

  10. Math Anxiety Questionnaire: Similar Latent Structure in Brazilian and German School Children

    Directory of Open Access Journals (Sweden)

    Guilherme Wood

    2012-01-01

    Full Text Available Math anxiety is a relatively frequent phenomenon often related to low mathematics achievement and dyscalculia. In the present study, the German and the Brazilian versions of the Mathematics Anxiety Questionnaire (MAQ were examined. The two-dimensional structure originally reported for the German MAQ, that includes both affective and cognitive components of math anxiety was reproduced in the Brazilian version. Moreover, mathematics anxiety also was found to increase with age in both populations and was particularly associated with basic numeric competencies and more complex arithmetics. The present results suggest that mathematics anxiety as measured by the MAQ presents the same internal structure in culturally very different populations.

  11. Do Gender and Exposure to Interparental Violence Moderate the Stability of Teen Dating Violence?: Latent Transition Analysis.

    Science.gov (United States)

    Choi, Hye Jeong; Temple, Jeff R

    2016-04-01

    This study investigates the development, change, and stability of teen dating violence (TDV) victimization over time. Specifically, we identify distinct subgroups of adolescents based on past-year TDV victimization, whether adolescents change victimization statuses over time (e.g., from psychological victimization to physical victimization), and how exposure to interparental violence and gender influence the prevalence and stability of TDV statuses. Adolescents (N=1,042) from 7 public high schools in Texas participated in this longitudinal study. The Conflict in Adolescent Dating Relationships Inventory (CADRI) (Wolfe et al., Psychological Assessment, 13(2), 277-293, 2001) was used to identify victimization statuses. Latent Transition Analysis (LTA) with measurement invariance was used to examine transition probability of an individual's latent status at Wave3 or Wave4 given his or her latent status at Wave2 or Wave3. Gender and exposure to interparental violence was included as moderators in the LTA. Three statuses of TDV victimization were identified: (1) non-victims; (2) emotional/verbal victims; and (3) physical/psychological victims. LTA showed that the majority of adolescents stayed in the same status over time; however, female youth exposed to interparental violence were more likely to move from a less to more severe status over time compared to non-exposed youth. This is among the first study to identify subgroups of TDV victimization and to examine the stability of group membership over time. Female youth exposed to interparental violence were more likely to remain in or move into a violent relationship compared to unexposed youth.

  12. Examining patterns of political, social service, and collaborative involvement of religious congregations: a latent class and transition analysis.

    Science.gov (United States)

    Todd, Nathan R; Houston, Jaclyn D

    2013-06-01

    This investigation examines typologies of congregations based on patterns of congregational political and social service activities and collaborative partners. Based on a latent class analysis of a national random sample of 2,153 congregations, results indicated four distinct types of congregations with unique patterns of political, social service, and collaborative partnerships labeled: (a) Active, (b) Not Active, (c) Social Service Not Political, and (d) Political Not Social Service. Moreover, congregational characteristics such as religious tradition and clergy characteristics predicted membership in certain types. A latent transition analysis using an additional 262 congregations revealed distinct patterns of how congregations changed types across a nine year period. Results showed both congregational continuity (e.g., Not Active congregations remained Not Active) and change (e.g., Active congregations were likely to change type membership). This study advances congregational research by examining congregational types, what predicts certain types, and how congregations change types across time. Implications for future research and partnership with religious congregations also are discussed.

  13. Maltreatment histories of foster youth exiting out-of-home care through emancipation: a latent class analysis.

    Science.gov (United States)

    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.

  14. Priorities of Municipal Policy Makers in Relation to Physical Activity and the Built Environment: A Latent Class Analysis.

    Science.gov (United States)

    Wang, Monica L; Goins, Karin Valentine; Anatchkova, Milena; Brownson, Ross C; Evenson, Kelly; Maddock, Jay; Clausen, Kristian E; Lemon, Stephenie C

    2016-01-01

    To examine policy makers' public policy priorities related to physical activity and the built environment, identify classes of policy makers based on priorities using latent class analysis, and assess factors associated with class membership. Cross-sectional survey data from municipal officials in 94 cities and towns across 6 US states were analyzed. Participants (N = 423) were elected or appointed municipal officials spanning public health, planning, transportation/public works, community and economic development, parks and recreation, and city management. Participants rated the importance of 11 policy areas (public health, physical activity, obesity, economic development, livability, climate change, air quality, natural resource conservation, traffic congestion, traffic safety, and needs of vulnerable populations) in their daily job responsibilities. Latent class analysis was used to determine response patterns and identify distinct classes based on officials' priorities. Logistic regression models assessed participant characteristics associated with class membership. Four classes of officials based on policy priorities emerged: (1) economic development and livability; (2) economic development and traffic concerns; (3) public health; and (4) general (all policy areas rated as highly important). Compared with class 4, officials in classes 1 and 3 were more likely to have a graduate degree, officials in class 2 were less likely to be in a public health job/department, and officials in class 3 were more likely to be in a public health job/department. Findings can guide public health professionals in framing discussions with policy makers to maximize physical activity potential of public policy initiatives, particularly economic development.

  15. The Latent Symptom Structure of the Beck Depression Inventory-II in Outpatients with Major Depression

    Science.gov (United States)

    Quilty, Lena C.; Zhang, K. Anne; Bagby, R. Michael

    2010-01-01

    The Beck Depression Inventory-II (BDI-II) is a self-report instrument frequently used in clinical and research settings to assess depression severity. Although investigators have examined the factor structure of the BDI-II, a clear consensus on the best fitting model has not yet emerged, resulting in different recommendations regarding how to best…

  16. A Latent Class Analysis to Empirically Describe Eating Disorders through Developmental Stages

    Science.gov (United States)

    Swanson, Sonja A.; Horton, Nicholas J.; Crosby, Ross D.; Micali, Nadia; Sonneville, Kendrin R.; Eddy, Kamryn; Field, Alison E.

    2014-01-01

    Objectives The current standards for classifying eating disorders were primarily informed by adult, clinical study populations, while it is unknown whether an empirically based classification system can be supported across preadolescence through young adulthood. Using latent class analyses, we sought to empirically classify disordered eating in females from preadolescence to young adulthood, and assess the association between classes and adverse outcomes. Methods Latent class models were fit using observations from the 9,039 girls participating in the Growing Up Today Study, an on-going cohort following participants annually or biennially since 1996 when they were ages 9–14 years. Associations between classes and drug use, binge drinking, and depressive symptoms were assessed using generalized estimating equations. Results Across age groups, there was evidence of six classes: a large asymptomatic class, a class characterized by shape/weight concerns, a class characterized by overeating without loss of control, and three resembling full and subthreshold binge eating disorder, purging disorder, and bulimia nervosa. Relative prevalences of classes varied across developmental stages, with symptomatic classes increasing in prevalence with increasing age. Symptomatic classes were associated with concurrent and incident drug use, binge drinking, and high depressive symptoms. Discussion A classification system resembling broader definitions of DSM-5 diagnoses along with two further subclinical symptomatic classes may be a useful framework for studying disordered eating among adolescent and young adult females. PMID:24909947

  17. Understanding Students’ Instrumental Goals, Motivation Deficits and Achievement: Through the Lens of a Latent Profile Analysis

    Directory of Open Access Journals (Sweden)

    Luke K. Fryer

    2016-07-01

    Full Text Available Building on the future oriented and regulated nature of instrumental goals, Lens and colleagues developed a 2 (proximal-distal x 2 (internal-external motivational framework. The current study aimed to test this framework from a person-centred perspective, while equally taking into account students’ lack of motivation as to extend the empirical and theoretical borders of the model. Latent Profile Analyses were used to test the viability of two to five motivational profiles among Japanese second-year students ('N' = 781. A solution with three latent subgroups fitted the sample best, explaining 6% to 62% of the variance in the measured variables. The profiles were labelled “low future oriented motivational profile”, “average motivated profile”, and “highly motivated profile”. The highly motivated subgroup reported the most adaptive pattern of motivation and highest levels of deep level learning, while few differences were found for surface learning and GPA. Theoretical and practical implications are discussed.

  18. Geertz versus Levi-Strauss: latent structural dispositions in Geertz "theory of culture"?

    Directory of Open Access Journals (Sweden)

    Gordana Gorunović

    2016-02-01

    Full Text Available These are two authors, in Foucauldian terms that certainly belong to the most influential individuals in socio-cultural anthropology, as well as in the social sciences and interdisciplinary research more broadly. Claude Levi- Strauss became some kind of an "intellectual hero" during the domination of structuralism in the mid-twentieth century and during the 1960s, while Clifford Geertz was an ‘icon and ambassador’ of anthropology in the second half of the twentieth century. They are both one of the founders of the discourse theory. They not only established a distinct theoretical approaches and methods – structural (Levi-Strauss and interpretative anthropology (Clifford Geertz, but through their intellectual authority they also inspired paradigms and intellectual movements making structuralism and "interpretation of culture" more than some passing episodes in the history of social though (in terms of "trendy ideas". My aim is to make some parallels between these two authors, who despite all the differences that are evident in their epistemological discourses, theoretical approaches and methods (as well as in their ethnographic and anthropological writings itself still have some similarities in their theorisation and interpretation of culture, which I would like to stress in this paper.

  19. A Latent Variable Approach to Determining the Structure of Executive Function in Preschool Children

    Science.gov (United States)

    Miller, Michael R.; Giesbrecht, Gerald F.; Muller, Ulrich; McInerney, Robert J.; Kerns, Kimberly A.

    2012-01-01

    The composition of executive function (EF) in preschool children was examined using confirmatory factor analysis (CFA). A sample of 129 children between 3 and 5 years of age completed a battery of EF tasks. Using performance indicators of working memory and inhibition similar to previous CFA studies with preschoolers, we replicated a unitary EF…

  20. Relationship types among adolescent parents participating in a home-visiting program: A latent-transition analysis.

    Science.gov (United States)

    Raskin, Maryna; Fosse, Nathan E; Fauth, Rebecca C; Bumgarner, Erin; Easterbrooks, M Ann

    2016-04-01

    Young parents (less than 25 years of age) have been shown to have especially low rates of father involvement and union stability. However, research has also shown that parenting experiences of young fathers may not be uniform. There is a need for more research that assesses both the multidimensionality of relationship typologies and their temporality. Using a large longitudinal sample of low-income, young mothers enrolled in a randomized control study of a home-visitation program (n = 704; 61% program, 39% control), we evaluated how mother-father relationship dynamics changed over time. Ten mother-reported indicators of relationships (e.g., coresidence, marital status, types of father support) were used to conduct a latent-class analysis of relationship types. A 4-class solution was identified at each time point: Single Parent, Supportive Nonresident Partner, Supportive Resident Partner, and Questioning/Ambivalent Coupling. Latent-transition analyses were used to evaluate stability of relationships across 2 years. At each transition, a large proportion of women moved from one relationship class to another, indicating heterogeneity in relationship dynamics of adolescent parents. Results revealed the potential of a home-visiting program targeted at young parents to favorably promote more stable and supportive mother-father relationships and coparenting arrangements.

  1. Original article Exploring somatization types among patients in Indonesia: latent class analysis using the Adult Symptom Inventory

    Directory of Open Access Journals (Sweden)

    Wahyu Widhiarso

    2014-12-01

    Full Text Available Background The aim of this study was to explore somatization types by reducing patient complaints to their most basic and parsimonious characteristics. We hypothesized that there were latent groups representing distinct types of somatization. Participants and procedure Data were collected from patients undergoing both inpatient and outpatient treatment at two hospitals in Yogyakarta, Indonesia (N = 212. Results Results from latent class analysis revealed four classes of somatization: two classes (Classes 1 and 2 referring to levels of somatization and two classes (Classes 3 and 4 referring to unique types of somatization. The first two classes (Classes 1 and 2; low and high levels of somatization, respectively corresponded to the number of different symptoms that patients reported out of the list of physical symptoms in the Adult Symptom Inventory. The second two classes (Classes 3 and 4; non-serious and critical complaints, respectively corresponded to two different sets of symptoms. Patients in Class 3 tended to report temporary mild complaints that are common in daily life, such as dizziness, nausea, and stomach pain. Patients in Class 4 tended to report severe complaints and medical problems that require serious treatment or medication, such as deafness or blindness. Conclusions The present study do confirm somatization as a unidimensional experience reflecting a general tendency to report somatic symptoms, but rather support the understanding of somatization as a multidimensional construct.

  2. Physicians' perception of demand-induced supply in the information age: a latent class model analysis.

    Science.gov (United States)

    Shih, Ya-Chen Tina; Tai-Seale, Ming

    2012-03-01

    This paper introduces a concept called 'demand-induced supply' that reflects the excess supply of services due to an increase in demand initiated by patients. We examine its association with the proportion of information-savvy patients in physicians' practice. Using data from a national representative physician survey, we apply latent class models to analyze this association. Our analyses categorize physicians into three 'types' according to the frequency with which they provided additional medical services at their patients' requests: frequent, occasional, and rare. The proportion of information-savvy patients is significantly and positively correlated with demand-induced supply for the frequent or occasional type, but not among physicians in the rare type. Efforts to contain healthcare costs through utilization control need to recognize the pattern of responses from physicians who treat an increasing number of information-savvy patients. Copyright © 2011 John Wiley & Sons, Ltd.

  3. The Different Facets of Work Stress: A Latent Profile Analysis of Nurses' Work Demands.

    Science.gov (United States)

    Jenull, Brigitte B; Wiedermann, Wolfgang

    2015-10-01

    Work-related stress has been identified as a relevant problem leading to negative effects on health and quality of life. Using data from 844 nurses, latent profile analyses (LPA) were applied to identify distinct patterns of work stress. Several sociodemographic variables, including nurses' working and living conditions, as well as nurses' reactions to workload, were considered to predict respondents' profile membership. LPA revealed three distinct profiles that can be distinguished by a low, moderate, and higher stress level. Being financially secure is positively related to the low stress profile, whereas working in an urban area and having low job satisfaction increases the chance of belonging to the higher stress profile. Our results can be used as a basis to develop interventions to create a healthy nursing home environment by supporting the balance between family and work, providing access to job resources and optimizing recovery opportunities. © The Author(s) 2013.

  4. Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: a latent class analysis approach.

    Science.gov (United States)

    Vasilenko, Sara A; Kugler, Kari C; Butera, Nicole M; Lanza, Stephanie T

    2015-04-01

    Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity.

  5. Energy and exergy analysis of particle dispersed latent heat storage system

    Directory of Open Access Journals (Sweden)

    S. Jegadheeswaran, S. D. Pohekar

    2010-05-01

    Full Text Available Latent heat thermal storage (LHTS system has been attractive over the years as an effective energy storage and retrieval device especially in solar thermal applications. However, the performance of LHTS systems is limited by the poor thermal conductivity of phase change materials (PCMs employed. A numerical study is carried out to investigate the performance enhancement of a LHTS unit of shell and tube configuration due to the dispersion of high conductivity particles in the PCM during charging process (melting. Temperature based governing equations have been formulated and solved numerically following an alternate iteration between the temperature and thermal resistance. Exergy based performance evaluation is taken as a main aspect. The numerical results are presented for several mass flow rates and inlet temperatures of heat transfer fluid (HTF. The results indicate a significant improvement in the performance of the LHTS unit when high conductivity particles are dispersed.

  6. Numerical analysis of latent heat storage system with encapsulated phase change material in spherical capsules

    Directory of Open Access Journals (Sweden)

    Bellan Selvan

    2017-01-01

    Full Text Available Solar energy has been considered as one of the promising solutions to replace the fossil fuels. To generate electricity beyond normal daylight hours, thermal energy storage systems (TES play a vital role in concentrated solar power (CSP plants. Thus, a significant focus has been given on the improvement of TES systems from the past few decades. In this study, a numerical model is developed to obtain the detailed heat transfer characteristics of lab-scale latent thermal energy storage system, which consists of molten salt encapsulated spherical capsules and air. The melting process and the corresponding temperature and velocity distributions in every capsule of the system are predicted. The enthalpy-porosity approach is used to model the phase change region. The model is validated with the reported experimental results. Influence of initial condition on the thermal performance of the TES system is predicted.

  7. Patterns of Adolescent Sexual Behavior Predicting Young Adult Sexually Transmitted Infections: A Latent Class Analysis Approach

    Science.gov (United States)

    Vasilenko, Sara A.; Kugler, Kari C.; Butera, Nicole M.; Lanza, Stephanie T.

    2014-01-01

    Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity. PMID:24449152

  8. Gender roles and binge drinking among Latino emerging adults: a latent class regression analysis.

    Science.gov (United States)

    Vaughan, Ellen L; Wong, Y Joel; Middendorf, Katharine G

    2014-09-01

    Gender roles are often cited as a culturally specific predictor of drinking among Latino populations. This study used latent class regression to test the relationships between gender roles and binge drinking in a sample of Latino emerging adults. Participants were Latino emerging adults who participated in Wave III of the National Longitudinal Study of Adolescent Health (N = 2,442). A subsample of these participants (n = 660) completed the Bem Sex Role Inventory--Short. We conducted latent class regression using 3 dimensions of gender roles (femininity, social masculinity, and personal masculinity) to predict binge drinking. Results indicated a 3-class solution. In Class 1, the protective personal masculinity class, personal masculinity (e.g., being a leader, defending one's own beliefs) was associated with a reduction in the odds of binge drinking. In Class 2, the nonsignificant class, gender roles were not related to binge drinking. In Class 3, the mixed masculinity class, personal masculinity was associated with a reduction in the odds of binge drinking, whereas social masculinity (e.g., forceful, dominant) was associated with an increase in the odds of binge drinking. Post hoc analyses found that females, those born outside the United States, and those with greater English language usage were at greater odds of being in Class 1 (vs. Class 2). Males, those born outside the United States, and those with greater Spanish language usage were at greater odds of being in Class 3 (vs. Class 2). Directions for future research and implications for practice with Latino emerging adults are discussed.

  9. Temperature measurements using a projection to latent structures of fluorescence spectra of potassium-aluminum borate glasses with copper-containing molecular clusters

    Science.gov (United States)

    Babkina, A. N.; Khodasevich, M. A.; Shirshnev, P. S.

    2017-02-01

    Luminescence spectra of a potassium-aluminum borate glass with copper-containing molecular clusters are presented in the temperature range of 295-624 K. Two methods of temperature measurement are compared with the aim of evaluating the possibility of their further application in optical temperature sensors: specifically, the classical method of measuring a temperature based on the spectral position of the fluorescence band peak and the measurement method based on projection to latent structures of fluorescence spectra in the visible range. It is shown that, concerning the accuracy of measuring a temperature, the fourdimensional space of latent structures is preferred for the case under consideration; it allows one to determine (using a training set of fluorescence spectra) a temperature with the relative error of no more than 1.2%.

  10. Auditory memory and proficiency of second language speaking: a latent variable analysis approach.

    Science.gov (United States)

    Tanaka, Akihiro; Nakamura, Kuninori

    2004-12-01

    Previous studies of second language aptitude have mainly used verbal stimuli in memory tasks. Memory for musical stimuli has not been used in aptitude studies although music and language have structural similarity. In this study, 30 Japanese university students who speak English as a second language (19 men, M=21.3 yr., SD=1.8) participated in the experiment as volunteers. They performed verbal memory tasks, musical memory tasks, and English pronunciation tasks. Factor analysis indicated that verbal and musical memory abilities are better represented as a unitary factor rather than two independent factors. Further, a path analysis supported the hypothesis that the memory for both verbal and musical tasks affects proficiency of second language pronunciation, including prosodic features such as stress in word or intonation through a couple of sentences. The memory factor was interpreted as reflecting the performance of "auditory working memory."

  11. The Czech audit: internal consistency, latent structure and identification of risky alcohol consumption.

    Science.gov (United States)

    Sovinová, Hana; Csémy, Ladislav

    2010-09-01

    The primary aim of the study is to examine the psychometric properties and the structure of the Czech version of the Alcohol Use Disorders Identification Test (AUDIT), and to estimate the rate of risky, harmful and problematic alcohol consumers. Two large data sets were analyzed. The first was based on the application of the AUDIT as a part of a general population survey (N = 1.326; age range 18-64), the second represents data gathered by general practitioners (GPs) in the context of a pilot screening and brief advice (SBA) project in the area of Greater Prague (N = 2.589). Analyses of reliability showed satisfying internal consistency of the AUDIT (Cronbach's alpha = 0.83 for population survey and 0.77 for survey based on SBA). Principal component analyses suggest two factor solutions where one factor represents drinking patterns and the second alcohol-related problems or symptoms of dependence. The principal component analyses of both data sets led to similar factor formation. A total of 19% of the general population sample was classified as risky or harmful drinkers and 2% as problem drinkers. These figures were slightly lower in the sample of patients of general practitioners. The Czech version of the AUDIT seems to be a plausible screening instrument. The properties of the instrument suggest usefulness of the summary score for identification of the level of risk.

  12. The Infinite Latent Events Model

    CERN Document Server

    Wingate, David; Roy, Daniel; Tenenbaum, Joshua

    2012-01-01

    We present the Infinite Latent Events Model, a nonparametric hierarchical Bayesian distribution over infinite dimensional Dynamic Bayesian Networks with binary state representations and noisy-OR-like transitions. The distribution can be used to learn structure in discrete timeseries data by simultaneously inferring a set of latent events, which events fired at each timestep, and how those events are causally linked. We illustrate the model on a sound factorization task, a network topology identification task, and a video game task.

  13. Application of core-shell-structured CdTe-SiO{sub 2} quantum dots synthesized via a facile solution method for improving latent fingerprint detection

    Energy Technology Data Exchange (ETDEWEB)

    Gao Feng; Han Jiaxing; Lv Caifeng; Wang Qin; Zhang Jun, E-mail: cejzhang@imu.edu.cn [Inner Mongolia University, College of Chemistry and Chemical Engineering (China); Li Qun; Bao Liru; Li Xin [Division of Science and Technology, Public Security Department of Inner Mongolia (China)

    2012-10-15

    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{sub 2} quantum dots (QDs) as fluorescent labeling marks. Core-shell-structured CdTe-SiO{sub 2} QDs are prepared via a simple solution-based approach using NH{sub 2}NH{sub 2}{center_dot}H{sub 2}O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe-SiO{sub 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{sub 2} QDs is largely enhanced by surface modification of the SiO{sub 2} shell. The CdTe-SiO{sub 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{sub 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{sub 2} QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.

  14. Does a latent class underlie schizotypal personality disorder? Implications for schizophrenia.

    Science.gov (United States)

    Ahmed, Anthony O; Green, Bradley A; Goodrum, Nada M; Doane, Nancy J; Birgenheir, Denis; Buckley, Peter F

    2013-05-01

    Despite growing enthusiasm for dimensional models of personality pathology, the taxonic versus dimensional status of schizotypal personality disorder (PD) remains a point of contention in modern psychiatry. The current study aimed to determine empirically the latent structure of schizotypal PD. We examined the latent structure of schizotypal PD in the Psychiatric Morbidity Survey in Great Britain and the second wave of the U.S.-based National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) survey. We analyzed composite indicators created from participant responses using the mean above minus mean below a cut (MAMBAC), Maximum Covariance (MAXCOV), and latent mode factor analysis (L-Mode) taxometric procedures. We also analyzed item-level responses using two latent variable mixture models--latent class analysis and latent class factor analysis. Taxometric and latent variable mixture analyses supported a dimensional, rather than taxonic, structure in both epidemiological samples. The dimensional model better predicted psychosis, intellectual functioning, disability, and treatment seeking than the categorical model based on DSM-IV diagnosis. People meeting criteria for schizotypal PD appear to exist on a spectrum of severity with the rest of the population. The possible dimensionality of schizotypal PD adds to growing support for a dimensional structure of PDs including other Cluster A disorders.

  15. Interferon-γ release assays for the diagnosis of latent Mycobacterium tuberculosis infection: a systematic review and meta-analysis

    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...... tuberculosis cases. IGRAs may have a relative advantage over the TST in detecting LTBI and allow the exclusion of M. tuberculosis infection with higher reliability....

  16. An analysis of a packed bed latent heat thermal energy storage system using PCM capsules. Numerical investigation

    Energy Technology Data Exchange (ETDEWEB)

    Felix Regin, A.; Solanki, S.C.; Saini, J.S. [Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247 667, UA (India)

    2009-07-15

    This paper is aimed at analyzing the behavior of a packed bed latent heat thermal energy storage system. The packed bed is composed of spherical capsules filled with paraffin wax as PCM usable with a solar water heating system. The model developed in this study uses the fundamental equations similar to those of Schumann, except that the phase change phenomena of PCM inside the capsules are analyzed by using enthalpy method. The equations are numerically solved, and the results obtained are used for the thermal performance analysis of both charging and discharging processes. The effects of the inlet heat transfer fluid temperature (Stefan number), mass flow rate and phase change temperature range on the thermal performance of the capsules of various radii have been investigated. The results indicate that for the proper modeling of performance of the system the phase change temperature range of the PCM must be accurately known, and should be taken into account. (author)

  17. Parents and adolescents growing up in the digital age: latent growth curve analysis of proactive media monitoring.

    Science.gov (United States)

    Padilla-Walker, Laura M; Coyne, Sarah M; Fraser, Ashley M; Dyer, W Justin; Yorgason, Jeremy B

    2012-10-01

    The current study examined how parents' use of restrictive and active monitoring and deference changed over three years, and examined both adolescent and parent characteristics as predictors of initial levels of media monitoring, as well as change in media monitoring. Participants included 276 mother-child dyads (M age of child = 12.08, SD = .63, 50% female) taken from Time 2 of the Flourishing Families Project, 96% of whom had complete data for Time 4 (N = 266). Active monitoring was the most common approach at the first and second time points, while active monitoring and deference were equally common by the final time point. Latent growth curve analysis revealed that restrictive and active monitoring decreased over time, while deference increased. In addition, both adolescent and parent characteristics were predictive of initial levels of all three types of monitoring, and of change in restrictive monitoring. Discussion focuses on developmental implications of these findings.

  18. Determination of psychosis-related clinical profiles in children with autism spectrum disorders using latent class analysis.

    Science.gov (United States)

    Kyriakopoulos, Marinos; Stringaris, Argyris; Manolesou, Sofia; Radobuljac, Maja Drobnič; Jacobs, Brian; Reichenberg, Avi; Stahl, Daniel; Simonoff, Emily; Frangou, Sophia

    2015-03-01

    In children with autism spectrum disorders (ASD), high rates of idiosyncratic fears and anxiety reactions and thought disorder are thought to increase the risk of psychosis. The critical next step is to identify whether combinations of these symptoms can be used to categorise individual patients into ASD subclasses, and to test their relevance to psychosis. All patients with ASD (n = 84) admitted to a specialist national inpatient unit from 2003 to 2012 were rated for the presence or absence of impairment in affective regulation and anxiety (peculiar phobias, panic episodes, explosive reactions to anxiety), social deficits (social disinterest, avoidance or withdrawal and abnormal attachment) and thought disorder (disorganised or illogical thinking, bizarre fantasies, overvalued or delusional ideas). Latent class analysis of individual symptoms was conducted to identify ASD classes. External validation of these classes was performed using as a criterion the presence of hallucinations. Latent class analysis identified two distinct classes. Bizarre fears and anxiety reactions and thought disorder symptoms differentiated ASD patients into those with psychotic features (ASD-P: 51 %) and those without (ASD-NonP: 49 %). Hallucinations were present in 26 % of the ASD-P class but only 2.4 % of the ASD-NonP. Both the ASD-P and the ASD-NonP class benefited from inpatient treatment although inpatient stay was prolonged in the ASD-P class. This study provides the first empirically derived classification of ASD in relation to psychosis based on three underlying symptom dimensions, anxiety, social deficits and thought disorder. These results can be further developed by testing the reproducibility and prognostic value of the identified classes.

  19. Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies.

    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.

  20. University and student segmentation: multilevel latent-class analysis of students' attitudes towards research methods and statistics.

    Science.gov (United States)

    Mutz, Rüdiger; Daniel, Hans-Dieter

    2013-06-01

    It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrollment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important for didactic purposes (heterogeneity of the student population). The paper presents a scale based on findings of the social psychology of attitudes (polar and emotion-based concept) in conjunction with a method for capturing beginning university students' attitudes towards research methods and statistics and identifying the proportion of students having positive attitudes at the institutional level. The study based on a re-analysis of a nationwide survey in Germany in August 2000 of all psychology students that enrolled in fall 1999/2000 (N= 1,490) and N= 44 universities. Using multilevel latent-class analysis (MLLCA), the aim was to group students in different student attitude types and at the same time to obtain university segments based on the incidences of the different student attitude types. Four student latent clusters were found that can be ranked on a bipolar attitude dimension. Membership in a cluster was predicted by age, grade point average (GPA) on school-leaving exam, and personality traits. In addition, two university segments were found: universities with an average proportion of students with positive attitudes and universities with a high proportion of students with positive attitudes (excellent segment). As psychology students make up a very heterogeneous group, the use of multiple learning activities as opposed to the classical lecture course is required. © 2011 The British Psychological Society.

  1. Parenting characteristics in the home environment and adolescent overweight: a latent class analysis.

    Science.gov (United States)

    Berge, Jerica M; Wall, Melanie; Bauer, Katherine W; Neumark-Sztainer, Dianne

    2010-04-01

    Parenting style and parental support and modeling of physical activity and healthy dietary intake have been linked to youth weight status, although findings have been inconsistent across studies. Furthermore, little is known about how these factors co-occur, and the influence of the coexistence of these factors on adolescents' weight. This article examines the relationship between the co-occurrence of various parenting characteristics and adolescents' weight status. Data are from Project EAT (eating among teens), a population-based study of 4,746 diverse adolescents. Theoretical and latent class groupings of parenting styles and parenting practices were created. Regression analyses examined the relationship between the created variables and adolescents' BMI. Having an authoritarian mother was associated with higher BMI in sons. The co-occurrence of an authoritarian mother and neglectful father was associated with higher BMI for sons. Daughters' whose fathers did not model or encourage healthy behaviors reported higher BMIs. The co-occurrence of neither parent modeling healthy behaviors was associated with higher BMIs for sons, and incongruent parental modeling and encouraging of healthy behaviors was associated with higher BMIs in daughters. Although, further research into the complex dynamics of the home environment is needed, findings indicate that authoritarian parenting style is associated with higher adolescent weight status and incongruent parenting styles and practices between mothers and fathers are associated with higher adolescent weight status.

  2. Sequence analysis and location of capsid proteins within RNA 2 of strawberry latent ringspot virus.

    Science.gov (United States)

    Kreiah, S; Strunk, G; Cooper, J I

    1994-09-01

    The nucleotide sequence of the RNA 2 of a strawberry isolate (H) of strawberry latent ringspot virus (SLRSV) comprised 3824 nucleotides and contained one long open reading frame with a theoretical coding capacity of 890 amino acids equivalent to a protein of 98.8K. The N-terminal amino acid sequences of virion-derived proteins were determined by Edman degradation allowing the capsid coding regions to be located and serine/glycine cleavage sites to be identified within the polyprotein. The amino acid sequence in the capsid coding region of an isolate of SLRSV from flowering cherry in New Zealand was 97% identical to that of SLRSV-H. Except in the 3' and 5' terminal non-coding sequences, computer-based alignment and comparison algorithms did not reveal any substantial homologies between RNA 2 of SLRSV-H and the equivalent genomic segments in the nepoviruses arabis mosaic, cherry leaf roll, grapevine fanleaf, raspberry ringspot, grapevine hungarian chrome mosaic, tomato blackring, tomato ringspot, tobacco ringspot, or in the comoviruses cowpea mosaic and red clover mottle. Despite the similarities in overall genome organization, data from RNA 2 remain insufficient for unambiguous positioning of SLRSV in relation to species/genera in the Comoviridae.

  3. Recent sexual victimization and drinking behavior in newly matriculated college students: a latent growth analysis.

    Science.gov (United States)

    Griffin, Melissa J; Wardell, Jeffrey D; Read, Jennifer P

    2013-12-01

    College matriculation is a time of developmental and social change and is often a time of heavy drinking. Sexual victimization (SV) is prevalent in late adolescence and poses additional risk for problem drinking behavior. Thus, matriculating students with a SV history may be at heightened risk for maladaptive alcohol use while transitioning through the first year of college. Furthermore, victimization that has occurred close to college matriculation may confer particular risk for problem alcohol use, because the added stressor of coping with a SV while negotiating the transition into college may lead to risky drinking behavior. Therefore, examining the influence of SV timing (i.e., recency) on drinking patterns in freshman year was the aim of the present study. Matriculating undergraduates with a history of SV were assessed at six points during freshman year. Using latent growth curve modeling, we tested differences in trajectories of drinking behavior (i.e., alcohol use, binge drinking) between students who reported a recent SV and those who reported a more distal SV. Students endorsing a recent SV evidenced greater overall levels of alcohol use and higher levels of binge drinking than individuals with SV that was less recent. Moreover, the recent SV group showed significantly more variability in drinking outcomes over freshman year, with escalations mapping onto more salient periods of transition over the first college year. SV that occurs close to college entry is associated with specific and persistent risk for maladaptive drinking behavior in newly matriculated college students.

  4. School climate and bullying victimization: a latent class growth model analysis.

    Science.gov (United States)

    Gage, Nicholas A; Prykanowski, Debra A; Larson, Alvin

    2014-09-01

    Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the social-ecological link between school climate factors and bullying/peer aggression. To address this gap, we examined the association between school climate factors and bullying victimization for 4,742 students in Grades 3-12 across 3 school years in a large, very diverse urban school district using latent class growth modeling. Across 3 different models (elementary, secondary, and transition to middle school), a 3-class model was identified, which included students at high-risk for bullying victimization. Results indicated that, for all students, respect for diversity and student differences (e.g., racial diversity) predicted within-class decreases in reports of bullying. High-risk elementary students reported that adult support in school was a significant predictor of within-class reduction of bullying, and high-risk secondary students report peer support as a significant predictor of within-class reduction of bullying.

  5. Does sponsorship improve outcomes above Alcoholics Anonymous attendance? A latent class growth curve analysis.

    Science.gov (United States)

    Witbrodt, Jane; Kaskutas, Lee; Bond, Jason; Delucchi, Kevin

    2012-02-01

    To construct Alcoholics Anonymous (AA) attendance, sponsorship and abstinence latent class trajectories to test the added benefit of having a sponsor above the benefits of attendance in predicting abstinence over time. Prospective with 1-, 3-, 5- and 7-year follow-ups. Alcoholic-dependent individuals from two probability samples, one from representative public and private treatment programs and another from the general population (n = 495). Individuals in the low attendance class (four classes identified) were less likely than those in the high, descending and medium attendance classes to be in high (versus low) abstinence class (three classes identified). No differences were found between the other attendance classes as related to abstinence class membership. Overall, being in the high sponsor class (three classes identified) predicted better abstinence outcomes than being in either of two other classes (descending and low), independent of attendance class effects. Although declining sponsor involvement was associated with greater likelihood of high abstinence than low sponsor involvement, being in the descending sponsor class also increased the odds of being in the descending abstinence class. Any pattern of Alcoholics Anonymous attendance, even if it declines or is never high for a particular 12-month period, is better than little or no attendance in terms of abstinence. Greater initial attendance carries added value. There is a benefit for maintaining a sponsor over time above that found for attendance. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  6. Distinct Classes of Negative Alcohol-Related Consequences in a National Sample of Incoming First-Year College Students: A Latent Class Analysis.

    Science.gov (United States)

    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.

  7. A multidimensional item response model : Constrained latent class analysis using the Gibbs sampler and posterior predictive checks

    NARCIS (Netherlands)

    Hoijtink, H; Molenaar, IW

    1997-01-01

    In this paper it will be shown that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. The parameters of this latent class model will be estimated using an application of the Gibbs sampler. It will be illust

  8. Combined Patterns of Risk for Problem and Obesogenic Behaviors in Adolescents: A Latent Class Analysis Approach

    Science.gov (United States)

    Fleary, Sasha A.

    2017-01-01

    Background: Several studies have used latent class analyses to explore obesogenic behaviors and substance use in adolescents independently. We explored a variety of health risks jointly to identify distinct patterns of risk behaviors among adolescents. Methods: Latent class models were estimated using Youth Risk Behavior Surveillance System…

  9. Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

    Science.gov (United States)

    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.…

  10. Identification of subgroups of inflammatory and degenerative MRI findings in the spine and sacroiliac joints: a latent class analysis of 1037 patients with persistent low back pain

    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: T...

  11. A Latent Class Analysis of Maternal Responsiveness and Autonomy-Granting in Early Adolescence: Prediction to Later Adolescent Sexual Risk-Taking

    Science.gov (United States)

    Lanza, H. Isabella; Huang, David Y. C.; Murphy, Debra A.; Hser, Yih-Ing

    2013-01-01

    The present study sought to extend empirical inquiry related to the role of parenting on adolescent sexual risk-taking by using latent class analysis (LCA) to identify patterns of adolescent-reported mother responsiveness and autonomy-granting in early adolescence and examine associations with sexual risk-taking in mid- and late-adolescence.…

  12. A Latent Class Analysis of Maternal Responsiveness and Autonomy-Granting in Early Adolescence: Prediction to Later Adolescent Sexual Risk-Taking

    Science.gov (United States)

    Lanza, H. Isabella; Huang, David Y. C.; Murphy, Debra A.; Hser, Yih-Ing

    2013-01-01

    The present study sought to extend empirical inquiry related to the role of parenting on adolescent sexual risk-taking by using latent class analysis (LCA) to identify patterns of adolescent-reported mother responsiveness and autonomy-granting in early adolescence and examine associations with sexual risk-taking in mid- and late-adolescence.…

  13. A Latent Class Analysis of Weight-Related Health Behaviors among 2-and 4-Year College Students and Associated Risk of Obesity

    Science.gov (United States)

    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…

  14. Single molecule analysis of replicated DNA reveals the usage of multiple KSHV genome regions for latent replication.

    Directory of Open Access Journals (Sweden)

    Subhash C Verma

    2011-11-01

    Full Text Available Kaposi's sarcoma associated herpesvirus (KSHV, an etiologic agent of Kaposi's sarcoma, Body Cavity Based Lymphoma and Multicentric Castleman's Disease, establishes lifelong latency in infected cells. The KSHV genome tethers to the host chromosome with the help of a latency associated nuclear antigen (LANA. Additionally, LANA supports replication of the latent origins within the terminal repeats by recruiting cellular factors. Our previous studies identified and characterized another latent origin, which supported the replication of plasmids ex-vivo without LANA expression in trans. Therefore identification of an additional origin site prompted us to analyze the entire KSHV genome for replication initiation sites using single molecule analysis of replicated DNA (SMARD. Our results showed that replication of DNA can initiate throughout the KSHV genome and the usage of these regions is not conserved in two different KSHV strains investigated. SMARD also showed that the utilization of multiple replication initiation sites occurs across large regions of the genome rather than a specified sequence. The replication origin of the terminal repeats showed only a slight preference for their usage indicating that LANA dependent origin at the terminal repeats (TR plays only a limited role in genome duplication. Furthermore, we performed chromatin immunoprecipitation for ORC2 and MCM3, which are part of the pre-replication initiation complex to determine the genomic sites where these proteins accumulate, to provide further characterization of potential replication initiation sites on the KSHV genome. The ChIP data confirmed accumulation of these pre-RC proteins at multiple genomic sites in a cell cycle dependent manner. Our data also show that both the frequency and the sites of replication initiation vary within the two KSHV genomes studied here, suggesting that initiation of replication is likely to be affected by the genomic context rather than the DNA

  15. Exploring the longitudinal offending pathways of child sexual abuse victims: A preliminary analysis using latent variable modeling.

    Science.gov (United States)

    Papalia, Nina L; Luebbers, Stefan; Ogloff, James R P; Cutajar, Margaret; Mullen, Paul E

    2017-01-16

    Very little research has been conducted to show the way in which criminal behavior unfolds over the life-course in children who have been sexually abused, and whether it differs from the 'age-crime' patterns consistently documented in the criminology literature. This study investigated the temporal pathways of criminal offending between the ages of 10-25 years among medically confirmed cases of child sexual abuse (CSA), and considered whether abuse variables, offense variables, and the presence of other adverse outcomes, were associated with heterogeneity in offending pathways among CSA survivors. This study utilized data gathered as part of a large-scale study involving the linkage of forensic examinations on 2759 cases of medically ascertained CSA between 1964 and 1995, to criminal justice and public psychiatric databases 13-44 years following abuse, together with a matched comparison sample of 2677 individuals. We used the subsample of 283 offending individuals (191 victims; 92 comparisons) for whom complete offending data were available. We compared the aggregate age-crime curves for CSA victims and comparisons, and applied longitudinal latent class analysis to identify distinct subgroups of offending pathways between ages 10-25 years within the abuse sample. Four latent pathways emerged among sexually abused offenders, labeled: Early-Onset/High-Risk/Adolescence-Limited; Intermediate-Onset/Low-Risk/Adolescence-Limited; Late-Onset/Low-Risk/Slow-Declining; and Early-Onset/High-Risk/Persistent offenders. Age at abuse, the nature and frequency of offending, and mental health problems, were associated with the offending pathway followed by CSA victims. Consistent with criminological literature, findings indicate considerable heterogeneity in the longitudinal offending patterns of offenders exposed to CSA. Implications for clinical practice and directions for research are highlighted.

  16. Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis

    Science.gov (United States)

    Ismayilova, Leyla; Gaveras, Eleni; Blum, Austin; Tô-Camier, Alexice; Nanema, Rachel

    2016-01-01

    Objectives Research about the mental health of children in Francophone West Africa is scarce. This paper examines the relationships between adverse childhood experiences, including exposure to violence and exploitation, and mental health outcomes among children living in ultra-poverty in rural Burkina Faso. Methods This paper utilizes baseline data collected from 360 children ages 10–15 and 360 of their mothers recruited from twelve impoverished villages in the Nord Region of Burkina, located near the Sahel Desert and affected by extreme food insecurity. We used a Latent Class Analysis to identify underlying patterns of maltreatment. Further, the relationships between latent classes and mental health outcomes were tested using mixed effected regression models adjusted for clustering within villages. Results About 15% of the children in the study scored above the clinical cut-off for depression, 17.8% for posttraumatic stress disorder (PTSD), and 6.4% for low self-esteem. The study identified five distinct sub-groups (or classes) of children based on their exposure to adverse childhood experiences. Children with the highest exposure to violence at home, at work and in the community (Abused and Exploited class) and children not attending school and working for other households, often away from their families (External Laborer class), demonstrated highest symptoms of depression and trauma. Despite living in adverse conditions and working to assist families, the study also identified a class of children who were not exposed to any violence at home or at work (Healthy and Non-abused class). Children in this class demonstrated significantly higher self-esteem (b = 0.92, SE = 0.45, pfamily-level poverty and violence in the family. PMID:27764155

  17. Classifying substance use disorder treatment facilities with co-located mental health services: A latent class analysis approach.

    Science.gov (United States)

    Mauro, Pia M; Furr-Holden, C Debra; Strain, Eric C; Crum, Rosa M; Mojtabai, Ramin

    2016-06-01

    The Affordable Care Act calls for increased integration and coordination of behavioral health services, as people with co-occurring disorders (CODs), meeting criteria for both substance use and psychiatric disorders, are overrepresented in treatment samples. Nationwide estimates of mental health (MH) service co-location in substance use disorder (SUD) treatment facilities are needed. We empirically derived a multiple-indicator categorization of services for CODs in SUD treatment facilities. We used latent class analysis to categorize 14,037 SUD treatment facilities in the United States and territories included in the 2012 National Survey of Substance Abuse Treatment Services. Latent class indicators included MH screening and diagnosis, MH support services, psychiatric medications, groups for CODs, and psychosocial approaches. Multinomial logistic regression compared facility-identified primary focus (i.e., SUD, MH, mix of SUD-MH, and general/other) and other facility characteristics across classes. A four-class solution was chosen with the following classes: Comprehensive MH/COD Services (25%), MH without COD Services (25%), MH Screening Services (21%), and Limited MH Services (29%). The former two classes with co-located MH services were less likely to report a SUD-primary focus than the latter classes reporting only MH screening or Limited MH Services. Only the Comprehensive MH/COD Services class also had a high probability of providing special groups for CODs. Approximately half of SUD treatment facilities were in classes with co-located mental health services, but only a quarter provided comprehensive COD services. Future studies should assess differences in patient experiences and treatment outcomes across facilities with and without COD services. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. Food shopping profiles and their association with dietary patterns: a latent class analysis.

    Science.gov (United States)

    VanKim, Nicole A; Erickson, Darin J; Laska, Melissa N

    2015-07-01

    Food shopping is a complex behavior that consists of multiple dimensions. Little research has explored multiple dimensions of food shopping or examined how it relates to dietary intake. To identify patterns (or classes) of food shopping across four domains (fresh food purchasing, conscientious food shopping, food shopping locations, and food/beverage purchasing on or near campus) and explore how these patterns relate to dietary intake among college students. A cross-sectional online survey was administered. Students attending a public 4-year university and a 2-year community college in the Twin Cities (Minnesota) metropolitan area (N=1,201) participated in this study. Fast-food and soda consumption as well as meeting fruit and vegetable, fiber, added sugar, calcium, dairy, and fat recommendations. Crude and adjusted latent class models and adjusted logistic regression models were fit. An eight-class solution was identified: "traditional shopper" (14.9%), "fresh food and supermarket shopper" (14.1%), "convenience shopper" (18.8%), "conscientious convenience shopper" (13.8%), "conscientious, fresh food, convenience shopper" (11.8%), "conscientious fresh food shopper" (6.6%), "conscientious nonshopper" (10.2%), and "nonshopper" (9.8%). "Fresh food and supermarket shoppers" and "conscientious fresh food shoppers" had better dietary intake (for fast food, calcium, dairy, and added sugar), whereas "convenience shoppers" and "conscientious convenience shoppers," and "nonshoppers" had worse dietary intake (for soda, calcium, dairy, fiber, and fat) than "traditional shoppers." These findings highlight unique patterns in food shopping and associated dietary patterns that could inform tailoring of nutrition interventions for college students. Additional research is needed to understand modifiable contextual influences of healthy food shopping. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  19. Patterns of Alcohol Policy Enforcement Activities among Local Law Enforcement Agencies: A Latent Class Analysis.

    Science.gov (United States)

    Erickson, Darin J; Rutledge, Patricia C; Lenk, Kathleen M; Nelson, Toben F; Jones-Webb, Rhonda; Toomey, Traci L

    We assessed levels and patterns of alcohol policy enforcement activities among U.S. local law enforcement agencies. We conducted a cross-sectional survey of a representative sample of 1,631 local law enforcement agencies across the 50 states. We assessed 29 alcohol policy enforcement activities within each of five enforcement domains-underage alcohol possession/consumption, underage alcohol provision, underage alcohol sales, impaired driving, and overservice of alcohol-and conducted a series of latent class analyses to identify unique classes or patterns of enforcement activity for each domain. We identified three to four unique enforcement activity classes for each of the enforcement domains. In four of the domains, we identified a Uniformly Low class (i.e., little or no enforcement) and a Uniformly High enforcement activity class (i.e., relatively high levels of enforcement), with one or two middle classes where some but not all activities were conducted. The underage provision domain had a Uniformly Low class but not a Uniformly High class. The Uniformly Low class was the most prevalent class in three domains: underage provision (58%), underage sales (61%), and overservice (79%). In contrast, less than a quarter of agencies were in Uniformly High classes. We identified qualitatively distinct patterns of enforcement activity, with a large proportion of agencies in classes characterized by little or no enforcement and fewer agencies in high enforcement classes. An important next step is to determine if these patterns are associated with rates of alcohol use and alcohol-related injury and mortality.

  20. Latent class analysis of reading, decoding, and writing performance using the Academic Performance Test: concurrent and discriminating validity

    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

  1. Clustering of immunological, metabolic and genetic features in latent autoimmune diabetes in adults: evidence from principal component analysis.

    Science.gov (United States)

    Pes, Giovanni Mario; Delitala, Alessandro Palmerio; Errigo, Alessandra; Delitala, Giuseppe; Dore, Maria Pina

    2016-06-01

    Latent autoimmune diabetes in adults (LADA) which accounts for more than 10 % of all cases of diabetes is characterized by onset after age 30, absence of ketoacidosis, insulin independence for at least 6 months, and presence of circulating islet-cell antibodies. Its marked heterogeneity in clinical features and immunological markers suggests the existence of multiple mechanisms underlying its pathogenesis. The principal component (PC) analysis is a statistical approach used for finding patterns in data of high dimension. In this study the PC analysis was applied to a set of variables from a cohort of Sardinian LADA patients to identify a smaller number of latent patterns. A list of 11 variables including clinical (gender, BMI, lipid profile, systolic and diastolic blood pressure and insulin-free time period), immunological (anti-GAD65, anti-IA-2 and anti-TPO antibody titers) and genetic features (predisposing gene variants previously identified as risk factors for autoimmune diabetes) retrieved from clinical records of 238 LADA patients referred to the Internal Medicine Unit of University of Sassari, Italy, were analyzed by PC analysis. The predictive value of each PC on the further development of insulin dependence was evaluated using Kaplan-Meier curves. Overall 4 clusters were identified by PC analysis. In component PC-1, the dominant variables were: BMI, triglycerides, systolic and diastolic blood pressure and duration of insulin-free time period; in PC-2: genetic variables such as Class II HLA, CTLA-4 as well as anti-GAD65, anti-IA-2 and anti-TPO antibody titers, and the insulin-free time period predominated; in PC-3: gender and triglycerides; and in PC-4: total cholesterol. These components explained 18, 15, 12, and 12 %, respectively, of the total variance in the LADA cohort. The predictive power of insulin dependence of the four components was different. PC-2 (characterized mostly by high antibody titers and presence of predisposing genetic markers

  2. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Directory of Open Access Journals (Sweden)

    Meghani Salimah

    2009-01-01

    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

  3. Not all experiences of (inauthenticity are created equal: A latent class analysis approach(retitled Identifying Differences in the Experience of (InAuthenticity: A Latent Class Analysis Approach

    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.

  4. Analysis of Structural Equation Model with Ignorable Missing Continuous and Polytomous Data.

    Science.gov (United States)

    Song, Xin-Yuan; Lee, Sik-Yum

    2002-01-01

    Developed a Bayesian approach for structural equation models with ignorable missing continuous and polytomous data that obtains joint Bayesian estimates of thresholds, structural parameters, and latent factor scores simultaneously. Illustrated the approach through analysis of a real data set of 20 patterns of condom use in the Philippines. (SLD)

  5. Biomedical Literature Exploration through Latent Semantics

    Directory of Open Access Journals (Sweden)

    Sérgio MATOS

    2013-08-01

    Full Text Available The fast increasing amount of articles published in the biomedical field is creating difficulties in the way this wealth of information can be efficiently exploited by researchers. As a way of overcoming these limitations and potentiating a more efficient use of the literature, we propose an approach for structuring the results of a literature search based on the latent semantic information extracted from a corpus. Moreover, we show how the results of the Latent Semantic Analysis method can be adapted so as to evidence differences between results of different searches. We also propose different visualization techniques that can be applied to explore these results. Used in combination, these techniques could empower users with tools for literature guided knowledge exploration and discovery.

  6. Biomedical Literature Exploration through Latent Semantics

    Directory of Open Access Journals (Sweden)

    Hugo ARAÚJO

    2013-08-01

    Full Text Available The fast increasing amount of articles published in the biomedical field is creating difficulties in the way this wealth of information can be efficiently exploited by researchers. As a way of overcoming these limitations and potentiating a more efficient use of the literature, we propose an approach for structuring the results of a literature search based on the latent semantic information extracted from a corpus. Moreover, we show how the results of the Latent Semantic Analysis method can be adapted so as to evidence differences between results of different searches. We also propose different visualization techniques that can be applied to explore these results. Used in combination, these techniques could empower users with tools for literature guided knowledge exploration and discovery.

  7. Can Latent Class Analysis Be Used to Improve the Diagnostic Process in Pediatric Patients with Chronic Ataxia?

    Science.gov (United States)

    Klassen, Samantha; Dufault, Brenden; Salman, Michael S

    2017-04-01

    Chronic ataxia is a relatively common symptom in children. There are numerous causes of chronic ataxia, making it difficult to derive a diagnosis in a timely manner. We hypothesized that the efficiency of the diagnostic process can be improved with systematic analysis of clinical features in pediatric patients with chronic ataxia. Our aim was to improve the efficiency of the diagnostic process in pediatric patients with chronic ataxia. A cohort of 184 patients, aged 0-16 years with chronic ataxia who received medical care at Winnipeg Children's Hospital during 1991-2008, was ascertained retrospectively from several hospital databases. Clinical details were extracted from hospital charts. The data were compared among the more common diseases using univariate analysis to identify pertinent clinical features that could potentially improve the efficiency of the diagnostic process. Latent class analysis was then conducted to detect unique patterns of clinical features and to determine whether these patterns could be associated with chronic ataxia diagnoses. Two models each with three classes were chosen based on statistical criteria and clinical knowledge for best fit. Each class represented a specific pattern of presenting symptoms or other clinical features. The three classes corresponded to a plausible and shorter list of possible diagnoses. For example, developmental delay and hypotonia correlated best with Angelman syndrome. Specific patterns of presenting symptoms or other clinical features can potentially aid in the initial assessment and diagnosis of pediatric patients with chronic ataxia. This will likely improve the efficiency of the diagnostic process.

  8. 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...... and independence. In music as well as language the patterns we come across become part of our mental workspace when the bottom-up sensory input raises above the background noise of core affect, and top-down trigger distinct feelings reflecting a shift of our attention. And as both low-level semantics and our...... 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...

  9. Structural analysis for Diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2001-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential technique to obtain redundant information for diagnosis, is re-considered in this paper. Matching is re-formulated as a problem...

  10. Structural analysis for diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2002-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem...

  11. Modelos de Teoría de Respuesta al Item en donde las habilidades tienen una Estructura Lineal Latente / Multidimensional Item Response Theory Models where the Ability has a Linear Latent Structure

    OpenAIRE

    Montenegro Díaz, Alvaro Mauricio

    2010-01-01

    Se propone una nueva clase de modelos multidimensionales de teoría de respuesta al ítem. Los modelos fueron diseñados para ajustar datos provenientes de prueba binarias o dicotomizadas, las cuales están dividida en m subpruebas. Se asume que cada subprueba está diseñada para medir un trazo latente unidimensional, el cual es llamado trazo latente principal o habilidad principal. El objetivo de la prueba es medir estos los trazos latentes principales. En este trabajo, se asume que la prueba com...

  12. EVALUACIÓN AUTOMÁTICA DE COHERENCIA TEXTUAL EN NOTICIAS POLICIALES UTILIZANDO ANÁLISIS SEMÁNTICO LATENTE AUTOMATIC EVALUATION OF TEXTUAL COHERENCE IN POLICE NEWS USING LATENT SEMANTIC ANALYSIS

    Directory of Open Access Journals (Sweden)

    SERGIO HERNÁNDEZ OSUNA

    2010-01-01

    Full Text Available El presente artículo expone los resultados de una investigación que buscó evaluar la coherencia textual en forma automática, utilizando el método de Análisis Semántico Latente, en el dominio formado por noticias policiales. Con este fin se construyó una herramienta prototipo, empleando únicamente software libre, que se puede obtener desde Internet. Para validar el funcionamiento del prototipo se comparó su evaluación con la realizada por ocho evaluadores humanos: cuatro periodistas y cuatro profesores de español con estudios de postgrado en lingüística.This article presents the results of an investigation that aimed to assess textual coherence automatically, using the method of Latent Semantic Analysis in the domain formed by police news. For this purpose, a prototype tool was built using only free software, which can be obtained from the Internet. To validate the performance of the prototype, its evaluation was compared with that made by eight human evaluators: four journalists and four spanish’s teachers with graduate studies in linguistics.

  13. Sampling Weights in Latent Variable Modeling

    Science.gov (United States)

    Asparouhov, Tihomir

    2005-01-01

    This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The…

  14. Violence against Congolese refugee women in Rwanda and mental health: a cross-sectional study using latent class analysis.

    Science.gov (United States)

    Sipsma, Heather L; Falb, Kathryn L; Willie, Tiara; Bradley, Elizabeth H; Bienkowski, Lauren; Meerdink, Ned; Gupta, Jhumka

    2015-04-23

    To examine patterns of conflict-related violence and intimate partner violence (IPV) and their associations with emotional distress among Congolese refugee women living in Rwanda. Cross-sectional study. Two Congolese refugee camps in Rwanda. 548 ever-married Congolese refugee women of reproductive age (15-49 years) residing in Rwanda. Our primary outcome was emotional distress as measured using the Self-Report Questionnaire-20 (SRQ-20). For analysis, we considered participants with scores greater than 10 to be experiencing emotional distress and participants with scores of 10 or less not to be experiencing emotional distress. Almost half of women (49%) reported experiencing physical, emotional or sexual violence during the conflict, and less than 10% of women reported experiencing of any type of violence after fleeing the conflict. Lifetime IPV was reported by approximately 22% of women. Latent class analysis derived four distinct classes of violence experiences, including the Low All Violence class, the High Violence During Conflict class, the High IPV class and the High Violence During and After Conflict class. In multivariate regression models, latent class was strongly associated with emotional distress. Compared with women in the Low All Violence class, women in the High Violence During and After Conflict class and women in the High Violence During Conflict had 2.7 times (95% CI 1.11 to 6.74) and 2.3 times (95% CI 1.30 to 4.07) the odds of experiencing emotional distress in the past 4 weeks, respectively. Furthermore, women in the High IPV class had a 4.7 times (95% CI 2.53 to 8.59) greater odds of experiencing emotional distress compared with women in the Low All Violence class. Experiences of IPV do not consistently correlate with experiences of conflict-related violence, and women who experience high levels of IPV may have the greatest likelihood for poor mental health in conflict-affected settings. Published by the BMJ Publishing Group Limited. For

  15. Demographic analysis from summaries of an age-structured population

    Science.gov (United States)

    Link, William A.; Royle, J. Andrew; Hatfield, Jeff S.

    2003-01-01

    Demographic analyses of age-structured populations typically rely on life history data for individuals, or when individual animals are not identified, on information about the numbers of individuals in each age class through time. While it is usually difficult to determine the age class of a randomly encountered individual, it is often the case that the individual can be readily and reliably assigned to one of a set of age classes. For example, it is often possible to distinguish first-year from older birds. In such cases, the population age structure can be regarded as a latent variable governed by a process prior, and the data as summaries of this latent structure. In this article, we consider the problem of uncovering the latent structure and estimating process parameters from summaries of age class information. We present a demographic analysis for the critically endangered migratory population of whooping cranes (Grus americana), based only on counts of first-year birds and of older birds. We estimate age and year-specific survival rates. We address the controversial issue of whether management action on the breeding grounds has influenced recruitment, relating recruitment rates to the number of seventh-year and older birds, and examining the pattern of variation through time in this rate.

  16. Probabilistic Structural Analysis Program

    Science.gov (United States)

    Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

    2010-01-01

    NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

  17. Racial Discrimination and Racial Socialization as Predictors of African American Adolescents’ Racial Identity Development using Latent Transition Analysis

    OpenAIRE

    Seaton, Eleanor K.; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M.

    2011-01-01

    The current study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over three years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing or remaining constant. Racial socializatio...

  18. Latent geometry of bipartite networks

    Science.gov (United States)

    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.

  19. A latent class analysis of bullies, victims and aggressive victims in Chinese adolescence: relations with social and school adjustments.

    Directory of Open Access Journals (Sweden)

    Aihui Shao

    Full Text Available This study used the latent class analysis (LCA to identify and classify Chinese adolescent children's aggressive behaviors. It was found that (1 Adolescent children could be divided into four categories: general children, aggressive children, victimized children and aggressive victimized children. (2 There were significant gender differences among the aggressive victimized children, the aggressive children and the general children. Specifically, aggressive victimized children and aggressive children had greater probabilities of being boys; victimized children had equal probabilities of being boys or girls. (3 Significant differences in loneliness, depression, anxiety and academic achievement existed among the aggressive victims, the aggressor, the victims and the general children, in which the aggressive victims scored the worst in all questionnaires. (4 As protective factors, peer and teacher supports had important influences on children's aggressive and victimized behaviors. Relative to general children, aggressive victims, aggressive children and victimized children had lower probabilities of receiving peer supports. On the other hand, compared to general children, aggressive victims had lower probabilities of receiving teacher supports; while significant differences in the probability of receiving teacher supports did not exist between aggressive children and victimized children.

  20. Life satisfaction and perceived stress among young offenders in a residential therapeutic community: Latent change score analysis.

    Science.gov (United States)

    Tang, Kristen N S; Chan, Christian S

    2017-06-01

    Recent rehabilitation frameworks underscore the importance of strength-based interventions for young offenders who may lack internal and external resources to manage their stress and plan for their life. This multi-wave longitudinal study investigated the dynamic relationship between perceived stress and life satisfaction among a group of young ex-offenders in a residential therapeutic community. Four waves of data were collected from 117 Hong Kong youths (24.0% female, mean age = 17.7) over one year. Latent change score analysis was employed to examine the univairate and bivariate changes of their perceived stress and life satisfaction. Results suggest a positive growth trajectory in life satisfaction over time. The results of perceived stress were less conclusive. Bivariate models indicated that the previous level of life satisfaction was negatively linked to the subsequent perceived stress level but not vice versa. The findings suggest that improvement in life satisfaction may reduce perceived stress in young ex-offenders. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  1. Concurrent and simultaneous polydrug use: latent class analysis of an Australian nationally representative sample of young adults.

    Directory of Open Access Journals (Sweden)

    Lake-Hui eQuek

    2013-11-01

    Full Text Available Background: Alcohol use and illicit drug use peak during young adulthood (around 18-29 years of age, but comparatively little is known about polydrug use in nationally representative samples of young adults. Drawing on a nationally representative cross-sectional survey (Australian National Drug Strategy Household Survey, this study examines polydrug use patterns and associated psychosocial risk factors among young adults (n = 3,333; age 19-29. Method: The use of a broad range of licit and illicit drugs were examined, including alcohol, tobacco, cannabis, cocaine, hallucinogens, ecstasy, ketamine, GHB, inhalants, steroids, barbiturates, meth/amphetamines, heroin, methadone/buprenorphine, other opiates, painkillers and tranquillizers/sleeping pills. Latent class analysis was employed to identify patterns of polydrug use. Results: Polydrug use in this sample was best described using a 5-class solution. The majority of young adults predominantly used alcohol only (52.3%, alcohol and tobacco (34.18%. The other classes were cannabis, ecstasy, and licit drug use (9.4%, cannabis, amphetamine derivative, and licit drug use (2.8%, and sedative and alcohol use (1.3%. Young adult males with low education and/or high income were most at risk of polydrug use. Conclusion: Almost half of young adults reported polydrug use, highlighting the importance of post-high school screening for key risk factors and polydrug use profiles, and the delivery of early intervention strategies targeting illicit drugs.

  2. Variations in students' perceived reasons for, sources of, and forms of in-school discrimination: A latent class analysis.

    Science.gov (United States)

    Byrd, Christy M; Carter Andrews, Dorinda J

    2016-08-01

    Although there exists a healthy body of literature related to discrimination in schools, this research has primarily focused on racial or ethnic discrimination as perceived and experienced by students of color. Few studies examine students' perceptions of discrimination from a variety of sources, such as adults and peers, their descriptions of the discrimination, or the frequency of discrimination in the learning environment. Middle and high school students in a Midwestern school district (N=1468) completed surveys identifying whether they experienced discrimination from seven sources (e.g., peers, teachers, administrators), for seven reasons (e.g., gender, race/ethnicity, religion), and in eight forms (e.g., punished more frequently, called names, excluded from social groups). The sample was 52% White, 15% Black/African American, 14% Multiracial, and 17% Other. Latent class analysis was used to cluster individuals based on reported sources of, reasons for, and forms of discrimination. Four clusters were found, and ANOVAs were used to test for differences between clusters on perceptions of school climate, relationships with teachers, perceptions that the school was a "good school," and engagement. The Low Discrimination cluster experienced the best outcomes, whereas an intersectional cluster experienced the most discrimination and the worst outcomes. The results confirm existing research on the negative effects of discrimination. Additionally, the paper adds to the literature by highlighting the importance of an intersectional approach to examining students' perceptions of in-school discrimination. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  3. Latent growth curve analysis of fear during a speech task before and after treatment for social phobia.

    Science.gov (United States)

    Price, Matthew; Anderson, Page L

    2011-11-01

    Models of social phobia highlight the importance of anticipatory anxiety in the experience of fear during a social situation. Anticipatory anxiety has been shown to be highly correlated with performance anxiety for a variety of social situations. A few studies show that average ratings of anxiety during the anticipation and performance phases of a social situation decline following treatment. Evidence also suggests that the point of confrontation with the feared stimulus is the peak level of fear. No study to date has evaluated the pattern of anxious responding across the anticipation, confrontation, and performance phases before and after treatment, which is the focus of the current study. Socially phobic individuals (N = 51) completed a behavioral avoidance task before and after two types of manualized cognitive behavioral therapy, and gave ratings of fear during the anticipation and performance phases. Results from latent growth curve analysis were the same for the two treatments and suggested that before treatment, anxiety sharply increased during the anticipation phase, was highly elevated at the confrontation, and gradually increased during the performance phase. After treatment, anxiety increased during the anticipation phase, although at a much slower rate than at pretreatment, peaked at confrontation, and declined during the performance phase. The findings suggest that anticipatory experiences are critical to the experience of fear for public speaking and should be incorporated into exposures.

  4. A biometric latent curve analysis of memory decline in older men of the NAS-NRC twin registry.

    Science.gov (United States)

    McArdle, John J; Plassman, Brenda L

    2009-09-01

    Previous research has shown cognitive abilities to have different biometric patterns of age-changes. We examined the variation in episodic memory (word recall task) for over 6,000 twin pairs who were initially aged 59-75, and were subsequently re-assessed up to three more times over 12 years. In cross-sectional analyses, variation in the number of words recalled independent of age was explained largely by non-shared influences (65-72%), with clear additive genetic influences (12-32%), and marginal shared family influences (1-18%). The longitudinal phenotypic analysis of the word recall task showed systematic linear declines over age, but several nonlinear models with more dramatic changes at later ages, improved the overall fit. A two-part spline model for the longitudinal twin data with an optimal turning point at age 74 led to: (a) a separation of non-shared environmental influences and transient measurement error (~50%); (b) strong additive genetic components of this latent curve (~44% at age 60) with increases (over 50%) up to age 74, but with no additional genetic variation after age 74; (c) the smaller influences of shared family environment (~15% at age 74) were constant over all ages; (d) non-shared effects play an important role over most of the life-span but diminish after age 74.

  5. Use of latent profile analysis to assess the validity of a peer-rejected group of children.

    Science.gov (United States)

    Hubbard, Julie A; Smith, Marissa A; Rubin, Ronnie M

    2013-01-01

    The goal of this article was to validate the existence and qualities of a peer-rejected group of children using latent profile analysis (LPA). Two separate racially/ethnically diverse samples (Study 1: N = 2,052 second graders; Study 2: N = 594 fourth and fifth graders) completed peer nominations of liking and disliking, from which we calculated Social Preference and Social Impact scores. These scores served as indicators in the LPAs to form LPA groups. In addition, we collected self-, teacher-, and peer-report report data on aggression, depressive symptoms, peer victimization, and social competence. In each sample, an LPA group emerged in which most children were classified as rejected using the Coie, Dodge, and Coppotelli ( 1982 ; CDC) approach (Study 1: 95%; Study 2: 86%). However, in both samples, only a minority of children classified as rejected using the CDC approach fell into this LPA group (Study 1: 46%; Study 2: 36%). The LPA group that mirrored the CDC rejected group received more maladjusted scores than all other LPA groups on aggression, depressive symptoms, peer victimization, and social competence. Furthermore, when compared to children classified as rejected using only the CDC approach, children classified as rejected under both the LPA and CDC approaches were more maladjusted in terms of all sociometric and socioemotional variables. LPA analyses across two developmental levels validated the existence of an empirically derived group of children who overlapped closely with the CDC rejected group. However, this group was considerably smaller and more maladjusted than the CDC rejected group.

  6. INTEGRASI PERINGKAS DOKUMEN OTOMATIS DENGAN ALGORITMA LATENT SEMANTIC ANALYSIS (LSA PADA PERINGKAS DOKUMEN OTOMATIS UNTUK PROSES CLUSTERING DOKUMEN

    Directory of Open Access Journals (Sweden)

    Ardytha Luthfiarta

    2014-08-01

    Full Text Available Teknologi pengklasteran dokumen memiliki peran yang signifkan dalam kemajuan teknologi informasi, diantaranya mempunyai peranan penting dalam pengembangan web  di bidang akurasi kategorisasi keyword otomatis pada search engine, kategorisasi berita untuk surat kabar elektronik,  peningkatan rating situs dengan teknologi Search Engine Optimization (SEO dan sangat memungkinkan untuk diimplementasikan dalam berbagai teknologi informasi lainnya, oleh karena  itu diperlukan penelitian untuk meningkatkan ketepatan akurasi dalam pengklasteran dokumen. Dalam penelitian ini Algoritma Latent Semantic Analysis (LSA dapat melakukan proses reduksi kalimat dengan lebih baik dibandingkan algoritma Feature Based sehingga mendapatkan hasil akurasi proses clustering dokumen yang lebih akurat. Beberapa tahapan clustering dalam penelitian ini, yaitu preprocessing, peringkas dokumen otomatis dengan metode fitur, peringkas dokumen otomatis dengan LSA, pembobotan kata, dan algoritma clustering. Hasil penelitian menunjukkan tingkat akurasi menggunakan peringkas dokumen otomatis dengan LSA dalam proses clustering dokumen mencapai 71,04 % yang diperoleh pada tingkat peringkas dokumen otomatis dengan LSA 40% dibandingkan dengan hasil clustering tanpa peringkas dokumen otomatis yang hanya mencapai tingkat akurasi 65,97 %. Kata kunci: Text Mining, Clustering, Peringkas Dokumen Otomatis, LSA.

  7. Analysis of culture media screening data by projection to latent pathways: The case of Pichia pastoris X-33.

    Science.gov (United States)

    Isidro, Inês A; Ferreira, Ana R; Clemente, João J; Cunha, António E; Oliveira, Rui

    2016-01-10

    Cell culture media formulations contain hundreds of individual components in water solutions which have complex interactions with metabolic pathways. The currently used statistical design methods are empirical and very limited to explore such a large design space. In a previous work we developed a computational method called projection to latent pathways (PLP), which was conceived to maximize covariance between envirome and fluxome data under the constraint of metabolic network elementary flux modes (EFM). More specifically, PLP identifies a minimal set of EFMs (i.e., pathways) with the highest possible correlation with envirome and fluxome measurements. In this paper we extend the concept for the analysis of culture media screening data to investigate how culture medium components up-regulate or down-regulate key metabolic pathways. A Pichia pastoris X-33 strain was cultivated in 26 shake flask experiments with variations in trace elements concentrations and basal medium dilution, based on the standard BSM+PTM1 medium. PLP identified 3 EFMs (growth, maintenance and by-product formation) describing 98.8% of the variance in observed fluxes. Furthermore, PLP presented an overall predictive power comparable to that of PLS regression. Our results show iron and manganese at concentrations close to the PTM1 standard inhibit overall metabolic activity, while the main salts concentration (BSM) affected mainly energy expenditures for cellular maintenance.

  8. Cationic bis-N-heterocyclic carbene (NHC) ruthenium complex: structure and application as latent catalyst in olefin metathesis.

    Science.gov (United States)

    Rouen, Mathieu; Queval, Pierre; Falivene, Laura; Allard, Jessica; Toupet, Loïc; Crévisy, Christophe; Caijo, Frédéric; Baslé, Olivier; Cavallo, Luigi; Mauduit, Marc

    2014-10-13

    An unexpected cationic bis-N-heterocyclic carbene (NHC) benzylidene ether based ruthenium complex (2 a) was prepared through the double incorporation of an unsymmetrical unsaturated N-heterocyclic carbene (U2 -NHC) ligand that bore an N-substituted cyclododecyl side chain. The isolation and full characterization (including X-ray diffraction studies) of key synthetic intermediates along with theoretical calculations allowed us to understand the mechanism of the overall cationization process. Finally, the newly developed complex 2 a displayed interesting latent behavior during ring-closing metathesis, which could be "switched on" under acidic conditions.

  9. Cationic bis-N-heterocyclic carbene (NHC) ruthenium complex: Structure and application as latent catalyst in olefin metathesis

    KAUST Repository

    Rouen, Mathieu

    2014-09-11

    An unexpected cationic bis-N-heterocyclic carbene (NHC) benzylidene ether based ruthenium complex (2 a) was prepared through the double incorporation of an unsymmetrical unsaturated N-heterocyclic carbene (U2-NHC) ligand that bore an N-substituted cyclododecyl side chain. The isolation and full characterization (including X-ray diffraction studies) of key synthetic intermediates along with theoretical calculations allowed us to understand the mechanism of the overall cationization process. Finally, the newly developed complex 2 a displayed interesting latent behavior during ring-closing metathesis, which could be "switched on" under acidic conditions.

  10. Predictive validity of the N2 and P3 ERP components to executive functioning in children: A latent-variable analysis

    Directory of Open Access Journals (Sweden)

    Christopher Robert Brydges

    2014-02-01

    Full Text Available Executive functions (EFs are commonly theorised to be related yet separable constructs in adults, and specific EFs, such as prepotent response inhibition and working memory, are thought to have clear and distinct neural underpinnings. However, recent evidence suggests that EFs are unitary in children up to about 9 years of age. The aim of the current study was to test the hypothesis that peaks of the event-related potential (ERP of specific EFs are related to behavioral performance, despite EFs being psychometrically indistinguishable in children. Specifically, N2 difference waveform (associated with cognitive control and response inhibition and P3b peak (associated with updating of working memory latent variables were created and entered into confirmatory factor analysis and structural equation models with a unitary executive functioning factor. Children aged 7-9 years (N = 215 completed eight measures of inhibition, working memory, and shifting. A modified flanker task was also completed during which EEG data were recorded. The N2 difference waveform and P3b mean amplitude factors both significantly correlated with (and were predictors of the executive functioning factor, but the P3b latency factor did not. These results provide evidence of the electrophysiological indices of executive functions being observable before the associated behavioral constructs are distinguishable from each other. From this, it is possible that ERPs could be used as a sensitive measure of development in the context of evaluation for neuropsychological interventions.

  11. Predictive validity of the N2 and P3 ERP components to executive functioning in children: a latent-variable analysis.

    Science.gov (United States)

    Brydges, Christopher R; Fox, Allison M; Reid, Corinne L; Anderson, Mike

    2014-01-01

    Executive functions (EFs) are commonly theorized to be related yet separable constructs in adults, and specific EFs, such as prepotent response inhibition and working memory, are thought to have clear and distinct neural underpinnings. However, recent evidence suggests that EFs are unitary in children up to about 9 years of age. The aim of the current study was to test the hypothesis that peaks of the event-related potential (ERP) of specific EFs are related to behavioral performance, despite EFs being psychometrically indistinguishable in children. Specifically, N2 difference waveform (associated with cognitive control and response inhibition) and P3b peak (associated with updating of working memory) latent variables were created and entered into confirmatory factor analysis and structural equation models with a unitary executive functioning factor. Children aged 7-9 years (N = 215) completed eight measures of inhibition, working memory, and shifting. A modified flanker task was also completed during which EEG data were recorded. The N2 difference waveform and P3b mean amplitude factors both significantly correlated with (and were predictors of) the executive functioning factor, but the P3b latency factor did not. These results provide evidence of the electrophysiological indices of EFs being observable before the associated behavioral constructs are distinguishable from each other. From this, it is possible that ERPs could be used as a sensitive measure of development in the context of evaluation for neuropsychological interventions.

  12. One-year follow up of cardiac anxiety after a myocardial infarction: A latent class analysis

    NARCIS (Netherlands)

    Beek, M.H. van; Mingels, M.; Oude Voshaar, R.C.; Balkom, A.J. van; Lappenschaar, M.; Pop, G.A.; Speckens, A.E.

    2012-01-01

    INTRODUCTION: Longitudinal elevated depressive symptom scores are associated with a less favorable cardiac outcome. Although anxiety has received less attention, meta-analysis suggests that high baseline levels of general anxiety might worsen cardiac outcome. The objective of this study was to explo

  13. One-year follow up of cardiac anxiety after a myocardial infarction : A latent class analysis

    NARCIS (Netherlands)

    van Beek, M. H. C. T.; Mingels, M.; Voshaar, R. C. Oude; van Balkom, A. J. L. M.; Lappenschaar, M.; Pop, G.; Speckens, A. E. M.

    2012-01-01

    Introduction: Longitudinal elevated depressive symptom scores are associated with a less favorable cardiac outcome. Although anxiety has received less attention, meta-analysis suggests that high baseline levels of general anxiety might worsen cardiac outcome. The objective of this study was to explo

  14. A Cost-benefit Analysis of a Proposed Immigrant Latent Tuberculosis Infection Screening Program for Cyprus

    Science.gov (United States)

    Zannetos, Savvas; Talias, Michael A.

    2016-01-01

    Introduction: The study explored the potential economic benefit of an expanded screening program of immigrants before entrance to Cyprus as a policy to reduce the overall cost of tuberculosis (TB). Thus, the aim of this study is to study whether screening all immigrants coming from countries (including European Union countries) with high incidence of tuberculosis would be in the economic interest of the Republic of Cyprus or not. Methods: In order to assess whether it could be economically beneficial for Cyprus to expand the screening checks for TB to all immigrants coming from high prevalence countries, a Cost-Benefit Analysis (CBA) was employed, and the Net Present Value (NPV) of the project was calculated. In order to assess for uncertainty, sensitivity analysis using different scenarios, was conducted. Results: The analysis has a fifteen year length of implementation period and the base year (Year 0) was 2011. The NPV was estimated at €3,188,653 which is greater than zero; therefore, the expansion of screening diagnostic tests for TB to European citizens coming from countries with high prevalence of TB will have a significant benefit to the Cypriot economy and society. This result is also supported by the fact that all “what-if scenarios” of the sensitivity analysis yielded a positive NPV. Conclusion: Our study concludes that testing all immigrants, including immigrants from high prevalence European countries that are not currently tested for TB, would be a cost-saving strategy to reduce the cost of treating TB in Cyprus. PMID:28144201

  15. Patterns of Change in Willingness to Communicate in Public Speaking Contexts: A Latent Growth Modeling Analysis

    Science.gov (United States)

    Hodis, Georgeta M.; Bardhan, Nilanjana R.; Hodis, Flaviu A.

    2010-01-01

    This study offers a comprehensive analysis of change in willingness to communicate (WTC) in public speaking contexts (i.e., PS-WTC). The proposed conceptualization of change was tested using longitudinal data collected from a sample of 706 undergraduate students enrolled in an introductory communication course in a US university. Results of latent…

  16. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

    Science.gov (United States)

    Can, Seda; van de Schoot, Rens; Hox, Joop

    2015-01-01

    Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation…

  17. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

    NARCIS (Netherlands)

    Can, Seda; van de Schoot, Rens; Hox, Joop

    2014-01-01

    Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influ

  18. Latent Variable Analysis of Coping, Anxiety/Depression, and Somatic Symptoms in Adolescents with Chronic Pain

    Science.gov (United States)

    Compas, Bruce E.; Boyer, Margaret C.; Stanger, Catherine; Colletti, Richard B.; Thomsen, Alexandra H.; Dufton, Lynette M.; Cole, David A.

    2006-01-01

    Reports of adolescents' coping with recurrent pain, symptoms of anxiety/depression, and somatic complaints were obtained from a sample of 164 adolescents with recurrent abdominal pain and their parents. Confirmatory factor analysis revealed that coping consisted of 3 nonorthogonal factors: Primary Control Engagement Coping (problem solving,…

  19. Emotional Psychological and Related Problems among Truant Youths: An Exploratory Latent Class Analysis

    Science.gov (United States)

    Dembo, Richard; Briones-Robinson, Rhissa; Ungaro, Rocio Aracelis; Gulledge, Laura M.; Karas, Lora M.; Winters, Ken C.; Belenko, Steven; Greenbaum, Paul E.

    2012-01-01

    Intervention Project. Results identified two classes of youths: Class 1(n=9) - youths with low levels of delinquency, mental health and substance abuse issues; and Class 2(n=37) - youths with high levels of these problems. Comparison of these two classes on their urine analysis test results and parent/guardian reports of traumatic events found…

  20. Mining the chemical quarry with joint chemical probes: an application of latent semantic structure indexing (LaSSI) and TOPOSIM (Dice) to chemical database mining.

    Science.gov (United States)

    Singh, S B; Sheridan, R P; Fluder, E M; Hull, R D

    2001-05-10

    In this study we use a novel similarity search technique called latent semantic structure indexing (LaSSI) with joint chemical probes as queries to mine the MDL drug data report database. LaSSI is based on latent semantic indexing developed for searching textual databases. We use atom pair and topological torsion descriptors in our calculations. The results obtained with LaSSI are compared with another in-house similarity search technique TOPOSIM. The results from the similarity searches using joint chemical probes are significantly better than searches using single chemical probes for both LaSSI and TOPOSIM. The selected molecules are closely related in activity to their queries and are ranked among the top 300 scoring molecules of the 82 860 entries in the database. Our implementation of LaSSI is very fast and efficient in finding active compounds. The results also show that LaSSI consistently retrieves more diverse chemical structures representative of the joint chemical probes in comparison to TOPOSIM. The use of multimolecule topological probes to identify compounds complements the use of searching databases with 3D pharmacophore hypotheses.

  1. Analysis of selected surface characteristics and latent heat storage for passive solar space heating

    Energy Technology Data Exchange (ETDEWEB)

    Fthenakis, V.; Leigh, R.

    1981-12-01

    Results are presented of an analysis of the value of various technical improvements in the solar collector and thermal storage subsystems of passive solar residential, agricultural, and industrial systems for two regions of the country. The evaluated improvements are: decreased emissivity and increased absorptivity of absorbing surfaces, decreased reflectivity, and decreased emissivity of glazing surface, and the substitution of sensible heat storage media with phase change materials. The value of each improvement is estimated by the additional energy savings resulting from the improvement.

  2. Latent Class Analysis of Gambling Activities in a Sample of Young Swiss Men: Association with Gambling Problems, Substance Use Outcomes, Personality Traits and Coping Strategies.

    OpenAIRE

    2016-01-01

    The study aimed to identify different patterns of gambling activities (PGAs) and to investigate how PGAs differed in gambling problems, substance use outcomes, personality traits and coping strategies. A representative sample of 4989 young Swiss males completed a questionnaire assessing seven distinct gambling activities, gambling problems, substance use outcomes, personality traits and coping strategies. PGAs were identified using latent class analysis (LCA). Differences between PGAs in gamb...

  3. Victimization profiles, non-suicidal self-injury, suicide attempt, and post-traumatic stress disorder symptomology: application of latent class analysis

    OpenAIRE

    Dhingra, Katie; Boduszek, Daniel; Sharratt, Kathryn

    2016-01-01

    Few studies have incorporated multiple dimensions of victimization or examined whether victimization profiles differ by gender. Consequently, the present study sought to extend prior research by using latent class analysis (LCA) to identify naturally occurring subgroups of individuals who have experienced victimization, and to test for sex differences. Data from 4,016 females and 3,032 males in the Adult Psychiatric Morbidity Survey (APMS) were analyzed. Evidence of the existence of similar v...

  4. Application of a latent variables model for the medical images analysis; Aplicacion de un modelo de variables latentes para el analisis de imagenes medicas

    Energy Technology Data Exchange (ETDEWEB)

    Campos S, Y.; Ruiz C, S. [Centro de Investigacion en Matematica, A.C. Jalisco s/n, Col. Valenciana, Guanajuato (Mexico)

    2008-07-01

    In recent years the technological advance has allowed the significant advance in diverse research fields, the medicine has not been exempt of this technology and the use of this technology has allowed a significant advance in the equipment that are used to obtain medical images. The quantity of information that is generated with this equipment has grown in exponential form and it is a difficult task to carry out a quantitative analysis of the data also the manipulation of big quantities of information makes the medical images analysis a complicated task. It is in fact this complexity what motivates this work where one of the main objectives is the analysis of techniques that allow to work with the complexity of the data generated with medical equipment. Likewise, it is wanted to illustrate an application of the peaceful uses of the nuclear energy to treat a medical problem where the diagnostic it depends essentially on the current medical equipment to give an appropriate treatment to the patients. (Author)

  5. Diagnostic accuracy of a bayesian latent group analysis for the detection of malingering-related poor effort.

    Science.gov (United States)

    Ortega, Alonso; Labrenz, Stephan; Markowitsch, Hans J; Piefke, Martina

    2013-01-01

    In the last decade, different statistical techniques have been introduced to improve assessment of malingering-related poor effort. In this context, we have recently shown preliminary evidence that a Bayesian latent group model may help to optimize classification accuracy using a simulation research design. In the present study, we conducted two analyses. Firstly, we evaluated how accurately this Bayesian approach can distinguish between participants answering in an honest way (honest response group) and participants feigning cognitive impairment (experimental malingering group). Secondly, we tested the accuracy of our model in the differentiation between patients who had real cognitive deficits (cognitively impaired group) and participants who belonged to the experimental malingering group. All Bayesian analyses were conducted using the raw scores of a visual recognition forced-choice task (2AFC), the Test of Memory Malingering (TOMM, Trial 2), and the Word Memory Test (WMT, primary effort subtests). The first analysis showed 100% accuracy for the Bayesian model in distinguishing participants of both groups with all effort measures. The second analysis showed outstanding overall accuracy of the Bayesian model when estimates were obtained from the 2AFC and the TOMM raw scores. Diagnostic accuracy of the Bayesian model diminished when using the WMT total raw scores. Despite, overall diagnostic accuracy can still be considered excellent. The most plausible explanation for this decrement is the low performance in verbal recognition and fluency tasks of some patients of the cognitively impaired group. Additionally, the Bayesian model provides individual estimates, p(zi |D), of examinees' effort levels. In conclusion, both high classification accuracy levels and Bayesian individual estimates of effort may be very useful for clinicians when assessing for effort in medico-legal settings.

  6. Inverse problem for multivariate time series using dynamical latent variables

    Science.gov (United States)

    Zamparo, M.; Stramaglia, S.; Banavar, J. R.; Maritan, A.

    2012-06-01

    Factor analysis is a well known statistical method to describe the variability among observed variables in terms of a smaller number of unobserved latent variables called factors. While dealing with multivariate time series, the temporal correlation structure of data may be modeled by including correlations in latent factors, but a crucial choice is the covariance function to be implemented. We show that analyzing multivariate time series in terms of latent Gaussian processes, which are mutually independent but with each of them being characterized by exponentially decaying temporal correlations, leads to an efficient implementation of the expectation-maximization algorithm for the maximum likelihood estimation of parameters, due to the properties of block-tridiagonal matrices. The proposed approach solves an ambiguity known as the identifiability problem, which renders the solution of factor analysis determined only up to an orthogonal transformation. Samples with just two temporal points are sufficient for the parameter estimation: hence the proposed approach may be applied even in the absence of prior information about the correlation structure of latent variables by fitting the model to pairs of points with varying time delay. Our modeling allows one to make predictions of the future values of time series and we illustrate our method by applying it to an analysis of published gene expression data from cell culture HeLa.

  7. Structural dynamics analysis

    Science.gov (United States)

    Housner, J. M.; Anderson, M.; Belvin, W.; Horner, G.

    1985-01-01

    Dynamic analysis of large space antenna systems must treat the deployment as well as vibration and control of the deployed antenna. Candidate computer programs for deployment dynamics, and issues and needs for future program developments are reviewed. Some results for mast and hoop deployment are also presented. Modeling of complex antenna geometry with conventional finite element methods and with repetitive exact elements is considered. Analytical comparisons with experimental results for a 15 meter hoop/column antenna revealed the importance of accurate structural properties including nonlinear joints. Slackening of cables in this antenna is also a consideration. The technology of designing actively damped structures through analytical optimization is discussed and results are presented.

  8. Confirmatory factor analysis, latent profile analysis, and factor mixture modeling of the syndromes of the Child Behavior Checklist and Teacher Report Form.

    Science.gov (United States)

    Gomez, Rapson; Vance, Alasdair

    2014-12-01

    The current study used confirmatory factor analysis (CFA), latent profile analysis (LPA), and factor mixture modeling (FMM) to examine the co-occurrence of the childhood syndromes using the Child Behavior Checklist (CBCL) and Teacher Report Form (TRF). Parents and teachers completed the CBCL and TRF, respectively, for a clinic-referred sample of 720 children, ages 7-12 years. For the CBCL, the analyses indicated most support a 2-class 2-factor FMM, and for the TRF, there was most support for a 2-class 3-factor model. The classes were all syndromes at average levels and all syndromes at high levels. The findings indicate high syndrome co-occurrence. The implications of the findings for understanding syndrome co-occurrence in the CBCL and TRF, theories of syndrome co-occurrence, and the clinical use of the CBCL and TRF are discussed. (c) 2014 APA, all rights reserved.

  9. Crystallization and preliminary crystallographic analysis of latent, active and recombinantly expressed aurone synthase, a polyphenol oxidase, from Coreopsis grandiflora

    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)

  10. Structural Equation Modeling of Travel Choice Dynamics

    OpenAIRE

    Golob, Thomas F.

    1988-01-01

    This research has two objectives. The first objective is to explore the use of the modeling tool called "latent structural equations" (structural equations with latent variables) in the general field of travel behavior analysis and the more specific field of dynamic analysis of travel behavior. The second objective is to apply a latent structural equation model in order to determine the causal relationships between income, car ownership, and mobility. Many transportation researchers ...

  11. The latent structure of loneliness: testing competing factor models of the UCLA Loneliness Scale in a large adolescent sample.

    Science.gov (United States)

    Shevlin, Mark; Murphy, Siobhan; Murphy, Jamie

    2015-04-01

    This study assessed the dimensional structure of the UCLA Loneliness Scale ([UCLA-LS], UCLA-3). Data from the Northern Ireland Young Life and Times Survey (2011), a survey of 1,434 16-year-olds, was used to examine the underlying factor structure of the scale. Confirmatory factor analysis was employed to compare alternative factor analytical models that can inform the scoring of the measure and determine the degree to which different factors provided unique predictive utility. Fit statistics indicated that the best fitting model comprised three correlated factors: Isolation, Related Connectedness, and Collective Connectedness. These findings were consistent with previous findings that identified the multidimensional nature of the UCLA-LS. The study also found evidence that the subscales were differentially associated with psychiatric morbidity as measured by the General Health Questionnaire (GHQ-12) and provides a more reliable and comprehensive framework to assess the clinical significance of loneliness.

  12. Convenient preparation of high molecular weight poly(dimethylsiloxane using thermally latent NHC-catalysis: a structure-activity correlation

    Directory of Open Access Journals (Sweden)

    Stefan Naumann

    2015-11-01

    Full Text Available The polymerization of octamethylcyclotetrasiloxane (D4 is investigated using several five-, six- and seven-membered N-heterocyclic carbenes (NHCs. The catalysts are delivered in situ from thermally susceptible CO2 adducts. It is demonstrated that the polymerization can be triggered from a latent state by mild heating, using the highly nucleophilic 1,3,4,5-tetramethylimidazol-2-ylidene as organocatalyst. This way, high molecular weight PDMS is prepared (up to >400 000 g/mol, 1.6 ÐM 95%, using low catalyst loadings (0.2–0.1 mol %. Furthermore, the results suggest that a nucleophilic, zwitterionic mechanism is in operation, in preference to purely anionic polymerization.

  13. The separation of between-person and within-person components of individual change over time: a latent curve model with structured residuals.

    Science.gov (United States)

    Curran, Patrick J; Howard, Andrea L; Bainter, Sierra A; Lane, Stephanie T; McGinley, James S

    2014-10-01

    Although recent statistical and computational developments allow for the empirical testing of psychological theories in ways not previously possible, one particularly vexing challenge remains: how to optimally model the prospective, reciprocal relations between 2 constructs as they developmentally unfold over time. Several analytic methods currently exist that attempt to model these types of relations, and each approach is successful to varying degrees. However, none provide the unambiguous separation over time of between-person and within-person components of stability and change, components that are often hypothesized to exist in the psychological sciences. Our goal in this article is to propose and demonstrate a novel extension of the multivariate latent curve model to allow for the disaggregation of these effects. We begin with a review of the standard latent curve models and describe how these primarily capture between-person differences in change. We then extend this model to allow for regression structures among the time-specific residuals to capture within-person differences in change. We demonstrate this model using an artificial data set generated to mimic the developmental relation between alcohol use and depressive symptomatology spanning 5 repeated measures. We obtain a specificity of results from the proposed analytic strategy that is not available from other existing methodologies. We conclude with potential limitations of our approach and directions for future research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  14. The association between school exclusion, delinquency and subtypes of cyber- and F2F-victimizations: identifying and predicting risk profiles and subtypes using latent class analysis.

    Science.gov (United States)

    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.

  15. Evaluation of antiphospholipid antibody assays using latent class analysis to address the lack of a reference standard.

    Science.gov (United States)

    Thaler, Markus A; Bietenbeck, Andreas; Yin, Meng-Xin; Steigerwald, Udo; Holmes, Andrew B; Lindhoff-Last, Edelgard; Luppa, Peter B

    2016-12-01

    Method evaluation of new assays for the detection of antiphospholipid antibodies (aPL) such as anti-cardiolipin (aCL) or anti-β2-glycoprotein I (aβ2-GPI) is challenging, as no internationally accepted reference material is available yet. Besides a lack of standardization, unacceptable inter-laboratory comparability of established tests is regularly observed. Owing to the absence of a commonly accepted reference standard, the evaluation of two research surface plasmon resonance (SPR) biosensor assays was performed using statistical methods from latent class analysis (LCA). aCL and aβ2-GPI IgG and IgM were measured in sera from 63 antiphospholipid syndrome patients, fulfilling the Sydney criteria, and in 34 healthy controls with four commercial assays. LCA was performed on the results and sera were assigned to the antibody-positive or antibody-negative group. Sera were subsequently evaluated in the SPR assays for aCL and aβ2-GPI. Optimal cutoffs and diagnostic performances of the research systems were established employing the LCA-derived gold standard. With area under the curve results of 0.96 and 0.89 for the detection of aCL and aβ2-GPI, the research SPR assays discriminated well between antibody-positive and antibody-negative sera. Their sensitivities and specificities were comparable to the investigated commercial immunoassays. SPR assays are a suitable tool for the detection of aCL and aβ2-GPI with diagnostic performances not different from currently available commercial tests. LCA enabled the calculation of sensitivities and specificities for aPL assays in absence of a reference standard.

  16. Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

    Science.gov (United States)

    Xin, Xiuhong; Ming, Qingsen; Zhang, Jibiao; Wang, Yuping; Liu, Mingli; Yao, Shuqiao

    2016-01-01

    Self-injurious behavior (SIB) among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years) to identify SIB classes based on 11 indicators falling under direct SIB (DSIB), indirect SIB (ISIB), and suicide attempts (SAs). Social and psychological characteristics of each subgroup were examined after controlling for age and gender. Results showed that a four-class model best fit the data and each class had a distinct pattern of co-occurrence of SIBs and external measures. Class 4 (the baseline/normative group, 65.3%) had a low probability of SIB. Class 3 (severe SIB group, 3.9%) had a high probability of SIB and the poorest social and psychological status. Class 1 (DSIB+SA group, 14.2%) had similar scores for external variables compared to class 3, and included a majority of girls [odds ratio (OR) = 1.94]. Class 2 (ISIB group, 16.6%) displayed moderate endorsement of ISIB items, and had a majority of boys and older adolescents (OR = 1.51). These findings suggest that SIB is a heterogeneous entity, but it may be best explained by four homogenous subgroups that display quantitative and qualitative differences. Findings in this study will improve our understanding on SIB and may facilitate the prevention and treatment of SIB.

  17. Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

    Directory of Open Access Journals (Sweden)

    Xiuhong Xin

    Full Text Available Self-injurious behavior (SIB among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years to identify SIB classes based on 11 indicators falling under direct SIB (DSIB, indirect SIB (ISIB, and suicide attempts (SAs. Social and psychological characteristics of each subgroup were examined after controlling for age and gender. Results showed that a four-class model best fit the data and each class had a distinct pattern of co-occurrence of SIBs and external measures. Class 4 (the baseline/normative group, 65.3% had a low probability of SIB. Class 3 (severe SIB group, 3.9% had a high probability of SIB and the poorest social and psychological status. Class 1 (DSIB+SA group, 14.2% had similar scores for external variables compared to class 3, and included a majority of girls [odds ratio (OR = 1.94]. Class 2 (ISIB group, 16.6% displayed moderate endorsement of ISIB items, and had a majority of boys and older adolescents (OR = 1.51. These findings suggest that SIB is a heterogeneous entity, but it may be best explained by four homogenous subgroups that display quantitative and qualitative differences. Findings in this study will improve our understanding on SIB and may facilitate the prevention and treatment of SIB.

  18. A cost-benefit analysis of a proposed overseas refugee latent tuberculosis infection screening and treatment program.

    Science.gov (United States)

    Wingate, La'Marcus T; Coleman, Margaret S; de la Motte Hurst, Christopher; Semple, Marie; Zhou, Weigong; Cetron, Martin S; Painter, John A

    2015-12-01

    This study explored the effect of screening and treatment of refugees for latent tuberculosis infection (LTBI) before entrance to the United States as a strategy for reducing active tuberculosis (TB). The purpose of this study was to estimate the costs and benefits of LTBI screening and treatment in United States bound refugees prior to arrival. Costs were included for foreign and domestic LTBI screening and treatment and the domestic treatment of active TB. A decision tree with multiple Markov nodes was developed to determine the total costs and number of active TB cases that occurred in refugee populations that tested 55, 35, and 20 % tuberculin skin test positive under two models: no overseas LTBI screening and overseas LTBI screening and treatment. For this analysis, refugees that tested 55, 35, and 20 % tuberculin skin test positive were divided into high, moderate, and low LTBI prevalence categories to denote their prevalence of LTBI relative to other refugee populations. For a hypothetical 1-year cohort of 100,000 refugees arriving in the United States from regions with high, moderate, and low LTBI prevalence, implementation of overseas screening would be expected to prevent 440, 220, and 57 active TB cases in the United States during the first 20 years after arrival. The cost savings associated with treatment of these averted cases would offset the cost of LTBI screening and treatment for refugees from countries with high (net cost-saving: $4.9 million) and moderate (net cost-saving: $1.6 million) LTBI prevalence. For low LTBI prevalence populations, LTBI screening and treatment exceed expected future TB treatment cost savings (net cost of $780,000). Implementing LTBI screening and treatment for United States bound refugees from countries with high or moderate LTBI prevalence would potentially save millions of dollars and contribute to United States TB elimination goals. These estimates are conservative since secondary transmission from tuberculosis cases

  19. The latent structure of post-traumatic stress disorder among Arabic-speaking refugees receiving psychiatric treatment in Denmark

    DEFF Research Database (Denmark)

    Vindbjerg, Erik; Carlsson, Jessica; Mortensen, Erik Lykke

    2016-01-01

    Background: Refugees are known to have high rates of post-traumatic stress disorder (PTSD). Although recent years have seen an increase in the number of refugees from Arabic speaking countries in the Middle East, no study so far has validated the construct of PTSD in an Arabic speaking sample...... provided sufficient fit indices. However, a combination of excessively small clusters, and a case of mistranslation in the official Arabic translation of the HTQ, rendered results two of the models inadmissible. A post hoc analysis revealed that a simpler factor structure is supported, once local...

  20. Latent class analysis of the Yale-Brown Obsessive-Compulsive Scale symptoms in obsessive-compulsive disorder

    NARCIS (Netherlands)

    K.L. Delucchi; H. Katerberg; S.E. Stewart; D.A.J.P. Denys; C. Lochner; D.E. Stack; J.A. den Boer; A.J.L.M. van Balkom; M.A. Jenike; D.J. Stein; D.C. Cath; C.A. Mathews

    2011-01-01

    Objective: 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 sym

  1. Structural Analysis Made 'NESSUSary'

    Science.gov (United States)

    2005-01-01

    Everywhere you look, chances are something that was designed and tested by a computer will be in plain view. Computers are now utilized to design and test just about everything imaginable, from automobiles and airplanes to bridges and boats, and elevators and escalators to streets and skyscrapers. Computer-design engineering first emerged in the 1970s, in the automobile and aerospace industries. Since computers were in their infancy, however, architects and engineers during the time were limited to producing only designs similar to hand-drafted drawings. (At the end of 1970s, a typical computer-aided design system was a 16-bit minicomputer with a price tag of $125,000.) Eventually, computers became more affordable and related software became more sophisticated, offering designers the "bells and whistles" to go beyond the limits of basic drafting and rendering, and venture into more skillful applications. One of the major advancements was the ability to test the objects being designed for the probability of failure. This advancement was especially important for the aerospace industry, where complicated and expensive structures are designed. The ability to perform reliability and risk assessment without using extensive hardware testing is critical to design and certification. In 1984, NASA initiated the Probabilistic Structural Analysis Methods (PSAM) project at Glenn Research Center to develop analysis methods and computer programs for the probabilistic structural analysis of select engine components for current Space Shuttle and future space propulsion systems. NASA envisioned that these methods and computational tools would play a critical role in establishing increased system performance and durability, and assist in structural system qualification and certification. Not only was the PSAM project beneficial to aerospace, it paved the way for a commercial risk- probability tool that is evaluating risks in diverse, down- to-Earth application

  2. Sequence analysis of the Epstein-Barr virus (EBV) latent membrane protein-1 gene and promoter region

    DEFF Research Database (Denmark)

    Sandvej, K; Gratama, J W; Munch, M

    1997-01-01

    Sequence variations in the Epstein-Barr virus (EBV) encoded latent membrane protein-1 (LMP-1) gene have been described in a Chinese nasopharyngeal carcinoma-derived isolate (CAO), and in viral isolates from various EBV-associated tumors. It has been suggested that these genetic changes, which inc...

  3. Differential School Effects among Low, Middle, and High Social Class Composition Schools: A Multiple Group, Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    Palardy, Gregory J.

    2008-01-01

    This study uses large-scale survey data and a multiple group, multilevel latent growth curve model to examine differential school effects between low, middle, and high social class composition public schools. The results show that the effects of school inputs and school practices on learning differ across the 3 subpopulations. Moreover, student…

  4. Differential School Effects among Low, Middle, and High Social Class Composition Schools: A Multiple Group, Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    Palardy, Gregory J.

    2008-01-01

    This study uses large-scale survey data and a multiple group, multilevel latent growth curve model to examine differential school effects between low, middle, and high social class composition public schools. The results show that the effects of school inputs and school practices on learning differ across the 3 subpopulations. Moreover, student…

  5. Structural analysis of biodiversity.

    Science.gov (United States)

    Sirovich, Lawrence; Stoeckle, Mark Y; Zhang, Yu

    2010-02-24

    Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17,000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11,000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity.

  6. Data on the interexaminer variation of minutia markup on latent fingerprints.

    Science.gov (United States)

    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.

  7. Data on the interexaminer variation of minutia markup on latent fingerprints

    Directory of Open Access Journals (Sweden)

    Bradford T. Ulery

    2016-09-01

    Full Text Available 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.

  8. Community patterns of stigma towards persons living with HIV: A population-based latent class analysis from rural Vietnam

    LENUS (Irish Health Repository)

    Pharris, Anastasia

    2011-09-18

    Abstract Background The negative effects of stigma on persons living with HIV (PLHIV) have been documented in many settings and it is thought that stigma against PLHIV leads to more difficulties for those who need to access HIV testing, treatment and care, as well as to limited community uptake of HIV prevention and testing messages. In order to understand and prevent stigma towards PLHIV, it is important to be able to measure stigma within communities and to understand which factors are associated with higher stigma. Methods To analyze patterns of community stigma and determinants to stigma toward PLHIV, we performed an exploratory population-based survey with 1874 randomly sampled adults within a demographic surveillance site (DSS) in rural Vietnam. Participants were interviewed regarding knowledge of HIV and attitudes towards persons living with HIV. Data were linked to socioeconomic and migration data from the DSS and latent class analysis and multinomial logistic regression were conducted to examine stigma group sub-types and factors associated with stigma group membership. Results We found unexpectedly high and complex patterns of stigma against PLHIV in this rural setting. Women had the greatest odds of belong to the highest stigma group (OR 1.84, 95% CI 1.42-2.37), while those with more education had lower odds of highest stigma group membership (OR 0.45, 95% CI 0.32-0.62 for secondary education; OR 0.19, 95% CI 0.10-0.35 for tertiary education). Long-term migration out of the district (OR 0.61, 95% CI 0.4-0.91), feeling at-risk for HIV (OR 0.42, 95% CI 0.27-0.66), having heard of HIV from more sources (OR 0.44, 95% CI 0.3-0.66), and knowing someone with HIV (OR 0.76, 95% CI 0.58-0.99) were all associated with lower odds of highest stigma group membership. Nearly 20% of the population was highly unsure of their attitudes towards PLHIV and persons in this group had significantly lower odds of feeling at-risk for HIV (OR 0.54, 95% CI 0.33-0.90) or of knowing

  9. Different screening strategies (single or dual for the diagnosis of suspected latent tuberculosis: a cost effectiveness analysis

    Directory of Open Access Journals (Sweden)

    Rook Graham

    2010-02-01

    Full Text Available Abstract Background Previous health economic studies recommend either a dual screening strategy [tuberculin skin test (TST followed by interferon-γ-release assay (IGRA] or a single one [IGRA only] for latent tuberculosis infection (LTBI, the former largely based on claims that it is more cost-effective. We sought to examine that conclusion through the use of a model that accounts for the additional costs of adverse drug reactions and directly compares two commercially available versions of the IGRA: the Quantiferon-TB-Gold-In-Tube (QFT-GIT and T-SPOT.TB. Methods A LTBI screening model directed at screening contacts was used to perform a cost-effectiveness analysis, from a UK healthcare perspective, taking into account the risk of isoniazid-related hepatotoxicity and post-exposure TB (2 years post contact using the TST, QFT-GIT and T-SPOT.TB IGRAs. Results Examining costs alone, the TST/IGRA dual screening strategies (TST/T-SPOT.TB and TST/QFT-GIT; £162,387 and £157,048 per 1000 contacts, respectively cost less than their single strategy counterparts (T-SPOT.TB and QFT-GIT; £203,983 and £202,921 per 1000 contacts which have higher IGRA test costs and greater numbers of persons undergoing LTBI treatment. However, IGRA alone strategies direct healthcare interventions and costs more accurately to those that are truly infected. Subsequently, less contacts need to be treated to prevent an active case of TB (T-SPOT.TB and QFT-GIT; 61.7 and 69.7 contacts in IGRA alone strategies. IGRA single strategies also prevent more cases of post-exposure TB. However, this greater effectiveness does not outweigh the lower incremental costs associated with the dual strategies. Consequently, when these costs are combined with effectiveness, the IGRA dual strategies are more cost-effective than their single strategy counterparts. Comparing between the IGRAs, T-SPOT.TB-based strategies (single and dual; £39,712 and £37,206 per active TB case prevented

  10. Somatic symptom profiles in the general population: a latent class analysis in a Danish population-based health survey

    Directory of Open Access Journals (Sweden)

    Eliasen M

    2017-08-01

    Full Text Available Marie Eliasen,1 Torben Jørgensen,1–3 Andreas Schröder,4 Thomas Meinertz Dantoft,1 Per Fink,4 Chalotte Heinsvig Poulsen,1,5 Nanna Borup Johansen,1 Lene Falgaard Eplov,5 Sine Skovbjerg,1 Svend Kreiner2 1Research Centre for Prevention and Health, Centre for Health, The Capital Region of Denmark, Glostrup, 2Department of Public Health, University of Copenhagen, Copenhagen, 3Department of Clinical Medicine, Aalborg University, Aalborg, 4Research Clinic for Functional Disorders and Psychosomatics, Aarhus University Hospital, Aarhus C, 5Mental Health Centre Copenhagen, The Capital Region of Denmark, Hellerup, Denmark Purpose: The aim of this study was to identify and describe somatic symptom profiles in the general adult population in order to enable further epidemiological research within multiple somatic symptoms.Methods: Information on 19 self-reported common somatic symptoms was achieved from a population-based questionnaire survey of 36,163 randomly selected adults in the Capital Region of Denmark (55.4% women. The participants stated whether they had been considerably bothered by each symptom within 14 days prior to answering the questionnaire. We used latent class analysis to identify the somatic symptom profiles. The profiles were further described by their association with age, sex, chronic disease, and self-perceived health.Results: We identified 10 different somatic symptom profiles defined by number, type, and site of the symptoms. The majority of the population (74.0% had a profile characterized by no considerable bothering symptoms, while a minor group of 3.9% had profiles defined by a high risk of multiple somatic symptoms. The remaining profiles were more likely to be characterized by a few specific symptoms. The profiles could further be described by their associations with age, sex, chronic disease, and self-perceived health.Conclusion: The identified somatic symptom profiles could be distinguished by number, type, and site of

  11. Racial Discrimination and Racial Socialization as Predictors of African American Adolescents’ Racial Identity Development using Latent Transition Analysis

    Science.gov (United States)

    Seaton, Eleanor K.; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M.

    2013-01-01

    The current study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over three years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing or remaining constant. Racial socialization and perceptions of racial discrimination were examined as covariates to assess the association with changes in racial identity status. The results indicated that perceptions of racial discrimination were not linked to any changes in racial identity. Youth who reported higher levels of racial socialization were less likely to be in Diffuse or Foreclosed compared to the Achieved group. PMID:21875184

  12. Racial discrimination and racial socialization as predictors of African American adolescents' racial identity development using latent transition analysis.

    Science.gov (United States)

    Seaton, Eleanor K; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M

    2012-03-01

    The present study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over 3 years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium, and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing, or remaining constant. Racial socialization and perceptions of racial discrimination were examined as covariates to assess the association with changes in racial identity status. The results indicated that perceptions of racial discrimination were not linked to any changes in racial identity. Youth who reported higher levels of racial socialization were less likely to be in Diffuse or Foreclosed compared with the Achieved group. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  13. Developmental Relations between Reading and Writing at the Word, Sentence and Text Levels: A Latent Change Score Analysis.

    Science.gov (United States)

    Ahmed, Yusra; Wagner, Richard K; Lopez, Danielle

    2014-05-01

    Relations between reading and writing have been studied extensively but the less is known about the developmental nature of their interrelations. This study applied latent change score modeling to investigate longitudinal relations between reading and writing skills at the word, sentence and text levels. Latent change score models were used to compare unidirectional pathways (reading-to-writing and writing-to-reading) and bidirectional pathways in a test of nested models. Participants included 316 boys and girls who were assessed annually in grades 1 through 4. Measures of reading included pseudo-word decoding, sentence reading efficiency, oral reading fluency and passage comprehension. Measures of writing included spelling, a sentence combining task and writing prompts. Findings suggest that a reading-to-writing model better described the data for the word and text levels of language, but a bidirectional model best fit the data at the sentence level.

  14. Peach latent mosaic viroid: not so latent.

    Science.gov (United States)

    Flores, Ricardo; Delgado, Sonia; Rodio, María-Elena; Ambrós, Silvia; Hernández, Carmen; Serio, Francesco D I

    2006-07-01

    SUMMARY Taxonomy: Peach latent mosaic viroid (PLMVd) is the type species of the genus Pelamoviroid within the family Avsunviroidae of chloroplastic viroids with hammerhead ribozymes. Physical properties: A small circular RNA of 336-351 nt (differences in size result from the absence or presence of certain insertions) adopting a branched conformation stabilized by a pseudoknot between two kissing loops. This particular conformation is most likely responsible for the insolubility of PLMVd in highly saline conditions (in which other viroids adopting a rod-like conformation are soluble). Both polarity strands are able to form hammerhead structures and to self-cleave during replication as predicted by these ribozymes. Biological properties: Although most infections occur without conspicuous symptoms, certain PLMVd isolates induce leaf mosaics, blotches and in the most extreme cases albinism (peach calico, PC), flower streaking, delays in foliation, flowering and ripening, deformations and decolorations of fruits, which usually present cracked sutures and enlarged roundish stones, bud necrosis, stem pitting and premature ageing of the trees, which also adopt a characteristic growing pattern (open habit). The molecular determinant for PC has been mapped at a 12-14-nt insertion that folds into a hairpin capped by a U-rich loop present only in certain variants. PLMVd is horizontally transmitted by the propagation of infected buds and to a lesser extent by pruning tools and aphids, but not by pollen; the viroid is not vertically transmitted through seed. Interesting features: This provides a suitable system for studying how a minimal non-protein-coding catalytic RNA replicates (subverting a DNA-dependent RNA polymerase to transcribe an RNA template), moves, interferes with the metabolism of its host (inciting specific symptoms and a defensive RNA silencing response) and evolves following a quasi-species model characterized by a complex spectrum of variants.

  15. An Empirical Comparison of Latent Trait Theory and Hierarchical Factor Analysis in Applications to the Measurements of Job Satisfaction.

    Science.gov (United States)

    1980-03-01

    or attitudes in general. In fact, except for some related models developed by by Lazarsfeld and described in Lazarafeld and Henry (1968), there has...and job characteristics. Technical report 78-4, University of Illinois, 1978. Lazarsfeld , P. F. and Henry, N. W. Latent Atru Analss. Lew York: Houghton...53706 Dr. John P. Trench, Jr. Dr. Paul S. Goodman University of Michigan Graduate School of Industrial Institute for Social Research Administration

  16. Latent Period of Relaxation.

    Science.gov (United States)

    Kobayashi, M; Irisawa, H

    1961-10-27

    The latent period of relaxation of molluscan myocardium due to anodal current is much longer than that of contraction. Although the rate and the grade of relaxation are intimately related to both the stimulus condition and the muscle tension, the latent period of relaxation remains constant, except when the temperature of the bathing fluid is changed.

  17. Latent myofascial trigger points.

    Science.gov (United States)

    Ge, Hong-You; Arendt-Nielsen, Lars

    2011-10-01

    A latent myofascial trigger point (MTP) is defined as a focus of hyperirritability in a muscle taut band that is clinically associated with local twitch response and tenderness and/or referred pain upon manual examination. Current evidence suggests that the temporal profile of the spontaneous electrical activity at an MTP is similar to focal muscle fiber contraction and/or muscle cramp potentials, which contribute significantly to the induction of local tenderness and pain and motor dysfunctions. This review highlights the potential mechanisms underlying the sensory-motor dysfunctions associated with latent MTPs and discusses the contribution of central sensitization associated with latent MTPs and the MTP network to the spatial propagation of pain and motor dysfunctions. Treating latent MTPs in patients with musculoskeletal pain may not only decrease pain sensitivity and improve motor functions, but also prevent latent MTPs from transforming into active MTPs, and hence, prevent the development of myofascial pain syndrome.

  18. The latent class structure of the posttraumatic stress disorder among adolescent%青少年创伤后应激障碍的潜类别结构分析

    Institute of Scientific and Technical Information of China (English)

    王孟成; 任芬; 吴艳

    2014-01-01

    目的 探索青少年创伤后应激障碍的潜类别结构或群体异质性.方法 采用中文创伤后应激障碍检查表(The PTSD Checklist,PCL)测试了560名受汶川地震影响的青少年,并使用潜类别模型分析数据.结果 依据潜类别分析结果可以将其分成高症状组(115人,20.5%),无症状组(165人,29.5%),中等症状伴情感麻木组(188人,33.6%)和中等症状伴低回避组(92人,16.4%).男生在4个类别中分别为55.7%,49.7%,50.5%和50.4%,各类别比例性别差异无统计学意义,x2=1.56,P=0.669.结论 青少年PTSD症状可以分成四个潜类别,临床上应考虑不同的干预方案.%Objective To explore the latent class structure and heterogeneity of posttraumatic stress disorder(PTSD) in adolescent.Methods The Chinese PTSD Checklist-Civilian Version (PCL-C) was used to assess 560 adolescent from the Wenchuan earthquake area.Latent Class Model was employed to analyze the data.Results Latent Class Analysis revealed four classes of adolescent PTSD sample:pervasive disturbance (n=115,20.5%),no disturbance (n=165,29.5%),Intermediate Symptom with high Emotional Numbing (n=188,33.6%),as well as Intermediate Symptom with low avoidance (n=92,16.4%).The proportion of boys in each subsample were 55.7%,49.7%,50.5% and 50.4%,respectively.In addition,there was no significant gender difference of prevalence within each class (x2=1.56,P=0.669).Conclusions Four-class model best fit the data for PTSD symptoms,and different clinical intervention should be adopted.

  19. Latent fingerprint matching.

    Science.gov (United States)

    Jain, Anil K; Feng, Jianjiang

    2011-01-01

    Latent fingerprint identification is of critical importance to law enforcement agencies in identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on surfaces of objects. While tremendous progress has been made in plain and rolled fingerprint matching, latent fingerprint matching continues to be a difficult problem. Poor quality of ridge impressions, small finger area, and large nonlinear distortion are the main difficulties in latent fingerprint matching compared to plain or rolled fingerprint matching. We propose a system for matching latent fingerprints found at crime scenes to rolled fingerprints enrolled in law enforcement databases. In addition to minutiae, we also use extended features, including singularity, ridge quality map, ridge flow map, ridge wavelength map, and skeleton. We tested our system by matching 258 latents in the NIST SD27 database against a background database of 29,257 rolled fingerprints obtained by combining the NIST SD4, SD14, and SD27 databases. The minutiae-based baseline rank-1 identification rate of 34.9 percent was improved to 74 percent when extended features were used. In order to evaluate the relative importance of each extended feature, these features were incrementally used in the order of their cost in marking by latent experts. The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.

  20. Knowledge and Attitudes towards Antibiotic Use and Resistance - A Latent Class Analysis of a Swedish Population-Based Sample

    Science.gov (United States)

    Rosales-Klintz, Senia; Tegmark Wisell, Karin; Stålsby Lundborg, Cecilia

    2016-01-01

    Background In 2006, a study investigating knowledge and attitudes regarding antibiotic use and resistance in Sweden, indicated high level of knowledge but also areas in need of improvement. Objective (i) To provide an update on the knowledge and attitudes to antibiotic use and resistance of the Swedish population, and (ii) to identify which groups within the population are in particular need of improved knowledge or attitudes. Methods A questionnaire was sent by post in 2013 to 2,500 randomly-selected individuals aged 18–74, living in Sweden. Latent class analyses were conducted to group respondents based on their responses. The association between socio-demographic characteristics and the probability of belonging to each latent class was assessed. Results The response rate was 57%. Ninety-four per cent of the responders knew that bacteria could become resistant to antibiotics and the majority answered correctly to the questions regarding antibiotic resistance development. The respondents expressed confidence in doctors who decided not to prescribe antibiotics. Three latent classes related to ‘knowledge regarding antibiotic use and resistance’, two regarding ‘attitudes towards antibiotic accessibility and infection prevention’ and three regarding ‘attitudes towards antibiotic use and effects’ were revealed. Men, younger and more educated people were more knowledgeable but males had a less restrictive attitude. Respondents with high levels of knowledge on antibiotics were more likely to have appropriate restrictive attitudes to antibiotics. Conclusion Knowledge on antibiotic use and resistance is maintained high and has improved in Sweden compared to 2006. People with lower education and elderly are especially in need of improved knowledge about antibiotic use and resistance. PMID:27096751

  1. Knowledge and Attitudes towards Antibiotic Use and Resistance - A Latent Class Analysis of a Swedish Population-Based Sample.

    Science.gov (United States)

    Vallin, Martina; Polyzoi, Maria; Marrone, Gaetano; Rosales-Klintz, Senia; Tegmark Wisell, Karin; Stålsby Lundborg, Cecilia

    2016-01-01

    In 2006, a study investigating knowledge and attitudes regarding antibiotic use and resistance in Sweden, indicated high level of knowledge but also areas in need of improvement. (i) To provide an update on the knowledge and attitudes to antibiotic use and resistance of the Swedish population, and (ii) to identify which groups within the population are in particular need of improved knowledge or attitudes. A questionnaire was sent by post in 2013 to 2,500 randomly-selected individuals aged 18-74, living in Sweden. Latent class analyses were conducted to group respondents based on their responses. The association between socio-demographic characteristics and the probability of belonging to each latent class was assessed. The response rate was 57%. Ninety-four per cent of the responders knew that bacteria could become resistant to antibiotics and the majority answered correctly to the questions regarding antibiotic resistance development. The respondents expressed confidence in doctors who decided not to prescribe antibiotics. Three latent classes related to 'knowledge regarding antibiotic use and resistance', two regarding 'attitudes towards antibiotic accessibility and infection prevention' and three regarding 'attitudes towards antibiotic use and effects' were revealed. Men, younger and more educated people were more knowledgeable but males had a less restrictive attitude. Respondents with high levels of knowledge on antibiotics were more likely to have appropriate restrictive attitudes to antibiotics. Knowledge on antibiotic use and resistance is maintained high and has improved in Sweden compared to 2006. People with lower education and elderly are especially in need of improved knowledge about antibiotic use and resistance.

  2. Modeling the latent dimensions of multivariate signaling datasets

    Science.gov (United States)

    Jensen, Karin J.; Janes, Kevin A.

    2012-08-01

    Cellular signal transduction is coordinated by modifications of many proteins within cells. Protein modifications are not independent, because some are connected through shared signaling cascades and others jointly converge upon common cellular functions. This coupling creates a hidden structure within a signaling network that can point to higher level organizing principles of interest to systems biology. One can identify important covariations within large-scale datasets by using mathematical models that extract latent dimensions—the key structural elements of a measurement set. In this paper, we introduce two principal component-based methods for identifying and interpreting latent dimensions. Principal component analysis provides a starting point for unbiased inspection of the major sources of variation within a dataset. Partial least-squares regression reorients these dimensions toward a specific hypothesis of interest. Both approaches have been used widely in studies of cell signaling, and they should be standard analytical tools once highly multivariate datasets become straightforward to accumulate.

  3. Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

    Science.gov (United States)

    Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

    2017-11-01

    To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.

  4. Latent geometry of bipartite networks

    CERN Document Server

    Kitsak, Maksim; Krioukov, Dmitri

    2016-01-01

    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 appli...

  5. Crystallization and preliminary X-ray crystallographic analysis of latent isoform PPO4 mushroom (Agaricus bisporus) tyrosinase

    Energy Technology Data Exchange (ETDEWEB)

    Mauracher, Stephan Gerhard; Molitor, Christian [Universität Wien, Althanstrasse 14, 1090 Wien (Austria); Al-Oweini, Rami; Kortz, Ulrich [Jacobs University, PO Box 750 561, 28759 Bremen (Germany); Rompel, Annette, E-mail: annette.rompel@univie.ac.at [Universität Wien, Althanstrasse 14, 1090 Wien (Austria)

    2014-01-23

    Polyphenol oxidase 4 (PPO4) from the natural source A. bisporus was crystallized in its latent precursor form (pro-tyrosinase; Ser2–Thr565) using the 6-tungstotellurate(VI) salt Na{sub 6}[TeW{sub 6}O{sub 24}]·22H{sub 2}O as a crystallization additive. Tyrosinase exhibits catalytic activity for the ortho-hydroxylation of monophenols to diphenols as well as their subsequent oxidation to quinones. Owing to polymerization of these quinones, brown-coloured high-molecular-weight compounds called melanins are generated. The latent precursor form of polyphenol oxidase 4, one of the six tyrosinase isoforms from Agaricus bisporus, was purified to homogeneity and crystallized. The obtained crystals belonged to space group C121 (two molecules per asymmetric unit) and diffracted to 2.78 Å resolution. The protein only formed crystals under low-salt conditions using the 6-tungstotellurate(VI) salt Na{sub 6}[TeW{sub 6}O{sub 24}]·22H{sub 2}O as a co-crystallization agent.

  6. Numerical Analysis of Shell-and-Tube Type Latent Thermal Energy Storage Performance with Different Arrangements of Circular Fins

    Directory of Open Access Journals (Sweden)

    Sebastian Kuboth

    2017-02-01

    Full Text Available Latent thermal energy storage (LTS systems are versatile due to their high-energy storage density within a small temperature range. In shell-and-tube type storage systems fins can be used in order to achieve enhanced charging and discharging power. Typically, circular fins are evenly distributed over the length of the heat exchanger pipe. However, it is yet to be proven that this allocation is the most suitable for every kind of system and application. Consequently, within this paper, a simulation model was developed in order to examine the effect of different fin distributions on the performance of shell-and-tube type latent thermal storage units at discharge. The model was set up in MATLAB Simulink R2015b (The MathWorks, Inc., Natick, MA, USA based on the enthalpy method and validated by a reference model designed in ANSYS Fluent 15.0 (ANSYS, Inc., Canonsburg, PA, USA. The fin density of the heat exchanger pipe was increased towards the pipe outlet. This concentration of fins was implemented linearly, exponentially or suddenly with the total number of fins remaining constant during the variation of fin allocations. Results show that there is an influence of fin allocation on storage performance. However, the average storage performance at total discharge only increased by three percent with the best allocation compared to an equidistant arrangement.

  7. Sensitivity and specificity of PCR analysis and bacteriological culture of milk samples for identification of intramammary infections in dairy cows using latent class analysis.

    Science.gov (United States)

    Nyman, A-K; Persson Waller, K; Emanuelson, U; Frössling, J

    2016-12-01

    Real-time PCR analysis of milk samples is a fast method to identify intramammary infections (IMI) in dairy cows, and has the potential to be used for routine analysis of test milking composite milk samples. However, the results of the PCR analysis can be difficult to interpret. The objective of this study was to compare the sensitivity (Se) and specificity (Sp) of PCR analysis of composite milk samples, and conventional bacteriological culturing (BC) of quarter milk samples, when used to identify cows with IMI. The comparisons were performed for IMI with four common udder pathogens; Staphylococcus aureus (S aureus), Streptococcus dysgalactiae (Str dysgalactiae), Str uberis and coagulase negative staphylococci (CoNS). The Se and Sp of real-time PCR (SePCR; SpPCR) and BC (SeBC; SpBC) was simultaneously estimated using latent class analysis (LCA), studying one pathogen at the time. Milk samples from 970 dairy cows from 25 herds were included. Aseptically collected quarter milk samples taken at the day before test milking (TM), at the day of TM, and at the day after TM, were analyzed using BC. Non-aseptically collected composite milk samples taken at the day of TM were analyzed using PCR. Moreover, the composite milk somatic cell count (SCC) was recorded and summarized by diagnostic test and bacterial finding. LCA was first performed using only test results from samples taken at the day of TM, but in a second analysis BC results from the three consecutive samplings, interpreted in parallel, were included. The SePCR was significantly higher than the SeBC for S aureus, Str dysgalactiae and CoNS in the first analysis, but only for CoNS in the second analysis. The SpPCR was significantly lower than the SpBC for Str dysgalactiae and CoNS. In conclusion, using PCR analysis of composite milk samples, as a diagnostic tool for identifying cows with IMI increased the Se for all the pathogens investigated (although not always significantly), while Sp in general remained on a

  8. Sífilis latente

    OpenAIRE

    Arévalo, Jose David

    2012-01-01

    Trabajo leído por su autor en la Academia Nacional de Medicina, el día 20 de mayo de 1948. La sífilis Latente es aquella en que el organismo se ha defendido biológicamente sin ningún tratamiento, En la sífilis latente hay que distinguir: la latencia clínica, la latencia serológica y la latencia patológica.

  9. Latent catalyst; Senzaisei shokubai

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-03-01

    Epoxy resin, an important function material to support such main industries as electric and electronic devices, automobiles, civil engineering, and building construction, is demanded of development of single liquid type resin having excellent quick hardening performance and storage stability. This requirement comes from environmental problems with an intention of saving energies and reducing resin wastes. The Company, using freely its independent phase separation technology that controls molecular structure of catalysts, developed a latent catalyst having excellent storage stability and high-temperature quick hardening performance. Its major features may be summarized as follows: (1) excellent storage stability at room temperature keeping the product stable for 2.5 months or longer (2 days in conventional products); (2) quick hardening performance hardening the resin in seven seconds at 150 degrees C (equivalent to conventional products); and (3) excellent insulation performance of hardened resin at 140 degrees C of 7 times 10 {sup 13} (ohm) (center dot) cm (2 times 10 {sup 12} (ohm) (center dot) cm in conventional products) (translated by NEDO)

  10. 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.

  11. A Latent Class Analysis of Risk Factors for Acquiring HIV Among Men Who Have Sex with Men: Implications for Implementing Pre-Exposure Prophylaxis Programs.

    Science.gov (United States)

    Chan, Philip A; Rose, Jennifer; Maher, Justine; Benben, Stacey; Pfeiffer, Kristen; Almonte, Alexi; Poceta, Joanna; Oldenburg, Catherine E; Parker, Sharon; Marshall, Brandon Dl; Lally, Mickey; Mayer, Kenneth; Mena, Leandro; Patel, Rupa; Nunn, Amy S

    2015-11-01

    Current Centers for Disease Control and Prevention (CDC) guidelines for prescribing pre-exposure prophylaxis (PrEP) to prevent HIV transmission are broad. In order to better characterize groups who may benefit most from PrEP, we reviewed demographics, behaviors, and clinical outcomes for individuals presenting to a publicly-funded sexually transmitted diseases (STD) clinic in Providence, Rhode Island, from 2012 to 2014. Latent class analysis (LCA) was used to identify subgroups of men who have sex with men (MSM) at highest risk for contracting HIV. A total of 1723 individuals presented for testing (75% male; 31% MSM). MSM were more likely to test HIV positive than heterosexual men or women. Among 538 MSM, we identified four latent classes. Class 1 had the highest rates of incarceration (33%), forced sex (24%), but had no HIV infections. Class 2 had 10 anal sex partners in the previous 12 months (69%), anonymous partners (100%), drug/alcohol use during sex (76%), and prior STDs (40%). Class 4 had similar characteristics and HIV prevalence as Class 2. In this population, MSM who may benefit most from PrEP include those who have >10 sexual partners per year, anonymous partners, drug/alcohol use during sex and prior STDs. LCA is a useful tool for identifying clusters of characteristics that may place individuals at higher risk for HIV infection and who may benefit most from PrEP in clinical practice.

  12. Patterns of DSM-5 posttraumatic stress disorder and depression symptoms in an epidemiological sample of Chinese earthquake survivors: A latent profile analysis.

    Science.gov (United States)

    Cao, Xing; Wang, Li; Cao, Chengqi; Zhang, Jianxin; Liu, Ping; Zhang, Biao; Wu, Qi; Zhang, Hong; Zhao, Zhihong; Fan, Gaolin; Elhai, Jon D

    2015-11-01

    Posttraumatic stress disorder (PTSD) and depression are highly comorbid in association with serious clinical consequences. Nevertheless, to date, no study using latent class or latent profile analysis (LCA/LPA) has examined patterns of co-occurring PTSD and depression symptoms among natural disaster survivors, nor has the distinctiveness of DSM-5 PTSD and depression symptoms been clarified in the aftermath of trauma. This study was primarily aimed at filling these gaps. LPA was used to examine self-reported PTSD and depression symptoms in an epidemiological sample of 1196 Chinese earthquake survivors. A 4-class solution characterized by low symptoms (53.9%), predominantly depression (18.2%), predominantly PTSD (18.9%) and combined PTSD-depression (9.0%) patterns fit the data best. Demographic characteristics and earthquake-related exposures were specifically or consistently associated with the non-parallel profiles varying in physical health impairment. A sample exposed to specific traumatic events was assessed by self-report measures. The distinctiveness of DSM-5 PTSD and depression symptoms following an earthquake suggests that PTSD and depression may be independent sequelae of psychological trauma rather than a manifestation of a single form of psychopathology. The current findings support the distinction between PTSD and depression constructs, and highlight the need for identifications of natural disaster survivors at high risk for PTSD and/or depression, and interventions individually tailored to one's symptom presentations. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Adherence styles of schizophrenia patients identified by a latent class analysis of the Medication Adherence Rating Scale (MARS): a six-month follow-up study.

    Science.gov (United States)

    Jaeger, Susanne; Pfiffner, Carmen; Weiser, Prisca; Kilian, Reinhold; Becker, Thomas; Längle, Gerhard; Eschweiler, Gerhard Wilhelm; Croissant, Daniela; Schepp, Wiltrud; Steinert, Tilman

    2012-12-30

    The purpose of this study was to examine patients' response profiles to the Medication Adherence Rating Scale (MARS) and to evaluate the potential of response styles as predictors of the future course of psychotic disorders in terms of rehospitalisation and maintenance of medication. A total of 371 psychiatric in-patients with schizophrenia or schizoaffective disorder who were taking part in a naturalistic long-term study completed a German version of the MARS. A Latent Class Analysis (LCA) was performed. Five latent classes of response styles could be identified: "moderately adherent", "critical discontinuers", "good compliers", "careless and forgetful", and "compliant sceptics". Class membership was found to be related to the severity of symptoms, level of functioning, insight into illness, insight into necessity of treatment, treatment satisfaction and medication side effects. At a six-month follow-up appointment, significant differences between the classes persisted. Participants showing a "good compliers" response pattern had a significantly better prognosis in terms of rehospitalisation rate and maintenance of the original medication than "critical discontinuers". Evaluation of the MARS by studying response profiles provides informative results that reach beyond the results obtained by an evaluation by scores. Patients can be classified into adherence groups that are of predictive value for long-term patient outcome.

  14. Victimization Profiles, Non-Suicidal Self-Injury, Suicide Attempt, and Post-Traumatic Stress Disorder Symptomology: Application of Latent Class Analysis.

    Science.gov (United States)

    Dhingra, Katie; Boduszek, Daniel; Sharratt, Kathryn

    2016-09-01

    Few studies have incorporated multiple dimensions of victimization or examined whether victimization profiles differ by gender. Consequently, the present study sought to extend prior research by using latent class analysis (LCA) to identify naturally occurring subgroups of individuals who have experienced victimization, and to test for sex differences. Data from 4,016 females and 3,032 males in the Adult Psychiatric Morbidity Survey (APMS) were analyzed. Evidence of the existence of similar victimization subtypes for both males and females emerged, with a three-class solution providing the best fit to the data for both sexes. Furthermore, the classes were labeled "low victimization" (the baseline class; Class 3), the "high victimization class" (Class 1), and "the bullying and domestic violence class" (Class 2) for both males and females. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the associations with post-traumatic stress disorder (PTSD) dimensions, suicide attempt, and non-suicidal self-injury. Although different constellations of victimization experiences did not emerge through the gender-specific analyses, the nature of the associations between class membership and external variables differed between males and females. Findings highlight the heterogeneity of victimization experiences and their relations to functioning, and have implications for policy and practice implications.

  15. A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

    Science.gov (United States)

    Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

    2016-10-05

    Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9(th) or 10(th) grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.

  16. Learning with Latent Factors in Time Series

    CERN Document Server

    Jalali, Ali

    2011-01-01

    This paper considers the problem of learning, from samples, the dependency structure of a system of linear stochastic differential equations, when some of the variables are latent. In particular, we observe the time evolution of some variables, and never observe other variables; from this, we would like to find the dependency structure between the observed variables -- separating out the spurious interactions caused by the (marginalizing out of the) latent variables' time series. We develop a new method, based on convex optimization, to do so in the case when the number of latent variables is smaller than the number of observed ones. For the case when the dependency structure between the observed variables is sparse, we theoretically establish a high-dimensional scaling result for structure recovery. We verify our theoretical result with both synthetic and real data (from the stock market).

  17. Numerical analysis of melting of nano-enhanced phase change material in latent heat thermal energy storage system

    Directory of Open Access Journals (Sweden)

    Kashani Sina

    2014-01-01

    Full Text Available The heat transfer enhancement in the latent heat thermal energy storage system through dispersion of nanoparticle is reported. The resulting nanoparticle-enhanced phase change materials exhibit enhanced thermal conductivity in comparison to the base material. Calculation is performed for nanoparticle volume fraction from 0 to 0.08. In this study rectangular and cylindrical containers are modeled numerically and the effect of containers dimensions and nano particle volume fraction are studied. It has been found that the rectangular container requires half of the melting time as for the cylindrical container of the same volume and the same heat transfer area and also, higher nano particle volume fraction result in a larger solid fraction. The increase of the heat release rate of the nanoparticle-enhanced phase change materials shows its great potential for diverse thermal energy storage application.

  18. Crystallization and preliminary X-ray crystallographic analysis of latent isoform PPO4 mushroom (Agaricus bisporus) tyrosinase.

    Science.gov (United States)

    Mauracher, Stephan Gerhard; Molitor, Christian; Al-Oweini, Rami; Kortz, Ulrich; Rompel, Annette

    2014-02-01

    Tyrosinase exhibits catalytic activity for the ortho-hydroxylation of monophenols to diphenols as well as their subsequent oxidation to quinones. Owing to polymerization of these quinones, brown-coloured high-molecular-weight compounds called melanins are generated. The latent precursor form of polyphenol oxidase 4, one of the six tyrosinase isoforms from Agaricus bisporus, was purified to homogeneity and crystallized. The obtained crystals belonged to space group C121 (two molecules per asymmetric unit) and diffracted to 2.78 Å resolution. The protein only formed crystals under low-salt conditions using the 6-tungstotellurate(VI) salt Na6[TeW6O24] · 22H2O as a co-crystallization agent.

  19. Gender and Facebook motives as predictors of specific types of Facebook use: A latent growth curve analysis in adolescence.

    Science.gov (United States)

    Frison, Eline; Eggermont, Steven

    2016-10-01

    Despite increasing evidence that specific types of Facebook use (i.e., active private, active public, and passive Facebook use) are differently related to adolescents' well-being, little is known how these types function over the course of adolescence and whether gender and Facebook motives may predict the initial level and changes in these types over time. To address these gaps, Flemish adolescents (ages 12-19) were questioned at three different time points, with six months in between (NTime1 = 1866). Latent growth curve models revealed that active private Facebook use increased over the course of adolescence, whereas public Facebook use decreased. Passive Facebook use, however, remained stable. In addition, gender and Facebook motives were related to initial levels of specific types of Facebook use, and predictive of dynamic change in specific types of Facebook use over time. The discussion focuses on the understanding and implications of these findings.

  20. How does consumer knowledge affect environmentally sustainable choices? Evidence from a cross-country latent class analysis of food labels.

    Science.gov (United States)

    Peschel, Anne O; Grebitus, Carola; Steiner, Bodo; Veeman, Michele

    2016-11-01

    This paper examines consumers' knowledge and lifestyle profiles and preferences regarding two environmentally labeled food staples, potatoes and ground beef. Data from online choice experiments conducted in Canada and Germany are analyzed through latent class choice modeling to identify the influence of consumer knowledge (subjective and objective knowledge as well as usage experience) on environmentally sustainable choices. We find that irrespective of product or country under investigation, high subjective and objective knowledge levels drive environmentally sustainable food choices. Subjective knowledge was found to be more important in this context. Usage experience had relatively little impact on environmentally sustainable choices. Our results suggest that about 20% of consumers in both countries are ready to adopt footprint labels in their food choices. Another 10-20% could be targeted by enhancing subjective knowledge, for example through targeted marketing campaigns.

  1. Non-linear modeling of 1H NMR metabonomic data using kernel-based orthogonal projections to latent structures optimized by simulated annealing.

    Science.gov (United States)

    Fonville, Judith M; Bylesjö, Max; Coen, Muireann; Nicholson, Jeremy K; Holmes, Elaine; Lindon, John C; Rantalainen, Mattias

    2011-10-31

    Linear multivariate projection methods are frequently applied for predictive modeling of spectroscopic data in metabonomic studies. The OPLS method is a commonly used computational procedure for characterizing spectral metabonomic data, largely due to its favorable model interpretation properties providing separate descriptions of predictive variation and response-orthogonal structured noise. However, when the relationship between descriptor variables and the response is non-linear, conventional linear models will perform sub-optimally. In this study we have evaluated to what extent a non-linear model, kernel-based orthogonal projections to latent structures (K-OPLS), can provide enhanced predictive performance compared to the linear OPLS model. Just like its linear counterpart, K-OPLS provides separate model components for predictive variation and response-orthogonal structured noise. The improved model interpretation by this separate modeling is a property unique to K-OPLS in comparison to other kernel-based models. Simulated annealing (SA) was used for effective and automated optimization of the kernel-function parameter in K-OPLS (SA-K-OPLS). Our results reveal that the non-linear K-OPLS model provides improved prediction performance in three separate metabonomic data sets compared to the linear OPLS model. We also demonstrate how response-orthogonal K-OPLS components provide valuable biological interpretation of model and data. The metabonomic data sets were acquired using proton Nuclear Magnetic Resonance (NMR) spectroscopy, and include a study of the liver toxin galactosamine, a study of the nephrotoxin mercuric chloride and a study of Trypanosoma brucei brucei infection. Automated and user-friendly procedures for the kernel-optimization have been incorporated into version 1.1.1 of the freely available K-OPLS software package for both R and Matlab to enable easy application of K-OPLS for non-linear prediction modeling.

  2. Structures and their analysis

    CERN Document Server

    Fuchs, Maurice Bernard

    2016-01-01

    Addressing structures, this book presents a classic discipline in a modern setting by combining illustrated examples with insights into the solutions. It is the fruit of the author’s many years of teaching the subject and of just as many years of research into the design of optimal structures. Although intended for an advanced level of instruction it has an undergraduate course at its core. Further, the book was written with the advantage of having massive computer power in the background, an aspect which changes the entire approach to many engineering disciplines and in particular to structures. This paradigm shift has dislodged the force (flexibility) method from its former prominence and paved the way for the displacement (stiffness) method, despite the multitude of linear equations it spawns. In this book, however, both methods are taught: the force method offers a perfect vehicle for understanding structural behavior, bearing in mind that it is the displacement method which does the heavy number crunch...

  3. Structured Analysis - IDEF0

    DEFF Research Database (Denmark)

    Larsen, Michael Holm

    1999-01-01

    that require a modelling technique for the analysis, development, re-engineering, integration, or acquisition of information systems; and incorporate a systems or enterprise modelling technique into a business process analysis or software engineering methodology.This note is a summary of the Standard...

  4. The latent structure of post-traumatic stress disorder among Arabic-speaking refugees receiving psychiatric treatment in Denmark

    DEFF Research Database (Denmark)

    Vindbjerg, Erik; Carlsson, Jessica; Mortensen, Erik Lykke;

    2016-01-01

    Background: Refugees are known to have high rates of post-traumatic stress disorder (PTSD). Although recent years have seen an increase in the number of refugees from Arabic speaking countries in the Middle East, no study so far has validated the construct of PTSD in an Arabic speaking sample...... of refugees. Methods: Responses to the Harvard Trauma Questionnaire (HTQ) were obtained from 409 Arabic-speaking refugees diagnosed with PTSD and undergoing treatment in Denmark. Confirmatory factor analysis was used to test and compare five alternative models. Results: All four- and five-factor models...... dependence is addressed. Conclusions: Overall, the construct of PTSD is supported in this sample of Arabic-speaking refugees. Apart from pursuing maximum fit, future studies may wish to test simpler, potentially more stable models, which allow a more informative analysis of individual items....

  5. The latent structure of post-traumatic stress disorder among Arabic-speaking refugees receiving psychiatric treatment in Denmark

    DEFF Research Database (Denmark)

    Vindbjerg, Erik; Carlsson, Jessica; Mortensen, Erik Lykke;

    2016-01-01

    Background: Refugees are known to have high rates of post-traumatic stress disorder (PTSD). Although recent years have seen an increase in the number of refugees from Arabic speaking countries in the Middle East, no study so far has validated the construct of PTSD in an Arabic speaking sample...... of refugees. Methods: Responses to the Harvard Trauma Questionnaire (HTQ) were obtained from 409 Arabic-speaking refugees diagnosed with PTSD and undergoing treatment in Denmark. Confirmatory factor analysis was used to test and compare five alternative models. Results: All four- and five-factor models...... dependence is addressed. Conclusions: Overall, the construct of PTSD is supported in this sample of arabic-speaking refugees. Apart from pursuing maximum fit, future studies may wish to test simpler, potentially more stable models, which allow a more informative analysis of individual items....

  6. A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.

    Science.gov (United States)

    Kent, Peter; Jensen, Rikke K; Kongsted, Alice

    2014-10-02

    There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets

  7. 基于混合概率潜在语义分析模型的Web聚类%Web clustering based on hybrid probabilistic latent semantic analysis model

    Institute of Scientific and Technical Information of China (English)

    王治和; 王凌云; 党辉; 潘丽娜

    2012-01-01

    In E-commerce, in order to know more about the inherent characteristics of user access and make better marketing strategies, a Web clustering algorithm based on Hybrid Probabilistic Latent Semantic Analysis (H-PLSA) model was proposed in this paper. The Probabilistic Latent Semantic Analysis ( PLSA) models were established respectively on user browsing data, page information and enhanced user transaction data by using PLSA technology. Using log-likelihood function, three PLSA models were merged to get the user clustering H-PLSA model and the page clustering H-PLSA model. Similarity calculation was based on the conditional probability among latent themes and user, page as well as site in the clustering analysis. The k-medoids algorithm based on distance was adopted in this clustering algorithm. The H-PLSA model was designed and constructed in this article, and the Web clustering algorithm was verified on this H-PLSA model. Then it is proved that the algorithm is effective.%在电子商务应用中,为了更好地了解用户的内在特征,制定有效的营销策略,提出一种基于混合概率潜在语义分析(H-PLSA)模型的Web聚类算法.利用概率潜在语义分析-(PLSA)技术分别对用户浏览数据、页面内容信息及内容增强型用户事务数据建立PLSA模型,通过对数一似然函数对三个PLSA模型进行合并得到用户聚类的H-PLSA模型和页面聚类的H-PLSA模型.聚类分析中以潜在主题与用户、页面以及站点之间的条件概率作为相似度计算依据,聚类算法采用基于距离的k-medoids算法.设计并构建了H-PLSA模型,在该模型上对Web聚类算法进行验证,表明该算法是可行的.

  8. Measuring burnout and work engagement: Factor structure, invariance, and latent mean differences across Greece and the Netherlands

    Directory of Open Access Journals (Sweden)

    Xanthopoulou, D.

    2012-01-01

    Full Text Available This study examines the factor structure and invariance of the instruments measuring burnout (Maslach Burnout Inventory - General Survey / MBI-GS and work engagement (Utrecht Work Engagement Scale / UWES in a sample of Dutch (N = 162 and Greek (N = 206 employees. Confirmatory factor analyses in both samples supported the superiority of the proposed three-factor structure of both the MBI-GS (exhaustion, cynicism, and reduced professional efficacy and the UWES (vigor, dedication, and absorption. Alternative two-factor and one-factor models did not show a better fit to the data. In addition, results of multigroup analyses partly supported the invariance of the three-factor model of the MBI-GS, and fully supported the invariance of the three-factor model of the UWES across the two national samples. These results suggest that the MBI-GS and the UWES are not only valid instruments for testing burnout and engagement but also allow comparisons across countries.

  9. Estimation of test characteristics of real-time PCR and bacterial culture for diagnosis of subclinical intramammary infections with Streptococcus agalactiae in Danish dairy cattle in 2012 using latent class analysis

    DEFF Research Database (Denmark)

    Mahmmod, Yasser; Toft, Nils; Katholm, Jørgen

    2013-01-01

    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......The misdiagnosis of intramammary infections (IMI) with Streptococcus agalactiae (S. agalactiae) could lead farmers to treat or cull animals unnecessarily. The objective of this field study was to estimate the sensitivity (Se) and specificity (Sp) of real-time PCR at different cut-offs for cycle...... 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...

  10. Perceived consequences of female labor-force participation: a multilevel latent-class analysis across 22 countries (Consecuencias percibidas de la participación femenina en el mercado de trabajo: un análisis multinivel de clases latentes en 22 países

    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

  11. Functional networks underlying latent inhibition learning in the mouse brain

    OpenAIRE

    Puga, Frank; Barrett, Douglas W.; Bastida, Christel C.; Gonzalez-Lima, F.

    2007-01-01

    The present study reports the first comprehensive map of brain networks underlying latent inhibition learning and the first application of structural equation modeling to cytochrome oxidase data. In latent inhibition, repeated exposure to a stimulus results in a latent form of learning that inhibits subsequent associations with that stimulus. As neuronal energy demand to form learned associations changes, so does the induction of the respiratory enzyme cytochrome oxidase. Therefore, cytochrom...

  12. Insights from the computational analysis of CD271 glycation in mescenchymal stem cells in diabetes mellitus as a predisposition to latent tuberculosis

    OpenAIRE

    Bhattacharyya, Rajasri; Shukla, Misha; Nagra, Sachin; Banerjee, Dibyajyoti

    2013-01-01

    Diabetes mellitus is considered as a predisposition factor for active tuberculosis and is known to activate the latent form of tuberculosis. However, the causative association of latent tuberculosis with diabetes is not conclusively established. Therefore, it is of interest to relate their predisposition. We describe the glycation pattern of mescenchymal stem cell surface markers as CD271+/CD45-mescenchymal stem cell is known to be associated with latent tuberculosis. We show that the lysine ...

  13. Using Confirmatory Factor Analysis to Understand Executive Control in Preschool Children: I. Latent Structure

    Science.gov (United States)

    Wiebe, Sandra A.; Espy, Kimberly Andrews; Charak, David

    2008-01-01

    Although many tasks have been developed recently to study executive control in the preschool years, the constructs that underlie performance on these tasks are poorly understood. In particular, it is unclear whether executive control is composed of multiple, separable cognitive abilities (e.g., inhibition and working memory) or whether it is…

  14. Insights from the computational analysis of CD271 glycation in mescenchymal stem cells in diabetes mellitus as a predisposition to latent tuberculosis.

    Science.gov (United States)

    Bhattacharyya, Rajasri; Shukla, Misha; Nagra, Sachin; Banerjee, Dibyajyoti

    2013-01-01

    Diabetes mellitus is considered as a predisposition factor for active tuberculosis and is known to activate the latent form of tuberculosis. However, the causative association of latent tuberculosis with diabetes is not conclusively established. Therefore, it is of interest to relate their predisposition. We describe the glycation pattern of mescenchymal stem cell surface markers as CD271+/CD45-mescenchymal stem cell is known to be associated with latent tuberculosis. We show that the lysine residues important for function of CD271 death domain are predicted to be and glycated. These observations help to discuss the role of CD271 and glycation to modulate the genesis of latent tuberculosis in chronic diabetic mellitus.

  15. Bayesian Multitask Learning with Latent Hierarchies

    CERN Document Server

    Daumé, Hal

    2009-01-01

    We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share covariance structure. Our hierarchical model is seen to subsume several previously proposed multitask learning models and performs well on three distinct real-world data sets.

  16. Assessing the latent structure of DSM-5 PTSD among Chinese adolescents after the Ya'an earthquake.

    Science.gov (United States)

    Zhou, Xiao; Wu, Xinchun; Zhen, Rui

    2017-08-01

    To examine the underlying substructure of DSM-5 PTSD in an adolescent sample, this study used a confirmatory factor analysis alternative model approach to assess 813 adolescents two and a half years after the Ya'an earthquake. Participants completed the PTSD Checklist for DSM-5, the Center for Epidemiologic Studies Depression Scale for Children, and the Screen for Child Anxiety Related Emotional Disorders. The results found that the seven-factor hybrid PTSD model entailing intrusion, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal, and dysphoric arousal had significantly better fit indices than other alternative models. Depression and anxiety displayed high correlations with the seven-factor model. The findings suggested that the seven-factor model was more applicable to adolescents following the earthquake, and may carry important implications for further clinical practice and research on posttraumatic stress symptomatology. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  17. A comparison between latent variable models for evaluating the quality perceived from the hospital service users

    Directory of Open Access Journals (Sweden)

    Silvia Cagnone

    2007-10-01

    Full Text Available During the last years, costumer satisfaction analysis is becoming more and more important in evaluating the service quality of the sanitary system. Typically the construct ‘satisfaction’ is assumed to be a not observable variable, that is a latent variable. In this paper we illustrate and compare two different methods for analyzing latent variable models. The first one is the structural equation models with Lisrel, the second one is the generalized linear latent variable models. The comparison is performed through an application of the satisfaction analysis to a real data set referred to the patients of a hospital in Bologna. The results highlights the methodological and the applicative similarity and dissimilarity between the two methods.

  18. Evidence of a right-shift factor affecting infant hand-use preferences from 7 to 11 months of age as revealed by latent class analysis.

    Science.gov (United States)

    Michel, George F; Sheu, Ching-Fan; Brumley, Michele R

    2002-01-01

    Infant hand-use preferences for apprehending objects were assessed three times at 7, 9, and 11 months of age for 154 infants (79 males) using a reliable and valid procedure. Two classification procedures (differing in Type I classification error rates) were used to identify an infant's preference (right, left, no preference) at each age, and these data were examined using two- and three-group latent class analysis models. These analyses revealed the importance of using a handedness classification procedure with low Type I error rates and evidence of a right-shift factor similar to that expressed in child and adult handedness. Thus, infant hand-use preferences for apprehending objects are likely a developmental precursor of adult handedness. The relation of the right-shift factor to increased susceptibility to social influences during development and the evolution of human abilities also is discussed.

  19. Latent tuberculosis infection.

    Science.gov (United States)

    Nuermberger, Eric; Bishai, William R; Grosset, Jacques H

    2004-06-01

    Latent tuberculosis infection (LTBI) is a clinical condition characterized by a positive tuberculin skin test in the absence of clinical or radiological signs of active tuberculosis disease. It has been estimated that one third of the world's population is latently infected with Mycobacterium tuberculosis and serves as an enormous reservoir for future cases of active tuberculosis. The detection and treatment of individuals with LTBI and a high risk of progression to active tuberculosis are effective means to control the spread of tuberculosis. Furthermore, a better understanding of the host-pathogen interactions that result in latent infection could provide important insights for future drug or vaccine development. This chapter reviews recent developments in the molecular genetics, natural history, diagnosis, and treatment of LTBI within its historical context, including the impact of human immunodeficiency virus infection. Current treatment recommendations are also summarized.

  20. Potentiation of latent inhibition.

    Science.gov (United States)

    Rodriguez, Gabriel; Hall, Geoffrey

    2008-07-01

    Rats were given exposure either to an odor (almond) or a compound of odor plus taste (almond plus saline), prior to training in which the odor served as the conditioned stimulus. It was found, for both appetitive and aversive procedures, that conditioning was retarded by preexposure (a latent inhibition effect), and the extent of the retardation was greater in rats preexposed to the compound (i.e., latent inhibition to the odor was potentiated by the presence of the taste). In contrast, the presence of the taste during conditioning itself overshadowed learning about the odor. We argue that the presence of the salient taste in compound with the odor enhances the rate of associative learning, producing a rapid loss in the associability of the odor. This loss of associability will generate both overshadowing and the potentiation of latent inhibition that is observed after preexposure to the compound.