Differential item functioning magnitude and impact measures from item response theory models.

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Kleinman, Marjorie; Teresi, Jeanne A

2016-01-01

Measures of magnitude and impact of differential item functioning (DIF) at the item and scale level, respectively are presented and reviewed in this paper. Most measures are based on item response theory models. Magnitude refers to item level effect sizes, whereas impact refers to differences between groups at the scale score level. Reviewed are magnitude measures based on group differences in the expected item scores and impact measures based on differences in the expected scale scores. The similarities among these indices are demonstrated. Various software packages are described that provide magnitude and impact measures, and new software presented that computes all of the available statistics conveniently in one program with explanations of their relationships to one another.

A Bayesian Beta-Mixture Model for Nonparametric IRT (BBM-IRT)

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Arenson, Ethan A.; Karabatsos, George

2017-01-01

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

Few items in the thyroid-related quality of life instrument ThyPRO exhibited differential item functioning

DEFF Research Database (Denmark)

Watt, Torquil; Grønvold, Mogens; Hegedüs, Laszlo

2014-01-01

To evaluate the extent of differential item functioning (DIF) within the thyroid-specific quality of life patient-reported outcome measure, ThyPRO, according to sex, age, education and thyroid diagnosis.......To evaluate the extent of differential item functioning (DIF) within the thyroid-specific quality of life patient-reported outcome measure, ThyPRO, according to sex, age, education and thyroid diagnosis....

Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

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Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

2016-01-01

In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

A scale purification procedure for evaluation of differential item functioning

NARCIS (Netherlands)

Khalid, Muhammad Naveed; Glas, Cornelis A.W.

2014-01-01

Item bias or differential item functioning (DIF) has an important impact on the fairness of psychological and educational testing. In this paper, DIF is seen as a lack of fit to an item response (IRT) model. Inferences about the presence and importance of DIF require a process of so-called test

"Detecting Differential Item Functioning and Differential Step Functioning due to Differences that ""Should"" Matter"

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Tess Miller

2010-07-01

Full Text Available This study illustrates the use of differential item functioning (DIF and differential step functioning (DSF analyses to detect differences in item difficulty that are related to experiences of examinees, such as their teachers' instructional practices, that are relevant to the knowledge, skill, or ability the test is intended to measure. This analysis is in contrast to the typical use of DIF or DSF to detect differences related to characteristics of examinees, such as gender, language, or cultural knowledge, that should be irrelevant. Using data from two forms of Ontario's Grade 9 Assessment of Mathematics, analyses were performed comparing groups of students defined by their teachers' instructional practices. All constructed-response items were tested for DIF using the Mantel Chi-Square, standardized Liu Agresti cumulative common log-odds ratio, and standardized Cox's noncentrality parameter. Items exhibiting moderate to large DIF were subsequently tested for DSF. In contrast to typical DIF or DSF analyses, which inform item development, these analyses have the potential to inform instructional practice.

Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.

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García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G

2017-08-01

The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.

Detection of differential item functioning using Lagrange multiplier tests

NARCIS (Netherlands)

Glas, Cornelis A.W.

1996-01-01

In this paper it is shown that differential item functioning can be evaluated using the Lagrange multiplier test or C. R. Rao's efficient score test. The test is presented in the framework of a number of item response theory (IRT) models such as the Rasch model, the one-parameter logistic model, the

Language-related differential item functioning between English and German PROMIS Depression items is negligible.

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Fischer, H Felix; Wahl, Inka; Nolte, Sandra; Liegl, Gregor; Brähler, Elmar; Löwe, Bernd; Rose, Matthias

2017-12-01

To investigate differential item functioning (DIF) of PROMIS Depression items between US and German samples we compared data from the US PROMIS calibration sample (n = 780), a German general population survey (n = 2,500) and a German clinical sample (n = 621). DIF was assessed in an ordinal logistic regression framework, with 0.02 as criterion for R 2 -change and 0.096 for Raju's non-compensatory DIF. Item parameters were initially fixed to the PROMIS Depression metric; we used plausible values to account for uncertainty in depression estimates. Only four items showed DIF. Accounting for DIF led to negligible effects for the full item bank as well as a post hoc simulated computer-adaptive test (German general population sample was considerably lower compared to the US reference value of 50. Overall, we found little evidence for language DIF between US and German samples, which could be addressed by either replacing the DIF items by items not showing DIF or by scoring the short form in German samples with the corrected item parameters reported. Copyright © 2016 John Wiley & Sons, Ltd.

Detection of Uniform and Nonuniform Differential Item Functioning by Item-Focused Trees

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Berger, Moritz; Tutz, Gerhard

2016-01-01

Detection of differential item functioning (DIF) by use of the logistic modeling approach has a long tradition. One big advantage of the approach is that it can be used to investigate nonuniform (NUDIF) as well as uniform DIF (UDIF). The classical approach allows one to detect DIF by distinguishing between multiple groups. We propose an…

Do people with and without medical conditions respond similarly to the short health anxiety inventory? An assessment of differential item functioning using item response theory.

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LeBouthillier, Daniel M; Thibodeau, Michel A; Alberts, Nicole M; Hadjistavropoulos, Heather D; Asmundson, Gordon J G

2015-04-01

Individuals with medical conditions are likely to have elevated health anxiety; however, research has not demonstrated how medical status impacts response patterns on health anxiety measures. Measurement bias can undermine the validity of a questionnaire by overestimating or underestimating scores in groups of individuals. We investigated whether the Short Health Anxiety Inventory (SHAI), a widely-used measure of health anxiety, exhibits medical condition-based bias on item and subscale levels, and whether the SHAI subscales adequately assess the health anxiety continuum. Data were from 963 individuals with diabetes, breast cancer, or multiple sclerosis, and 372 healthy individuals. Mantel-Haenszel tests and item characteristic curves were used to classify the severity of item-level differential item functioning in all three medical groups compared to the healthy group. Test characteristic curves were used to assess scale-level differential item functioning and whether the SHAI subscales adequately assess the health anxiety continuum. Nine out of 14 items exhibited differential item functioning. Two items exhibited differential item functioning in all medical groups compared to the healthy group. In both Thought Intrusion and Fear of Illness subscales, differential item functioning was associated with mildly deflated scores in medical groups with very high levels of the latent traits. Fear of Illness items poorly discriminated between individuals with low and very low levels of the latent trait. While individuals with medical conditions may respond differentially to some items, clinicians and researchers can confidently use the SHAI with a variety of medical populations without concern of significant bias. Copyright © 2015 Elsevier Inc. All rights reserved.

Mixture Item Response Theory-MIMIC Model: Simultaneous Estimation of Differential Item Functioning for Manifest Groups and Latent Classes

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Bilir, Mustafa Kuzey

2009-01-01

This study uses a new psychometric model (mixture item response theory-MIMIC model) that simultaneously estimates differential item functioning (DIF) across manifest groups and latent classes. Current DIF detection methods investigate DIF from only one side, either across manifest groups (e.g., gender, ethnicity, etc.), or across latent classes…

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory.

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Yau, David T W; Wong, May C M; Lam, K F; McGrath, Colman

2015-08-19

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ11-14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ11-14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions. A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions. Both CPQ11-14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item "Concerned with what other people think" demonstrated a uniform DIF (p Items related to oral symptoms were not informative to OHRQoL and deletion of these items is suggested. The impact of DIF across gender on the overall score was minimal. CPQ11-14 RSF:8 performed slightly better than ISF:8 in measurement precision. The 6-item short forms

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

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Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

Differential item functioning of the UWES-17 in South Africa

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Leanne Goliath-Yarde

2011-11-01

Research purpose: This study assesses the Differential Item Functioning (DIF of the Utrecht Work Engagement Scale (UWES-17 for different South African cultural groups in a South African company. Motivation for the study: Organisations are using the UWES-17 more and more in South Africa to assess work engagement. Therefore, research evidence from psychologists or assessment practitioners on its DIF across different cultural groups is necessary. Research design, approach and method: The researchers conducted a Secondary Data Analysis (SDA on the UWES-17 sample (n = 2429 that they obtained from a cross-sectional survey undertaken in a South African Information and Communication Technology (ICT sector company (n = 24 134. Quantitative item data on the UWES-17 scale enabled the authors to address the research question. Main findings: The researchers found uniform and/or non-uniform DIF on five of the vigour items, four of the dedication items and two of the absorption items. This also showed possible Differential Test Functioning (DTF on the vigour and dedication dimensions. Practical/managerial implications: Based on the DIF, the researchers suggested that organisations should not use the UWES-17 comparatively for different cultural groups or employment decisions in South Africa. Contribution/value add: The study provides evidence on DIF and possible DTF for the UWES-17. However, it also raises questions about possible interaction effects that need further investigation.

Polytomous latent scales for the investigation of the ordering of items

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Ligtvoet, R.; van der Ark, L.A.; Bergsma, W. P.; Sijtsma, K.

2011-01-01

We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering

Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers.

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Stochl, Jan; Jones, Peter B; Croudace, Tim J

2012-06-11

Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12)--when binary scored--were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech's "well-being" and "distress" clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental

Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers

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Stochl Jan

2012-06-01

Full Text Available Abstract Background Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Methods Scalability of data from 1 a cross-sectional health survey (the Scottish Health Education Population Survey and 2 a general population birth cohort study (the National Child Development Study illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. Results and conclusions After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items we show that all items from the 12-item General Health Questionnaire (GHQ-12 – when binary scored – were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech’s “well-being” and “distress” clinical scales. An illustration of ordinal item analysis

Item response theory analysis of the life orientation test-revised: age and gender differential item functioning analyses.

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Steca, Patrizia; Monzani, Dario; Greco, Andrea; Chiesi, Francesca; Primi, Caterina

2015-06-01

This study is aimed at testing the measurement properties of the Life Orientation Test-Revised (LOT-R) for the assessment of dispositional optimism by employing item response theory (IRT) analyses. The LOT-R was administered to a large sample of 2,862 Italian adults. First, confirmatory factor analyses demonstrated the theoretical conceptualization of the construct measured by the LOT-R as a single bipolar dimension. Subsequently, IRT analyses for polytomous, ordered response category data were applied to investigate the items' properties. The equivalence of the items across gender and age was assessed by analyzing differential item functioning. Discrimination and severity parameters indicated that all items were able to distinguish people with different levels of optimism and adequately covered the spectrum of the latent trait. Additionally, the LOT-R appears to be gender invariant and, with minor exceptions, age invariant. Results provided evidence that the LOT-R is a reliable and valid measure of dispositional optimism. © The Author(s) 2014.

Effect Size Measures for Differential Item Functioning in a Multidimensional IRT Model

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Suh, Youngsuk

2016-01-01

This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P-difference and unsigned weighted P-difference. The performance of…

Differential item functioning of the patient-reported outcomes information system (PROMIS®) pain interference item bank by language (Spanish versus English).

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Paz, Sylvia H; Spritzer, Karen L; Reise, Steven P; Hays, Ron D

2017-06-01

About 70% of Latinos, 5 years old or older, in the United States speak Spanish at home. Measurement equivalence of the PROMIS ® pain interference (PI) item bank by language of administration (English versus Spanish) has not been evaluated. A sample of 527 adult Spanish-speaking Latinos completed the Spanish version of the 41-item PROMIS ® pain interference item bank. We evaluate dimensionality, monotonicity and local independence of the Spanish-language items. Then we evaluate differential item functioning (DIF) using ordinal logistic regression with item response theory scores estimated from DIF-free "anchor" items. One of the 41 items in the Spanish version of the PROMIS ® PI item bank was identified as having significant uniform DIF. English- and Spanish-speaking subjects with the same level of pain interference responded differently to 1 of the 41 items in the PROMIS ® PI item bank. This item was not retained due to proprietary issues. The original English language item parameters can be used when estimating PROMIS ® PI scores.

Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

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Woods, Carol M.; Grimm, Kevin J.

2011-01-01

In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

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Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

2015-07-01

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Nonparametric statistical inference

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Gibbons, Jean Dickinson

2010-01-01

Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente

Geriatric Anxiety Scale: item response theory analysis, differential item functioning, and creation of a ten-item short form (GAS-10).

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Mueller, Anne E; Segal, Daniel L; Gavett, Brandon; Marty, Meghan A; Yochim, Brian; June, Andrea; Coolidge, Frederick L

2015-07-01

The Geriatric Anxiety Scale (GAS; Segal et al. (Segal, D. L., June, A., Payne, M., Coolidge, F. L. and Yochim, B. (2010). Journal of Anxiety Disorders, 24, 709-714. doi:10.1016/j.janxdis.2010.05.002) is a self-report measure of anxiety that was designed to address unique issues associated with anxiety assessment in older adults. This study is the first to use item response theory (IRT) to examine the psychometric properties of a measure of anxiety in older adults. A large sample of older adults (n = 581; mean age = 72.32 years, SD = 7.64 years, range = 60 to 96 years; 64% women; 88% European American) completed the GAS. IRT properties were examined. The presence of differential item functioning (DIF) or measurement bias by age and sex was assessed, and a ten-item short form of the GAS (called the GAS-10) was created. All GAS items had discrimination parameters of 1.07 or greater. Items from the somatic subscale tended to have lower discrimination parameters than items on the cognitive or affective subscales. Two items were flagged for DIF, but the impact of the DIF was negligible. Women scored significantly higher than men on the GAS and its subscales. Participants in the young-old group (60 to 79 years old) scored significantly higher on the cognitive subscale than participants in the old-old group (80 years old and older). Results from the IRT analyses indicated that the GAS and GAS-10 have strong psychometric properties among older adults. We conclude by discussing implications and future research directions.

Statistical and extra-statistical considerations in differential item functioning analyses

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G. K. Huysamen

2004-10-01

Full Text Available This article briefly describes the main procedures for performing differential item functioning (DIF analyses and points out some of the statistical and extra-statistical implications of these methods. Research findings on the sources of DIF, including those associated with translated tests, are reviewed. As DIF analyses are oblivious of correlations between a test and relevant criteria, the elimination of differentially functioning items does not necessarily improve predictive validity or reduce any predictive bias. The implications of the results of past DIF research for test development in the multilingual and multi-cultural South African society are considered. Opsomming Hierdie artikel beskryf kortliks die hoofprosedures vir die ontleding van differensiële itemfunksionering (DIF en verwys na sommige van die statistiese en buite-statistiese implikasies van hierdie metodes. ’n Oorsig word verskaf van navorsingsbevindings oor die bronne van DIF, insluitend dié by vertaalde toetse. Omdat DIF-ontledings nie die korrelasies tussen ’n toets en relevante kriteria in ag neem nie, sal die verwydering van differensieel-funksionerende items nie noodwendig voorspellingsgeldigheid verbeter of voorspellingsydigheid verminder nie. Die implikasies van vorige DIF-navorsingsbevindings vir toetsontwikkeling in die veeltalige en multikulturele Suid-Afrikaanse gemeenskap word oorweeg.

A more general model for testing measurement invariance and differential item functioning.

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Bauer, Daniel J

2017-09-01

The evaluation of measurement invariance is an important step in establishing the validity and comparability of measurements across individuals. Most commonly, measurement invariance has been examined using 1 of 2 primary latent variable modeling approaches: the multiple groups model or the multiple-indicator multiple-cause (MIMIC) model. Both approaches offer opportunities to detect differential item functioning within multi-item scales, and thereby to test measurement invariance, but both approaches also have significant limitations. The multiple groups model allows 1 to examine the invariance of all model parameters but only across levels of a single categorical individual difference variable (e.g., ethnicity). In contrast, the MIMIC model permits both categorical and continuous individual difference variables (e.g., sex and age) but permits only a subset of the model parameters to vary as a function of these characteristics. The current article argues that moderated nonlinear factor analysis (MNLFA) constitutes an alternative, more flexible model for evaluating measurement invariance and differential item functioning. We show that the MNLFA subsumes and combines the strengths of the multiple group and MIMIC models, allowing for a full and simultaneous assessment of measurement invariance and differential item functioning across multiple categorical and/or continuous individual difference variables. The relationships between the MNLFA model and the multiple groups and MIMIC models are shown mathematically and via an empirical demonstration. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Detection of differential item functioning using Lagrange multiplier tests

NARCIS (Netherlands)

Glas, Cornelis A.W.

1998-01-01

Abstract: In the present paper it is shown that differential item functioning can be evaluated using the Lagrange multiplier test or Rao’s efficient score test. The test is presented in the framework of a number of IRT models such as the Rasch model, the OPLM, the 2-parameter logistic model, the

Examining the Psychometric Quality of Multiple-Choice Assessment Items using Mokken Scale Analysis.

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Wind, Stefanie A

The concept of invariant measurement is typically associated with Rasch measurement theory (Engelhard, 2013). Concerned with the appropriateness of the parametric transformation upon which the Rasch model is based, Mokken (1971) proposed a nonparametric procedure for evaluating the quality of social science measurement that is theoretically and empirically related to the Rasch model. Mokken's nonparametric procedure can be used to evaluate the quality of dichotomous and polytomous items in terms of the requirements for invariant measurement. Despite these potential benefits, the use of Mokken scaling to examine the properties of multiple-choice (MC) items in education has not yet been fully explored. A nonparametric approach to evaluating MC items is promising in that this approach facilitates the evaluation of assessments in terms of invariant measurement without imposing potentially inappropriate transformations. Using Rasch-based indices of measurement quality as a frame of reference, data from an eighth-grade physical science assessment are used to illustrate and explore Mokken-based techniques for evaluating the quality of MC items. Implications for research and practice are discussed.

Differential Item Functioning Analysis of the Mental, Emotional, and Bodily Toughness Inventory

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Gao, Yong; Mack, Mick G.; Ragan, Moira A.; Ragan, Brian

2012-01-01

In this study the authors used differential item functioning analysis to examine if there were items in the Mental, Emotional, and Bodily Toughness Inventory functioning differently across gender and athletic membership. A total of 444 male (56.3%) and female (43.7%) participants (30.9% athletes and 69.1% non-athletes) responded to the Mental,…

Does Gender-Specific Differential Item Functioning Affect the Structure in Vocational Interest Inventories?

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Beinicke, Andrea; Pässler, Katja; Hell, Benedikt

2014-01-01

The study investigates consequences of eliminating items showing gender-specific differential item functioning (DIF) on the psychometric structure of a standard RIASEC interest inventory. Holland's hexagonal model was tested for structural invariance using a confirmatory methodological approach (confirmatory factor analysis and randomization…

Few items in the thyroid-related quality of life instrument ThyPRO exhibited differential item functioning.

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Watt, Torquil; Groenvold, Mogens; Hegedüs, Laszlo; Bonnema, Steen Joop; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla; Bjorner, Jakob Bue

2014-02-01

To evaluate the extent of differential item functioning (DIF) within the thyroid-specific quality of life patient-reported outcome measure, ThyPRO, according to sex, age, education and thyroid diagnosis. A total of 838 patients with benign thyroid diseases completed the ThyPRO questionnaire (84 five-point items, 13 scales). Uniform and nonuniform DIF were investigated using ordinal logistic regression, testing for both statistical significance and magnitude (∆R(2) > 0.02). Scale level was estimated by the sum score, after purification. Twenty instances of DIF in 17 of the 84 items were found. Eight according to diagnosis, where the goiter scale was the one most affected, possibly due to differing perceptions in patients with auto-immune thyroid diseases compared to patients with simple goiter. Eight DIFs according to age were found, of which 5 were in positively worded items, which younger patients were more likely to endorse; one according to gender: women were more likely to report crying, and three according to educational level. The vast majority of DIF had only minor influence on the scale scores (0.1-2.3 points on the 0-100 scales), but two DIF corresponded to a difference of 4.6 and 9.8, respectively. Ordinal logistic regression identified DIF in 17 of 84 items. The potential impact of this on the present scales was low, but items displaying DIF could be avoided when developing abbreviated scales, where the potential impact of DIF (due to fewer items) will be larger.

Assessing Differential Item Functioning on the Test of Relational Reasoning

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Denis Dumas

2018-03-01

Full Text Available The test of relational reasoning (TORR is designed to assess the ability to identify complex patterns within visuospatial stimuli. The TORR is designed for use in school and university settings, and therefore, its measurement invariance across diverse groups is critical. In this investigation, a large sample, representative of a major university on key demographic variables, was collected, and the resulting data were analyzed using a multi-group, multidimensional item-response theory model-comparison procedure. No significant differential item functioning was found on any of the TORR items across any of the demographic groups of interest. This finding is interpreted as evidence of the cultural fairness of the TORR, and potential test-development choices that may have contributed to that cultural fairness are discussed.

Differential Weighting of Items to Improve University Admission Test Validity

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Eduardo Backhoff Escudero

2001-05-01

Full Text Available This paper gives an evaluation of different ways to increase university admission test criterion-related validity, by differentially weighting test items. We compared four methods of weighting multiple-choice items of the Basic Skills and Knowledge Examination (EXHCOBA: (1 punishing incorrect responses by a constant factor, (2 weighting incorrect responses, considering the levels of error, (3 weighting correct responses, considering the item’s difficulty, based on the Classic Measurement Theory, and (4 weighting correct responses, considering the item’s difficulty, based on the Item Response Theory. Results show that none of these methods increased the instrument’s predictive validity, although they did improve its concurrent validity. It was concluded that it is appropriate to score the test by simply adding up correct responses.

Parametric and Non-Parametric System Modelling

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg

1999-01-01

the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...

On the use of permutation in and the performance of a class of nonparametric methods to detect differential gene expression.

Science.gov (United States)

Pan, Wei

2003-07-22

Recently a class of nonparametric statistical methods, including the empirical Bayes (EB) method, the significance analysis of microarray (SAM) method and the mixture model method (MMM), have been proposed to detect differential gene expression for replicated microarray experiments conducted under two conditions. All the methods depend on constructing a test statistic Z and a so-called null statistic z. The null statistic z is used to provide some reference distribution for Z such that statistical inference can be accomplished. A common way of constructing z is to apply Z to randomly permuted data. Here we point our that the distribution of z may not approximate the null distribution of Z well, leading to possibly too conservative inference. This observation may apply to other permutation-based nonparametric methods. We propose a new method of constructing a null statistic that aims to estimate the null distribution of a test statistic directly. Using simulated data and real data, we assess and compare the performance of the existing method and our new method when applied in EB, SAM and MMM. Some interesting findings on operating characteristics of EB, SAM and MMM are also reported. Finally, by combining the idea of SAM and MMM, we outline a simple nonparametric method based on the direct use of a test statistic and a null statistic.

Examples of the Application of Nonparametric Information Geometry to Statistical Physics

Directory of Open Access Journals (Sweden)

Giovanni Pistone

2013-09-01

Full Text Available We review a nonparametric version of Amari’s information geometry in which the set of positive probability densities on a given sample space is endowed with an atlas of charts to form a differentiable manifold modeled on Orlicz Banach spaces. This nonparametric setting is used to discuss the setting of typical problems in machine learning and statistical physics, such as black-box optimization, Kullback-Leibler divergence, Boltzmann-Gibbs entropy and the Boltzmann equation.

Item analysis of ADAS-Cog: effect of baseline cognitive impairment in a clinical AD trial.

Science.gov (United States)

Sevigny, Jeffrey J; Peng, Yahong; Liu, Lian; Lines, Christopher R

2010-03-01

We explored the association of Alzheimer's disease (AD) Assessment Scale (ADAS-Cog) item scores with AD severity using cross-sectional and longitudinal data from the same study. Post hoc analyses were performed using placebo data from a 12-month trial of patients with mild-to-moderate AD (N =281 randomized, N =209 completed). Baseline distributions of ADAS-Cog item scores by Mini-Mental State Examination (MMSE) score and Clinical Dementia Rating (CDR) sum of boxes score (measures of dementia severity) were estimated using local and nonparametric regressions. Mixed-effect models were used to characterize ADAS-Cog item score changes over time by dementia severity (MMSE: mild =21-26, moderate =14-20; global CDR: mild =0.5-1, moderate =2). In the cross-sectional analysis of baseline ADAS-Cog item scores, orientation was the most sensitive item to differentiate patients across levels of cognitive impairment. Several items showed a ceiling effect, particularly in milder AD. In the longitudinal analysis of change scores over 12 months, orientation was the only item with noticeable decline (8%-10%) in mild AD. Most items showed modest declines (5%-20%) in moderate AD.

Use of differential item functioning analysis to assess the equivalence of translations of a questionnaire

NARCIS (Netherlands)

Petersen, Morten Aa; Groenvold, Mogens; Bjorner, Jakob B.; Aaronson, Neil; Conroy, Thierry; Cull, Ann; Fayers, Peter; Hjermstad, Marianne; Sprangers, Mirjam; Sullivan, Marianne

2003-01-01

In cross-national comparisons based on questionnaires, accurate translations are necessary to obtain valid results. Differential item functioning (DIF) analysis can be used to test whether translations of items in multi-item scales are equivalent to the original. In data from 10,815 respondents

A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.

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Zhang, Qingyang

2018-05-16

Differential co-expression analysis, as a complement of differential expression analysis, offers significant insights into the changes in molecular mechanism of different phenotypes. A prevailing approach to detecting differentially co-expressed genes is to compare Pearson's correlation coefficients in two phenotypes. However, due to the limitations of Pearson's correlation measure, this approach lacks the power to detect nonlinear changes in gene co-expression which is common in gene regulatory networks. In this work, a new nonparametric procedure is proposed to search differentially co-expressed gene pairs in different phenotypes from large-scale data. Our computational pipeline consisted of two main steps, a screening step and a testing step. The screening step is to reduce the search space by filtering out all the independent gene pairs using distance correlation measure. In the testing step, we compare the gene co-expression patterns in different phenotypes by a recently developed edge-count test. Both steps are distribution-free and targeting nonlinear relations. We illustrate the promise of the new approach by analyzing the Cancer Genome Atlas data and the METABRIC data for breast cancer subtypes. Compared with some existing methods, the new method is more powerful in detecting nonlinear type of differential co-expressions. The distance correlation screening can greatly improve computational efficiency, facilitating its application to large data sets.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

Science.gov (United States)

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Effects of Differential Item Functioning on Examinees' Test Performance and Reliability of Test

Science.gov (United States)

Lee, Yi-Hsuan; Zhang, Jinming

2017-01-01

Simulations were conducted to examine the effect of differential item functioning (DIF) on measurement consequences such as total scores, item response theory (IRT) ability estimates, and test reliability in terms of the ratio of true-score variance to observed-score variance and the standard error of estimation for the IRT ability parameter. The…

Assessment of Differential Item Functioning in the Experiences of Discrimination Index

Science.gov (United States)

Cunningham, Timothy J.; Berkman, Lisa F.; Gortmaker, Steven L.; Kiefe, Catarina I.; Jacobs, David R.; Seeman, Teresa E.; Kawachi, Ichiro

2011-01-01

The psychometric properties of instruments used to measure self-reported experiences of discrimination in epidemiologic studies are rarely assessed, especially regarding construct validity. The authors used 2000–2001 data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study to examine differential item functioning (DIF) in 2 versions of the Experiences of Discrimination (EOD) Index, an index measuring self-reported experiences of racial/ethnic and gender discrimination. DIF may confound interpretation of subgroup differences. Large DIF was observed for 2 of 7 racial/ethnic discrimination items: White participants reported more racial/ethnic discrimination for the “at school” item, and black participants reported more racial/ethnic discrimination for the “getting housing” item. The large DIF by race/ethnicity in the index for racial/ethnic discrimination probably reflects item impact and is the result of valid group differences between blacks and whites regarding their respective experiences of discrimination. The authors also observed large DIF by race/ethnicity for 3 of 7 gender discrimination items. This is more likely to have been due to item bias. Users of the EOD Index must consider the advantages and disadvantages of DIF adjustment (omitting items, constructing separate measures, and retaining items). The EOD Index has substantial usefulness as an instrument that can assess self-reported experiences of discrimination. PMID:22038104

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

Science.gov (United States)

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

A Monte Carlo Study of the Effect of Item Characteristic Curve Estimation on the Accuracy of Three Person-Fit Statistics

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St-Onge, Christina; Valois, Pierre; Abdous, Belkacem; Germain, Stephane

2009-01-01

To date, there have been no studies comparing parametric and nonparametric Item Characteristic Curve (ICC) estimation methods on the effectiveness of Person-Fit Statistics (PFS). The primary aim of this study was to determine if the use of ICCs estimated by nonparametric methods would increase the accuracy of item response theory-based PFS for…

Use of multilevel logistic regression to identify the causes of differential item functioning.

Science.gov (United States)

Balluerka, Nekane; Gorostiaga, Arantxa; Gómez-Benito, Juana; Hidalgo, María Dolores

2010-11-01

Given that a key function of tests is to serve as evaluation instruments and for decision making in the fields of psychology and education, the possibility that some of their items may show differential behaviour is a major concern for psychometricians. In recent decades, important progress has been made as regards the efficacy of techniques designed to detect this differential item functioning (DIF). However, the findings are scant when it comes to explaining its causes. The present study addresses this problem from the perspective of multilevel analysis. Starting from a case study in the area of transcultural comparisons, multilevel logistic regression is used: 1) to identify the item characteristics associated with the presence of DIF; 2) to estimate the proportion of variation in the DIF coefficients that is explained by these characteristics; and 3) to evaluate alternative explanations of the DIF by comparing the explanatory power or fit of different sequential models. The comparison of these models confirmed one of the two alternatives (familiarity with the stimulus) and rejected the other (the topic area) as being a cause of differential functioning with respect to the compared groups.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

Science.gov (United States)

Drabinová, Adéla; Martinková, Patrícia

2017-01-01

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

Differential item functioning analysis of the Vanderbilt Expertise Test for cars.

Science.gov (United States)

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge.

Validation and psychometric properties of the Somatic and Psychological HEalth REport (SPHERE) in a young Australian-based population sample using non-parametric item response theory.

Science.gov (United States)

Couvy-Duchesne, Baptiste; Davenport, Tracey A; Martin, Nicholas G; Wright, Margaret J; Hickie, Ian B

2017-08-01

The Somatic and Psychological HEalth REport (SPHERE) is a 34-item self-report questionnaire that assesses symptoms of mental distress and persistent fatigue. As it was developed as a screening instrument for use mainly in primary care-based clinical settings, its validity and psychometric properties have not been studied extensively in population-based samples. We used non-parametric Item Response Theory to assess scale validity and item properties of the SPHERE-34 scales, collected through four waves of the Brisbane Longitudinal Twin Study (N = 1707, mean age = 12, 51% females; N = 1273, mean age = 14, 50% females; N = 1513, mean age = 16, 54% females, N = 1263, mean age = 18, 56% females). We estimated the heritability of the new scores, their genetic correlation, and their predictive ability in a sub-sample (N = 1993) who completed the Composite International Diagnostic Interview. After excluding items most responsible for noise, sex or wave bias, the SPHERE-34 questionnaire was reduced to 21 items (SPHERE-21), comprising a 14-item scale for anxiety-depression and a 10-item scale for chronic fatigue (3 items overlapping). These new scores showed high internal consistency (alpha > 0.78), moderate three months reliability (ICC = 0.47-0.58) and item scalability (Hi > 0.23), and were positively correlated (phenotypic correlations r = 0.57-0.70; rG = 0.77-1.00). Heritability estimates ranged from 0.27 to 0.51. In addition, both scores were associated with later DSM-IV diagnoses of MDD, social anxiety and alcohol dependence (OR in 1.23-1.47). Finally, a post-hoc comparison showed that several psychometric properties of the SPHERE-21 were similar to those of the Beck Depression Inventory. The scales of SPHERE-21 measure valid and comparable constructs across sex and age groups (from 9 to 28 years). SPHERE-21 scores are heritable, genetically correlated and show good predictive ability of mental health in an Australian-based population

Identifying Country-Specific Cultures of Physics Education: A differential item functioning approach

Science.gov (United States)

Mesic, Vanes

2012-11-01

In international large-scale assessments of educational outcomes, student achievement is often represented by unidimensional constructs. This approach allows for drawing general conclusions about country rankings with respect to the given achievement measure, but it typically does not provide specific diagnostic information which is necessary for systematic comparisons and improvements of educational systems. Useful information could be obtained by exploring the differences in national profiles of student achievement between low-achieving and high-achieving countries. In this study, we aimed to identify the relative weaknesses and strengths of eighth graders' physics achievement in Bosnia and Herzegovina in comparison to the achievement of their peers from Slovenia. For this purpose, we ran a secondary analysis of Trends in International Mathematics and Science Study (TIMSS) 2007 data. The student sample consisted of 4,220 students from Bosnia and Herzegovina and 4,043 students from Slovenia. After analysing the cognitive demands of TIMSS 2007 physics items, the correspondent differential item functioning (DIF)/differential group functioning contrasts were estimated. Approximately 40% of items exhibited large DIF contrasts, indicating significant differences between cultures of physics education in Bosnia and Herzegovina and Slovenia. The relative strength of students from Bosnia and Herzegovina showed to be mainly associated with the topic area 'Electricity and magnetism'. Classes of items which required the knowledge of experimental method, counterintuitive thinking, proportional reasoning and/or the use of complex knowledge structures proved to be differentially easier for students from Slovenia. In the light of the presented results, the common practice of ranking countries with respect to universally established cognitive categories seems to be potentially misleading.

Development of a short form Social Interaction Anxiety (SIAS) and Social Phobia Scale (SPS) using nonparametric item response theory: the SIAS-6 and the SPS-6.

Science.gov (United States)

Peters, Lorna; Sunderland, Matthew; Andrews, Gavin; Rapee, Ronald M; Mattick, Richard P

2012-03-01

Shortened forms of the Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS) were developed using nonparametric item response theory methods. Using data from socially phobic participants enrolled in 5 treatment trials (N = 456), 2 six-item scales (the SIAS-6 and the SPS-6) were developed. The validity of the scores on the SIAS-6 and the SPS-6 was then tested using traditional methods for their convergent validity in an independent clinical sample and a student sample, as well as for their sensitivity to change and diagnostic sensitivity in the clinical sample. The scores on the SIAS-6 and the SPS-6 correlated as well as the scores on the original SIAS and SPS, with scores on measures of related constructs, discriminated well between those with and without a diagnosis of social phobia, providing cutoffs for diagnosis and were as sensitive to measuring change associated with treatment as were the SIAS and SPS. Together, the SIAS-6 and the SPS-6 appear to be an efficient method of measuring symptoms of social phobia and provide a brief screening tool.

The linear transformation model with frailties for the analysis of item response times.

Science.gov (United States)

Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey A

2013-02-01

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested. © 2012 The British Psychological Society.

Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

DEFF Research Database (Denmark)

Scott, Neil W.; Fayers, Peter M.; Aaronson, Neil K.

2010-01-01

Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise...

Non-parametric smoothing of experimental data

International Nuclear Information System (INIS)

Kuketayev, A.T.; Pen'kov, F.M.

2007-01-01

Full text: Rapid processing of experimental data samples in nuclear physics often requires differentiation in order to find extrema. Therefore, even at the preliminary stage of data analysis, a range of noise reduction methods are used to smooth experimental data. There are many non-parametric smoothing techniques: interval averages, moving averages, exponential smoothing, etc. Nevertheless, it is more common to use a priori information about the behavior of the experimental curve in order to construct smoothing schemes based on the least squares techniques. The latter methodology's advantage is that the area under the curve can be preserved, which is equivalent to conservation of total speed of counting. The disadvantages of this approach include the lack of a priori information. For example, very often the sums of undifferentiated (by a detector) peaks are replaced with one peak during the processing of data, introducing uncontrolled errors in the determination of the physical quantities. The problem is solvable only by having experienced personnel, whose skills are much greater than the challenge. We propose a set of non-parametric techniques, which allows the use of any additional information on the nature of experimental dependence. The method is based on a construction of a functional, which includes both experimental data and a priori information. Minimum of this functional is reached on a non-parametric smoothed curve. Euler (Lagrange) differential equations are constructed for these curves; then their solutions are obtained analytically or numerically. The proposed approach allows for automated processing of nuclear physics data, eliminating the need for highly skilled laboratory personnel. Pursuant to the proposed approach is the possibility to obtain smoothing curves in a given confidence interval, e.g. according to the χ 2 distribution. This approach is applicable when constructing smooth solutions of ill-posed problems, in particular when solving

The MIMIC Method with Scale Purification for Detecting Differential Item Functioning

Science.gov (United States)

Wang, Wen-Chung; Shih, Ching-Lin; Yang, Chih-Chien

2009-01-01

This study implements a scale purification procedure onto the standard MIMIC method for differential item functioning (DIF) detection and assesses its performance through a series of simulations. It is found that the MIMIC method with scale purification (denoted as M-SP) outperforms the standard MIMIC method (denoted as M-ST) in controlling…

The practical impact of differential item functioning analyses in a health-related quality of life instrument

DEFF Research Database (Denmark)

Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

2009-01-01

Differential item functioning (DIF) analyses are commonly used to evaluate health-related quality of life (HRQoL) instruments. There is, however, a lack of consensus as to how to assess the practical impact of statistically significant DIF results.......Differential item functioning (DIF) analyses are commonly used to evaluate health-related quality of life (HRQoL) instruments. There is, however, a lack of consensus as to how to assess the practical impact of statistically significant DIF results....

Why Consumers Misattribute Sponsorships to Non-Sponsor Brands: Differential Roles of Item and Relational Communications.

Science.gov (United States)

Weeks, Clinton S; Humphreys, Michael S; Cornwell, T Bettina

2018-02-01

Brands engaged in sponsorship of events commonly have objectives that depend on consumer memory for the sponsor-event relationship (e.g., sponsorship awareness). Consumers however, often misattribute sponsorships to nonsponsor competitor brands, indicating erroneous memory for these relationships. The current research uses an item and relational memory framework to reveal sponsor brands may inadvertently foster this misattribution when they communicate relational linkages to events. Effects can be explained via differential roles of communicating item information (information that supports processing item distinctiveness) versus relational information (information that supports processing relationships among items) in contributing to memory outcomes. Experiment 1 uses event-cued brand recall to show that correct memory retrieval is best supported by communicating relational information when sponsorship relationships are not obvious (low congruence). In contrast, correct retrieval is best supported by communicating item information when relationships are obvious (high congruence). Experiment 2 uses brand-cued event recall to show that, against conventional marketing recommendations, relational information increases misattribution, whereas item information guards against misattribution. Results suggest sponsor brands must distinguish between item and relational communications to enhance correct retrieval and limit misattribution. Methodologically, the work shows that choice of cueing direction is critical in differentially revealing patterns of correct and incorrect retrieval with pair relationships. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Overcoming the effects of differential skewness of test items in scale construction

Directory of Open Access Journals (Sweden)

Johann M. Schepers

2004-10-01

Full Text Available The principal objective of the study was to develop a procedure for overcoming the effects of differential skewness of test items in scale construction. It was shown that the degree of skewness of test items places an upper limit on the correlations between the items, regardless of the contents of the items. If the items are ordered in terms of skewness the resulting inter correlation matrix forms a simplex or a pseudo simplex. Factoring such a matrix results in a multiplicity of factors, most of which are artifacts. A procedure for overcoming this problem was demonstrated with items from the Locus of Control Inventory (Schepers, 1995. The analysis was based on a sample of 1662 first year university students. Opsomming Die hoofdoel van die studie was om ’n prosedure te ontwikkel om die gevolge van differensiële skeefheid van toetsitems, in skaalkonstruksie, teen te werk. Daar is getoon dat die graad van skeefheid van toetsitems ’n boonste grens plaas op die korrelasies tussen die items ongeag die inhoud daarvan. Indien die items gerangskik word volgens graad van skeefheid, sal die interkorrelasiematriks van die items ’n simpleks of pseudosimpleks vorm. Indien so ’n matriks aan faktorontleding onderwerp word, lei dit tot ’n veelheid van faktore waarvan die meerderheid artefakte is. ’n Prosedure om hierdie probleem te bowe te kom, is gedemonstreer met behulp van die items van die Lokus van Beheer-vraelys (Schepers, 1995. Die ontledings is op ’n steekproef van 1662 eerstejaaruniversiteitstudente gebaseer.

Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS: An item response theory approach

Directory of Open Access Journals (Sweden)

JOSEPH P. EIMICKE

2009-06-01

Full Text Available The aims of this paper are to present findings related to differential item functioning (DIF in the Patient Reported Outcome Measurement Information System (PROMIS depression item bank, and to discuss potential threats to the validity of results from studies of DIF. The 32 depression items studied were modified from several widely used instruments. DIF analyses of gender, age and education were performed using a sample of 735 individuals recruited by a survey polling firm. DIF hypotheses were generated by asking content experts to indicate whether or not they expected DIF to be present, and the direction of the DIF with respect to the studied comparison groups. Primary analyses were conducted using the graded item response model (for polytomous, ordered response category data with likelihood ratio tests of DIF, accompanied by magnitude measures. Sensitivity analyses were performed using other item response models and approaches to DIF detection. Despite some caveats, the items that are recommended for exclusion or for separate calibration were "I felt like crying" and "I had trouble enjoying things that I used to enjoy." The item, "I felt I had no energy," was also flagged as evidencing DIF, and recommended for additional review. On the one hand, false DIF detection (Type 1 error was controlled to the extent possible by ensuring model fit and purification. On the other hand, power for DIF detection might have been compromised by several factors, including sparse data and small sample sizes. Nonetheless, practical and not just statistical significance should be considered. In this case the overall magnitude and impact of DIF was small for the groups studied, although impact was relatively large for some individuals.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

Czech Academy of Sciences Publication Activity Database

Drabinová, Adéla; Martinková, Patrícia

2017-01-01

Roč. 54, č. 4 (2017), s. 498-517 ISSN 0022-0655 R&D Projects: GA ČR GJ15-15856Y Institutional support: RVO:67985807 Keywords : differential item functioning * non-linear regression * logistic regression * item response theory Subject RIV: AM - Education OBOR OECD: Statistics and probability Impact factor: 0.979, year: 2016

Re-evaluating a vision-related quality of life questionnaire with item response theory (IRT and differential item functioning (DIF analyses

Directory of Open Access Journals (Sweden)

Knol Dirk L

2011-09-01

Full Text Available Abstract Background For the Low Vision Quality Of Life questionnaire (LVQOL it is unknown whether the psychometric properties are satisfactory when an item response theory (IRT perspective is considered. This study evaluates some essential psychometric properties of the LVQOL questionnaire in an IRT model, and investigates differential item functioning (DIF. Methods Cross-sectional data were used from an observational study among visually-impaired patients (n = 296. Calibration was performed for every dimension of the LVQOL in the graded response model. Item goodness-of-fit was assessed with the S-X2-test. DIF was assessed on relevant background variables (i.e. age, gender, visual acuity, eye condition, rehabilitation type and administration type with likelihood-ratio tests for DIF. The magnitude of DIF was interpreted by assessing the largest difference in expected scores between subgroups. Measurement precision was assessed by presenting test information curves; reliability with the index of subject separation. Results All items of the LVQOL dimensions fitted the model. There was significant DIF on several items. For two items the maximum difference between expected scores exceeded one point, and DIF was found on multiple relevant background variables. Item 1 'Vision in general' from the "Adjustment" dimension and item 24 'Using tools' from the "Reading and fine work" dimension were removed. Test information was highest for the "Reading and fine work" dimension. Indices for subject separation ranged from 0.83 to 0.94. Conclusions The items of the LVQOL showed satisfactory item fit to the graded response model; however, two items were removed because of DIF. The adapted LVQOL with 21 items is DIF-free and therefore seems highly appropriate for use in heterogeneous populations of visually impaired patients.

Measurement equivalence and differential item functioning in family psychology.

Science.gov (United States)

Bingenheimer, Jeffrey B; Raudenbush, Stephen W; Leventhal, Tama; Brooks-Gunn, Jeanne

2005-09-01

Several hypotheses in family psychology involve comparisons of sociocultural groups. Yet the potential for cross-cultural inequivalence in widely used psychological measurement instruments threatens the validity of inferences about group differences. Methods for dealing with these issues have been developed via the framework of item response theory. These methods deal with an important type of measurement inequivalence, called differential item functioning (DIF). The authors introduce DIF analytic methods, linking them to a well-established framework for conceptualizing cross-cultural measurement equivalence in psychology (C.H. Hui and H.C. Triandis, 1985). They illustrate the use of DIF methods using data from the Project on Human Development in Chicago Neighborhoods (PHDCN). Focusing on the Caregiver Warmth and Environmental Organization scales from the PHDCN's adaptation of the Home Observation for Measurement of the Environment Inventory, the authors obtain results that exemplify the range of outcomes that may result when these methods are applied to psychological measurement instruments. (c) 2005 APA, all rights reserved

Secondary Psychometric Examination of the Dimensional Obsessive-Compulsive Scale: Classical Testing, Item Response Theory, and Differential Item Functioning.

Science.gov (United States)

Thibodeau, Michel A; Leonard, Rachel C; Abramowitz, Jonathan S; Riemann, Bradley C

2015-12-01

The Dimensional Obsessive-Compulsive Scale (DOCS) is a promising measure of obsessive-compulsive disorder (OCD) symptoms but has received minimal psychometric attention. We evaluated the utility and reliability of DOCS scores. The study included 832 students and 300 patients with OCD. Confirmatory factor analysis supported the originally proposed four-factor structure. DOCS total and subscale scores exhibited good to excellent internal consistency in both samples (α = .82 to α = .96). Patient DOCS total scores reduced substantially during treatment (t = 16.01, d = 1.02). DOCS total scores discriminated between students and patients (sensitivity = 0.76, 1 - specificity = 0.23). The measure did not exhibit gender-based differential item functioning as tested by Mantel-Haenszel chi-square tests. Expected response options for each item were plotted as a function of item response theory and demonstrated that DOCS scores incrementally discriminate OCD symptoms ranging from low to extremely high severity. Incremental differences in DOCS scores appear to represent unbiased and reliable differences in true OCD symptom severity. © The Author(s) 2014.

Gender Invariance of the Gambling Behavior Scale for Adolescents (GBS-A): An Analysis of Differential Item Functioning Using Item Response Theory.

Science.gov (United States)

Donati, Maria Anna; Chiesi, Francesca; Izzo, Viola A; Primi, Caterina

2017-01-01

As there is a lack of evidence attesting the equivalent item functioning across genders for the most employed instruments used to measure pathological gambling in adolescence, the present study was aimed to test the gender invariance of the Gambling Behavior Scale for Adolescents (GBS-A), a new measurement tool to assess the severity of Gambling Disorder (GD) in adolescents. The equivalence of the items across genders was assessed by analyzing Differential Item Functioning within an Item Response Theory framework. The GBS-A was administered to 1,723 adolescents, and the graded response model was employed. The results attested the measurement equivalence of the GBS-A when administered to male and female adolescent gamblers. Overall, findings provided evidence that the GBS-A is an effective measurement tool of the severity of GD in male and female adolescents and that the scale was unbiased and able to relieve truly gender differences. As such, the GBS-A can be profitably used in educational interventions and clinical treatments with young people.

Exploring differential item functioning (DIF) with the Rasch model: A comparison of gender differences on eighth-grade science items in the United States and Spain

Science.gov (United States)

Calvert, Tasha

Despite the attention that has been given to gender and science, boys continue to outperform girls in science achievement, particularly by the end of secondary school. Because it is unclear whether gender differences have narrowed over time (Leder, 1992; Willingham & Cole, 1997), it is important to continue a line of inquiry into the nature of gender differences, specifically at the international level. The purpose of this study was to investigate gender differences in science achievement across two countries: United States and Spain. A secondary purpose was to demonstrate an alternative method for exploring gender differences based on the many-faceted Rasch model (1980). A secondary analysis of the data from the Third International Mathematics and Science Study (TIMSS) was used to examine the relationship between gender DIF (differential item functioning) and item characteristics (item type, content, and performance expectation) across both countries. Nationally representative samples of eighth grade students in the United States and Spain who participated in TIMSS were analyzed to answer the research questions in this study. In both countries, girls showed an advantage over boys on life science items and most extended response items, whereas boys, by and large, had an advantage on earth science, physics, and chemistry items. However, even within areas that favored boys, such as physics, there were items that were differentially easier for girls. In general, patterns in gender differences were similar across both countries although there were a few differences between the countries on individual items. It was concluded that simply looking at mean differences does not provide an adequate understanding of the nature of gender differences in science achievement.

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

Science.gov (United States)

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

Parent Ratings of ADHD Symptoms: Generalized Partial Credit Model Analysis of Differential Item Functioning across Gender

Science.gov (United States)

Gomez, Rapson

2012-01-01

Objective: Generalized partial credit model, which is based on item response theory (IRT), was used to test differential item functioning (DIF) for the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.), inattention (IA), and hyperactivity/impulsivity (HI) symptoms across boys and girls. Method: To accomplish this, parents completed…

Determination of a Differential Item Functioning Procedure Using the Hierarchical Generalized Linear Model

Directory of Open Access Journals (Sweden)

Tülin Acar

2012-01-01

Full Text Available The aim of this research is to compare the result of the differential item functioning (DIF determining with hierarchical generalized linear model (HGLM technique and the results of the DIF determining with logistic regression (LR and item response theory–likelihood ratio (IRT-LR techniques on the test items. For this reason, first in this research, it is determined whether the students encounter DIF with HGLM, LR, and IRT-LR techniques according to socioeconomic status (SES, in the Turkish, Social Sciences, and Science subtest items of the Secondary School Institutions Examination. When inspecting the correlations among the techniques in terms of determining the items having DIF, it was discovered that there was significant correlation between the results of IRT-LR and LR techniques in all subtests; merely in Science subtest, the results of the correlation between HGLM and IRT-LR techniques were found significant. DIF applications can be made on test items with other DIF analysis techniques that were not taken to the scope of this research. The analysis results, which were determined by using the DIF techniques in different sample sizes, can be compared.

Racial differences in hypertension knowledge: effects of differential item functioning.

Science.gov (United States)

Ayotte, Brian J; Trivedi, Ranak; Bosworth, Hayden B

2009-01-01

Health-related knowledge is an important component in the self-management of chronic illnesses. The objective of this study was to more accurately assess racial differences in hypertension knowledge by using a latent variable modeling approach that controlled for sociodemographic factors and accounted for measurement issues in the assessment of hypertension knowledge. Cross-sectional data from 1,177 participants (45% African American; 35% female) were analyzed using a multiple indicator multiple causes (MIMIC) modeling approach. Available sociodemographic data included race, education, sex, financial status, and age. All participants completed six items on a hypertension knowledge questionnaire. Overall, the final model suggested that females, Whites, and patients with at least a high school diploma had higher latent knowledge scores than males, African Americans, and patients with less than a high school diploma, respectively. The model also detected differential item functioning (DIF) based on race for two of the items. Specifically, the error rate for African Americans was lower than would be expected given the lower level of latent knowledge on the items, on the questions related to: (a) the association between high blood pressure and kidney disease, and (b) the increased risk African Americans have for developing hypertension. Not accounting for DIF resulted in the difference between Whites and African Americans to be underestimated. These results are discussed in the context of the need for careful measurement of health-related constructs, and how measurement-related issues can result in an inaccurate estimation of racial differences in hypertension knowledge.

Investigation of MLE in nonparametric estimation methods of reliability function

International Nuclear Information System (INIS)

Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo

2001-01-01

There have been lots of trials to estimate a reliability function. In the ESReDA 20 th seminar, a new method in nonparametric way was proposed. The major point of that paper is how to use censored data efficiently. Generally there are three kinds of approach to estimate a reliability function in nonparametric way, i.e., Reduced Sample Method, Actuarial Method and Product-Limit (PL) Method. The above three methods have some limits. So we suggest an advanced method that reflects censored information more efficiently. In many instances there will be a unique maximum likelihood estimator (MLE) of an unknown parameter, and often it may be obtained by the process of differentiation. It is well known that the three methods generally used to estimate a reliability function in nonparametric way have maximum likelihood estimators that are uniquely exist. So, MLE of the new method is derived in this study. The procedure to calculate a MLE is similar just like that of PL-estimator. The difference of the two is that in the new method, the mass (or weight) of each has an influence of the others but the mass in PL-estimator not

Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

DEFF Research Database (Denmark)

Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

2010-01-01

Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise ...... when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application....

Differential items functioning to assess aggressiveness in college students / Funcionamento diferencial de itens para avaliar a agressividade de universitários

Directory of Open Access Journals (Sweden)

Fermino Fernandes Sisto

2008-01-01

Full Text Available In this research evidences of construct validity were searched analyzing the differential functioning items related to aggressiveness. The participants were 445 college students of both genders, attending the courses of Engineering, Computing and Psychology. The scale of aggressiveness composed by 81 items was collectively applied, in the classroom, to the students who consented to participate in the study. The items of the instrument were studied by means of the Rasch model. Twenty-eight items presented differential functioning item, 15 were characterized as typical for females and 13 for males. The reliability coefficients were 0.99 to the items and 0.86 to the persons. It was concluded that the aggressiveness can be measured separately on the basis of gender.

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

Science.gov (United States)

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

Nonparametric correlation models for portfolio allocation

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Casas, Isabel

2013-01-01

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural ...... currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis....

Nonparametric statistics for social and behavioral sciences

CERN Document Server

Kraska-MIller, M

2013-01-01

Introduction to Research in Social and Behavioral SciencesBasic Principles of ResearchPlanning for ResearchTypes of Research Designs Sampling ProceduresValidity and Reliability of Measurement InstrumentsSteps of the Research Process Introduction to Nonparametric StatisticsData AnalysisOverview of Nonparametric Statistics and Parametric Statistics Overview of Parametric Statistics Overview of Nonparametric StatisticsImportance of Nonparametric MethodsMeasurement InstrumentsAnalysis of Data to Determine Association and Agreement Pearson Chi-Square Test of Association and IndependenceContingency

A contingency table approach to nonparametric testing

CERN Document Server

Rayner, JCW

2000-01-01

Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effects are virtually ignored. Using a fresh approach, A Contingency Table Approach to Nonparametric Testing unifies and extends the popular, standard tests by linking them to tests based on models for data that can be presented in contingency tables.This approach unifies popular nonparametric statistical inference and makes the traditional, most commonly performed nonparametric analyses much more comp

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

Consolidation differentially modulates schema effects on memory for items and associations.

Science.gov (United States)

van Kesteren, Marlieke T R; Rijpkema, Mark; Ruiter, Dirk J; Fernández, Guillén

2013-01-01

Newly learned information that is congruent with a preexisting schema is often better remembered than information that is incongruent. This schema effect on memory has previously been associated to more efficient encoding and consolidation mechanisms. However, this effect is not always consistently supported in the literature, with differential schema effects reported for different types of memory, different retrieval cues, and the possibility of time-dependent effects related to consolidation processes. To examine these effects more directly, we tested participants on two different types of memory (item recognition and associative memory) for newly encoded visuo-tactile associations at different study-test intervals, thus probing memory retrieval accuracy for schema-congruent and schema-incongruent items and associations at different time points (t = 0, t = 20, and t = 48 hours) after encoding. Results show that the schema effect on visual item recognition only arises after consolidation, while the schema effect on associative memory is already apparent immediately after encoding, persisting, but getting smaller over time. These findings give further insight into different factors influencing the schema effect on memory, and can inform future schema experiments by illustrating the value of considering effects of memory type and consolidation on schema-modulated retrieval.

Consolidation differentially modulates schema effects on memory for items and associations.

Directory of Open Access Journals (Sweden)

Marlieke T R van Kesteren

Full Text Available Newly learned information that is congruent with a preexisting schema is often better remembered than information that is incongruent. This schema effect on memory has previously been associated to more efficient encoding and consolidation mechanisms. However, this effect is not always consistently supported in the literature, with differential schema effects reported for different types of memory, different retrieval cues, and the possibility of time-dependent effects related to consolidation processes. To examine these effects more directly, we tested participants on two different types of memory (item recognition and associative memory for newly encoded visuo-tactile associations at different study-test intervals, thus probing memory retrieval accuracy for schema-congruent and schema-incongruent items and associations at different time points (t = 0, t = 20, and t = 48 hours after encoding. Results show that the schema effect on visual item recognition only arises after consolidation, while the schema effect on associative memory is already apparent immediately after encoding, persisting, but getting smaller over time. These findings give further insight into different factors influencing the schema effect on memory, and can inform future schema experiments by illustrating the value of considering effects of memory type and consolidation on schema-modulated retrieval.

Nonparametric tests for censored data

CERN Document Server

Bagdonavicus, Vilijandas; Nikulin, Mikhail

2013-01-01

This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.

Nonparametric Bayesian Modeling of Complex Networks

DEFF Research Database (Denmark)

Schmidt, Mikkel Nørgaard; Mørup, Morten

2013-01-01

an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

Application of Group-Level Item Response Models in the Evaluation of Consumer Reports about Health Plan Quality

Science.gov (United States)

Reise, Steven P.; Meijer, Rob R.; Ainsworth, Andrew T.; Morales, Leo S.; Hays, Ron D.

2006-01-01

Group-level parametric and non-parametric item response theory models were applied to the Consumer Assessment of Healthcare Providers and Systems (CAHPS[R]) 2.0 core items in a sample of 35,572 Medicaid recipients nested within 131 health plans. Results indicated that CAHPS responses are dominated by within health plan variation, and only weakly…

Detection of Differential Item Functioning on the Kirton Adaption-Innovation Inventory Using Multiple-Group Mean and Covariance Structure Analyses.

Science.gov (United States)

Chan, David

2000-01-01

Demonstrates how the mean and covariance structure analysis model of D. Sorbom (1974) can be used to detect uniform and nonuniform differential item functioning (DIF) on polytomous ordered response items assumed to approximate a continuous scale. Uses results from 773 civil service employees administered the Kirton Adaption-Innovation Inventory…

Standard Errors for National Trends in International Large-Scale Assessments in the Case of Cross-National Differential Item Functioning

Science.gov (United States)

Sachse, Karoline A.; Haag, Nicole

2017-01-01

Standard errors computed according to the operational practices of international large-scale assessment studies such as the Programme for International Student Assessment's (PISA) or the Trends in International Mathematics and Science Study (TIMSS) may be biased when cross-national differential item functioning (DIF) and item parameter drift are…

An Examination of Differential Item Functioning on the Vanderbilt Assessment of Leadership in Education

Science.gov (United States)

Polikoff, Morgan S.; May, Henry; Porter, Andrew C.; Elliott, Stephen N.; Goldring, Ellen; Murphy, Joseph

2009-01-01

The Vanderbilt Assessment of Leadership in Education is a 360-degree assessment of the effectiveness of principals' learning-centered leadership behaviors. In this report, we present results from a differential item functioning (DIF) study of the assessment. Using data from a national field trial, we searched for evidence of DIF on school level,…

Nonparametric Bounds in the Presence of Item Nonresponse, Unfolding Brackets and Anchoring

NARCIS (Netherlands)

Vazquez-Alvarez, R.; Melenberg, B.; van Soest, A.H.O.

2001-01-01

Household surveys often suffer from nonresponse on variables such as income, savings or wealth.Recent work by Manski shows how bounds on conditional quantiles of the variable of interest can be derived, allowing for any type of nonrandom item nonresponse.The width between these bounds can be reduced

Decision support using nonparametric statistics

CERN Document Server

Beatty, Warren

2018-01-01

This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.

Examining Multiple Sources of Differential Item Functioning on the Clinician & Group CAHPS® Survey

Science.gov (United States)

Rodriguez, Hector P; Crane, Paul K

2011-01-01

Objective To evaluate psychometric properties of a widely used patient experience survey. Data Sources English-language responses to the Clinician & Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS®) survey (n = 12,244) from a 2008 quality improvement initiative involving eight southern California medical groups. Methods We used an iterative hybrid ordinal logistic regression/item response theory differential item functioning (DIF) algorithm to identify items with DIF related to patient sociodemographic characteristics, duration of the physician–patient relationship, number of physician visits, and self-rated physical and mental health. We accounted for all sources of DIF and determined its cumulative impact. Principal Findings The upper end of the CG-CAHPS® performance range is measured with low precision. With sensitive settings, some items were found to have DIF. However, overall DIF impact was negligible, as 0.14 percent of participants had salient DIF impact. Latinos who spoke predominantly English at home had the highest prevalence of salient DIF impact at 0.26 percent. Conclusions The CG-CAHPS® functions similarly across commercially insured respondents from diverse backgrounds. Consequently, previously documented racial and ethnic group differences likely reflect true differences rather than measurement bias. The impact of low precision at the upper end of the scale should be clarified. PMID:22092021

Psychometric evaluation of Persian Nomophobia Questionnaire: Differential item functioning and measurement invariance across gender.

Science.gov (United States)

Lin, Chung-Ying; Griffiths, Mark D; Pakpour, Amir H

2018-03-01

Background and aims Research examining problematic mobile phone use has increased markedly over the past 5 years and has been related to "no mobile phone phobia" (so-called nomophobia). The 20-item Nomophobia Questionnaire (NMP-Q) is the only instrument that assesses nomophobia with an underlying theoretical structure and robust psychometric testing. This study aimed to confirm the construct validity of the Persian NMP-Q using Rasch and confirmatory factor analysis (CFA) models. Methods After ensuring the linguistic validity, Rasch models were used to examine the unidimensionality of each Persian NMP-Q factor among 3,216 Iranian adolescents and CFAs were used to confirm its four-factor structure. Differential item functioning (DIF) and multigroup CFA were used to examine whether males and females interpreted the NMP-Q similarly, including item content and NMP-Q structure. Results Each factor was unidimensional according to the Rach findings, and the four-factor structure was supported by CFA. Two items did not quite fit the Rasch models (Item 14: "I would be nervous because I could not know if someone had tried to get a hold of me;" Item 9: "If I could not check my smartphone for a while, I would feel a desire to check it"). No DIF items were found across gender and measurement invariance was supported in multigroup CFA across gender. Conclusions Due to the satisfactory psychometric properties, it is concluded that the Persian NMP-Q can be used to assess nomophobia among adolescents. Moreover, NMP-Q users may compare its scores between genders in the knowledge that there are no score differences contributed by different understandings of NMP-Q items.

Exploring differential item functioning in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC

Directory of Open Access Journals (Sweden)

Pollard Beth

2012-12-01

Full Text Available Abstract Background The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC is a widely used patient reported outcome in osteoarthritis. An important, but frequently overlooked, aspect of validating health outcome measures is to establish if items exhibit differential item functioning (DIF. That is, if respondents have the same underlying level of an attribute, does the item give the same score in different subgroups or is it biased towards one subgroup or another. The aim of the study was to explore DIF in the Likert format WOMAC for the first time in a UK osteoarthritis population with respect to demographic, social, clinical and psychological factors. Methods The sample comprised a community sample of 763 people with osteoarthritis who participated in the Somerset and Avon Survey of Health. The WOMAC was explored for DIF by gender, age, social deprivation, social class, employment status, distress, body mass index and clinical factors. Ordinal regression models were used to identify DIF items. Results After adjusting for age, two items were identified for the physical functioning subscale as having DIF with age identified as the DIF factor for 2 items, gender for 1 item and body mass index for 1 item. For the WOMAC pain subscale, for people with hip osteoarthritis one item was identified with age-related DIF. The impact of the DIF items rarely had a significant effect on the conclusions of group comparisons. Conclusions Overall, the WOMAC performed well with only a small number of DIF items identified. However, as DIF items were identified in for the WOMAC physical functioning subscale it would be advisable to analyse data taking into account the possible impact of the DIF items when weight, gender or especially age effects, are the focus of interest in UK-based osteoarthritis studies. Similarly for the WOMAC pain subscale in people with hip osteoarthritis it would be worthwhile to analyse data taking into account the

Theory of nonparametric tests

CERN Document Server

Dickhaus, Thorsten

2018-01-01

This textbook provides a self-contained presentation of the main concepts and methods of nonparametric statistical testing, with a particular focus on the theoretical foundations of goodness-of-fit tests, rank tests, resampling tests, and projection tests. The substitution principle is employed as a unified approach to the nonparametric test problems discussed. In addition to mathematical theory, it also includes numerous examples and computer implementations. The book is intended for advanced undergraduate, graduate, and postdoc students as well as young researchers. Readers should be familiar with the basic concepts of mathematical statistics typically covered in introductory statistics courses.

Nonparametric statistics with applications to science and engineering

CERN Document Server

Kvam, Paul H

2007-01-01

A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provide...

Differential Item Functioning of the Psychological Domain of the Menopause Rating Scale

Science.gov (United States)

Portela-Buelvas, Katherin; Oviedo, Heidi C.; Herazo, Edwin; Campo-Arias, Adalberto

2016-01-01

Introduction. Quality of life could be quantified with the Menopause Rating Scale (MRS), which evaluates the severity of somatic, psychological, and urogenital symptoms in menopause. However, differential item functioning (DIF) analysis has not been applied previously. Objective. To establish the DIF of the psychological domain of the MRS in Colombian women. Methods. 4,009 women aged between 40 and 59 years, who participated in the CAVIMEC (Calidad de Vida en la Menopausia y Etnias Colombianas) project, were included. Average age was 49.0 ± 5.9 years. Women were classified in mestizo, Afro-Colombian, and indigenous. The results were presented as averages and standard deviation (X ± SD). A p value <0.001 was considered statistically significant. Results. In mestizo women, the highest X ± SD were obtained in physical and mental exhaustion (PME) (0.86 ± 0.93) and the lowest ones in anxiety (0.44 ± 0.79). In Afro-Colombian women, an average score of 0.99 ± 1.07 for PME and 0.63 ± 0.88 for anxiety was gotten. Indigenous women obtained an increased average score for PME (1.33 ± 0.93). The lowest score was evidenced in depressive mood (0.50 ± 0.81), which is different from other Colombian women (p < 0.001). Conclusions. The psychological items of the MRS show differential functioning according to the ethnic group, which may induce systematic error in the measurement of the construct. PMID:27847825

Differential Item Functioning of the Psychological Domain of the Menopause Rating Scale.

Science.gov (United States)

Monterrosa-Castro, Alvaro; Portela-Buelvas, Katherin; Oviedo, Heidi C; Herazo, Edwin; Campo-Arias, Adalberto

2016-01-01

Introduction. Quality of life could be quantified with the Menopause Rating Scale (MRS), which evaluates the severity of somatic, psychological, and urogenital symptoms in menopause. However, differential item functioning (DIF) analysis has not been applied previously. Objective . To establish the DIF of the psychological domain of the MRS in Colombian women. Methods . 4,009 women aged between 40 and 59 years, who participated in the CAVIMEC (Calidad de Vida en la Menopausia y Etnias Colombianas) project, were included. Average age was 49.0 ± 5.9 years. Women were classified in mestizo, Afro-Colombian, and indigenous. The results were presented as averages and standard deviation ( X ± SD). A p value <0.001 was considered statistically significant. Results . In mestizo women, the highest X ± SD were obtained in physical and mental exhaustion (PME) (0.86 ± 0.93) and the lowest ones in anxiety (0.44 ± 0.79). In Afro-Colombian women, an average score of 0.99 ± 1.07 for PME and 0.63 ± 0.88 for anxiety was gotten. Indigenous women obtained an increased average score for PME (1.33 ± 0.93). The lowest score was evidenced in depressive mood (0.50 ± 0.81), which is different from other Colombian women ( p < 0.001). Conclusions . The psychological items of the MRS show differential functioning according to the ethnic group, which may induce systematic error in the measurement of the construct.

A simulation study provided sample size guidance for differential item functioning (DIF) studies using short scales

DEFF Research Database (Denmark)

Scott, Neil W.; Fayers, Peter M.; Bottomley, Andrew

2009-01-01

Differential item functioning (DIF) analyses are increasingly used to evaluate health-related quality of life (HRQoL) instruments, which often include relatively short subscales. Computer simulations were used to explore how various factors including scale length affect analysis of DIF by ordinal...... logistic regression....

Nonparametric Transfer Function Models

Science.gov (United States)

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Bayesian nonparametric data analysis

CERN Document Server

Müller, Peter; Jara, Alejandro; Hanson, Tim

2015-01-01

This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.

Differential Item Functioning (DIF) Etnis pada Big Five Inventory (BFI) versi Adaptasi Fakultas Psikologi Universitas Sumatera Utara

OpenAIRE

Manik, Hitler

2014-01-01

Big Five Inventory (BFI) is one of personality test had been adapted into Indonesia language. More research had been developed to adapt the Indonesian Big Five Inventory. The purpose of this research is to check whether BFI’s personality test is fair if apply to ethnic of Batak Toba and Java. Therefore, examination of BFI’s items is needed. In psychology, especially in psychometric study, it is called Differential Item Functioning (DIF). Subject in this research is 327 people around 18 to 40 ...

Evaluating the validity of the Work Role Functioning Questionnaire (Canadian French version) using classical test theory and item response theory.

Science.gov (United States)

Hong, Quan Nha; Coutu, Marie-France; Berbiche, Djamal

2017-01-01

The Work Role Functioning Questionnaire (WRFQ) was developed to assess workers' perceived ability to perform job demands and is used to monitor presenteeism. Still few studies on its validity can be found in the literature. The purpose of this study was to assess the items and factorial composition of the Canadian French version of the WRFQ (WRFQ-CF). Two measurement approaches were used to test the WRFQ-CF: Classical Test Theory (CTT) and non-parametric Item Response Theory (IRT). A total of 352 completed questionnaires were analyzed. A four-factor and three-factor model models were tested and shown respectively good fit with 14 items (Root Mean Square Error of Approximation (RMSEA) = 0.06, Standardized Root Mean Square Residual (SRMR) = 0.04, Bentler Comparative Fit Index (CFI) = 0.98) and with 17 items (RMSEA = 0.059, SRMR = 0.048, CFI = 0.98). Using IRT, 13 problematic items were identified, of which 9 were common with CTT. This study tested different models with fewer problematic items found in a three-factor model. Using a non-parametric IRT and CTT for item purification gave complementary results. IRT is still scarcely used and can be an interesting alternative method to enhance the quality of a measurement instrument. More studies are needed on the WRFQ-CF to refine its items and factorial composition.

Nonparametric functional mapping of quantitative trait loci.

Science.gov (United States)

Yang, Jie; Wu, Rongling; Casella, George

2009-03-01

Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

Differential Item Functioning (DIF) among Spanish-Speaking English Language Learners (ELLs) in State Science Tests

Science.gov (United States)

Ilich, Maria O.

Psychometricians and test developers evaluate standardized tests for potential bias against groups of test-takers by using differential item functioning (DIF). English language learners (ELLs) are a diverse group of students whose native language is not English. While they are still learning the English language, they must take their standardized tests for their school subjects, including science, in English. In this study, linguistic complexity was examined as a possible source of DIF that may result in test scores that confound science knowledge with a lack of English proficiency among ELLs. Two years of fifth-grade state science tests were analyzed for evidence of DIF using two DIF methods, Simultaneous Item Bias Test (SIBTest) and logistic regression. The tests presented a unique challenge in that the test items were grouped together into testlets---groups of items referring to a scientific scenario to measure knowledge of different science content or skills. Very large samples of 10, 256 students in 2006 and 13,571 students in 2007 were examined. Half of each sample was composed of Spanish-speaking ELLs; the balance was comprised of native English speakers. The two DIF methods were in agreement about the items that favored non-ELLs and the items that favored ELLs. Logistic regression effect sizes were all negligible, while SIBTest flagged items with low to high DIF. A decrease in socioeconomic status and Spanish-speaking ELL diversity may have led to inconsistent SIBTest effect sizes for items used in both testing years. The DIF results for the testlets suggested that ELLs lacked sufficient opportunity to learn science content. The DIF results further suggest that those constructed response test items requiring the student to draw a conclusion about a scientific investigation or to plan a new investigation tended to favor ELLs.

A new Integrated Negative Symptom structure of the Positive and Negative Syndrome Scale (PANSS) in schizophrenia using item response analysis.

Science.gov (United States)

Khan, Anzalee; Lindenmayer, Jean-Pierre; Opler, Mark; Yavorsky, Christian; Rothman, Brian; Lucic, Luka

2013-10-01

Debate persists with regard to how best to categorize the syndromal dimension of negative symptoms in schizophrenia. The aim was to first review published Principle Components Analysis (PCA) of the PANSS, and extract items most frequently included in the negative domain, and secondly, to examine the quality of items using Item Response Theory (IRT) to select items that best represent a measurable dimension (or dimensions) of negative symptoms. First, 22 factor analyses and PCA met were included. Second, using a large dataset (n=7187) of participants in clinical trials with chronic schizophrenia, we extracted items loading on one or more PCA. Third, items not loading with a value of ≥ 0.5, or loading on more than one component with values of ≥ 0.5 were discarded. Fourth, resulting items were included in a non-parametric IRT and retained based on Option Characteristic Curves (OCCs) and Item Characteristic Curves (ICCs). 15 items loaded on a negative domain in at least one study, with Emotional Withdrawal loading on all studies. Non-parametric IRT retained nine items as an Integrated Negative Factor: Emotional Withdrawal, Blunted Affect, Passive/Apathetic Social Withdrawal, Poor Rapport, Lack of Spontaneity/Conversation Flow, Active Social Avoidance, Disturbance of Volition, Stereotyped Thinking and Difficulty in Abstract Thinking. This is the first study to use a psychometric IRT process to arrive at a set of negative symptom items. Future steps will include further examination of these nine items in terms of their stability, sensitivity to change, and correlations with functional and cognitive outcomes. © 2013 Elsevier B.V. All rights reserved.

Introduction to nonparametric statistics for the biological sciences using R

CERN Document Server

MacFarland, Thomas W

2016-01-01

This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses a...

Gender-based Differential Item Functioning in the Application of the Theory of Planned Behavior for the Study of Entrepreneurial Intentions.

Science.gov (United States)

Zampetakis, Leonidas A; Bakatsaki, Maria; Litos, Charalambos; Kafetsios, Konstantinos G; Moustakis, Vassilis

2017-01-01

Over the past years the percentage of female entrepreneurs has increased, yet it is still far below of that for males. Although various attempts have been made to explain differences in mens' and women's entrepreneurial attitudes and intentions, the extent to which those differences are due to self-report biases has not been yet considered. The present study utilized Differential Item Functioning (DIF) to compare men and women's reporting on entrepreneurial intentions. DIF occurs in situations where members of different groups show differing probabilities of endorsing an item despite possessing the same level of the ability that the item is intended to measure. Drawing on the theory of planned behavior (TPB), the present study investigated whether constructs such as entrepreneurial attitudes, perceived behavioral control, subjective norms and intention would show gender differences and whether these gender differences could be explained by DIF. Using DIF methods on a dataset of 1800 Greek participants (50.4% female) indicated that differences at the item-level are almost non-existent. Moreover, the differential test functioning (DTF) analysis, which allows assessing the overall impact of DIF effects with all items being taken into account simultaneously, suggested that the effect of DIF across all the items for each scale was negligible. Future research should consider that measurement invariance can be assumed when using TPB constructs for the study of entrepreneurial motivation independent of gender.

A Differential Item Functional Analysis by Age of Perceived Interpersonal Discrimination in a Multi-racial/ethnic Sample of Adults.

Science.gov (United States)

Owens, Sherry; Kristjansson, Alfgeir L; Hunte, Haslyn E R

2015-11-05

We investigated whether individual items on the nine item William's Perceived Everyday Discrimination Scale (EDS) functioned differently by age (ethnic group. Overall, Asian and Hispanic respondents reported less discrimination than Whites; on the other hand, African Americans and Black Caribbeans reported more discrimination than Whites. Regardless of race/ethnicity, the younger respondents (aged ethnicity, the results were mixed for 19 out of 45 tests of DIF (40%). No differences in item function were observed among Black Caribbeans. "Being called names or insulted" and others acting as "if they are afraid" of the respondents were the only two items that did not exhibit differential item functioning by age across all racial/ethnic groups. Overall, our findings suggest that the EDS scale should be used with caution in multi-age multi-racial/ethnic samples.

Differential item functional analysis on pedagogic and content knowledge (PCK) questionnaire for Indonesian teachers using RASCH model

Science.gov (United States)

Rahmani, B. D.

2018-01-01

The purpose of this paper is to evaluate Indonesian senior high school teacher’s pedagogical content knowledge also their perception toward curriculum changing in West Java Indonesia. The data used in this study were derived from a questionnaire survey conducted among teachers in Bandung, West Java. A total of 61 usable responses were collected. The Differential Item Functioning (DIFF) was used to analyze the data whether the item had a difference or not toward gender, education background also on school location. However, the result showed that there was no any significant difference on gender and school location toward the item response but educational background. As a conclusion, the teacher’s educational background influence on giving the response to the questionnaire. Therefore, it is suggested in the future to construct the items on the questionnaire which is coped the differences of the participant particularly the educational background.

Identifying group-sensitive physical activities: a differential item functioning analysis of NHANES data.

Science.gov (United States)

Gao, Yong; Zhu, Weimo

2011-05-01

The purpose of this study was to identify subgroup-sensitive physical activities (PA) using differential item functioning (DIF) analysis. A sub-unweighted sample of 1857 (men=923 and women=934) from the 2003-2004 National Health and Nutrition Examination Survey PA questionnaire data was used for the analyses. Using the Mantel-Haenszel, the simultaneous item bias test, and the ANOVA DIF methods, 33 specific leisure-time moderate and/or vigorous PA (MVPA) items were analyzed for DIF across race/ethnicity, gender, education, income, and age groups. Many leisure-time MVPA items were identified as large DIF items. When participating in the same amount of leisure-time MVPA, non-Hispanic blacks were more likely to participate in basketball and dance activities than non-Hispanic whites (NHW); NHW were more likely to participated in golf and hiking than non-Hispanic blacks; Hispanics were more likely to participate in dancing, hiking, and soccer than NHW, whereas NHW were more likely to engage in bicycling, golf, swimming, and walking than Hispanics; women were more likely to participate in aerobics, dancing, stretching, and walking than men, whereas men were more likely to engage in basketball, fishing, golf, running, soccer, weightlifting, and hunting than women; educated persons were more likely to participate in jogging and treadmill exercise than less educated persons; persons with higher incomes were more likely to engage in golf than those with lower incomes; and adults (20-59 yr) were more likely to participate in basketball, dancing, jogging, running, and weightlifting than older adults (60+ yr), whereas older adults were more likely to participate in walking and golf than younger adults. DIF methods are able to identify subgroup-sensitive PA and thus provide useful information to help design group-sensitive, targeted interventions for disadvantaged PA subgroups. © 2011 by the American College of Sports Medicine

Gender-based Differential Item Functioning in the Application of the Theory of Planned Behavior for the Study of Entrepreneurial Intentions

Science.gov (United States)

Zampetakis, Leonidas A.; Bakatsaki, Maria; Litos, Charalambos; Kafetsios, Konstantinos G.; Moustakis, Vassilis

2017-01-01

Over the past years the percentage of female entrepreneurs has increased, yet it is still far below of that for males. Although various attempts have been made to explain differences in mens’ and women’s entrepreneurial attitudes and intentions, the extent to which those differences are due to self-report biases has not been yet considered. The present study utilized Differential Item Functioning (DIF) to compare men and women’s reporting on entrepreneurial intentions. DIF occurs in situations where members of different groups show differing probabilities of endorsing an item despite possessing the same level of the ability that the item is intended to measure. Drawing on the theory of planned behavior (TPB), the present study investigated whether constructs such as entrepreneurial attitudes, perceived behavioral control, subjective norms and intention would show gender differences and whether these gender differences could be explained by DIF. Using DIF methods on a dataset of 1800 Greek participants (50.4% female) indicated that differences at the item-level are almost non-existent. Moreover, the differential test functioning (DTF) analysis, which allows assessing the overall impact of DIF effects with all items being taken into account simultaneously, suggested that the effect of DIF across all the items for each scale was negligible. Future research should consider that measurement invariance can be assumed when using TPB constructs for the study of entrepreneurial motivation independent of gender. PMID:28386244

On Cooper's Nonparametric Test.

Science.gov (United States)

Schmeidler, James

1978-01-01

The basic assumption of Cooper's nonparametric test for trend (EJ 125 069) is questioned. It is contended that the proper assumption alters the distribution of the statistic and reduces its usefulness. (JKS)

A nonparametric mixture model for cure rate estimation.

Science.gov (United States)

Peng, Y; Dear, K B

2000-03-01

Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

Differential Item Functioning of Pathological Gambling Criteria: An Examination of Gender, Race/Ethnicity, and Age

OpenAIRE

Sacco, Paul; Torres, Luis R.; Cunningham-Williams, Renee M.; Woods, Carol; Unick, G. Jay

2011-01-01

This study tested for the presence of differential item functioning (DIF) in DSM-IV Pathological Gambling Disorder (PGD) criteria based on gender, race/ethnicity and age. Using a nationally representative sample of adults from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), indicating current gambling (n = 10,899), Multiple Indicator-Multiple Cause (MIMIC) models tested for DIF, controlling for income, education, and marital status. Compared to the reference grou...

A Structural Labor Supply Model with Nonparametric Preferences

NARCIS (Netherlands)

van Soest, A.H.O.; Das, J.W.M.; Gong, X.

2000-01-01

Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis.This paper presents an example where nonparametric flexibility can be attained

Nonparametric Bayesian inference for multidimensional compound Poisson processes

NARCIS (Netherlands)

Gugushvili, S.; van der Meulen, F.; Spreij, P.

2015-01-01

Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,

2nd Conference of the International Society for Nonparametric Statistics

CERN Document Server

Manteiga, Wenceslao; Romo, Juan

2016-01-01

This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers...

Bayesian nonparametric hierarchical modeling.

Science.gov (United States)

Dunson, David B

2009-04-01

In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard

and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

Funcionamento diferencial de itens para avaliar a agressividade de universitários Differential items functioning to assess aggressiveness in college students

Directory of Open Access Journals (Sweden)

Fermino Fernandes Sisto

2008-01-01

Full Text Available Nesta pesquisa buscou-se evidência de validade de construto relacionada ao funcionamento dos itens para diferenciar sexos em um instrumento de agressividade. Participaram 445 universitários, de ambos os sexos, dos cursos de Engenharia, Computação e Psicologia. A escala de agressividade composta por 81 itens foi aplicada coletivamente, em sala de aula, nos estudantes que consentiram em participar do estudo. Os itens do instrumento foram analisados por meio do modelo Rasch. Vinte e oito itens apresentaram funcionamento diferencial, sendo 15 condutas mais características de pessoas do sexo feminino e outras 13 mais características do masculino. Os índices de precisão foram de 0,99 para os itens e 0,86 para as pessoas. Conclui-se que a agressividade pode ser medida separadamente em razão do sexo.In this research evidences of construct validity were searched analyzing the differential functioning items related to aggressiveness. The participants were 445 college students of both genders, attending the courses of Engineering, Computing and Psychology. The scale of aggressiveness composed by 81 items was collectively applied, in the classroom, to the students who consented to participate in the study. The items of the instrument were studied by means of the Rasch model. Twenty-eight items presented differential functioning item, 15 were characterized as typical for females and 13 for males. The reliability coefficients were 0.99 to the items and 0.86 to the persons. It was concluded that the aggressiveness can be measured separately on the basis of gender.

Comparing Two Versions of the MEOCS Using Differential Item Functioning

National Research Council Canada - National Science Library

Truhon, Stephen

2003-01-01

...) from item response theory (IRT). DIF was found for the majority of the 40 items examined, although in many cases the DIF indicated improvements in the revised items. Implications for these scales and for the use of IRT with the MEOCS are discussed.

Checking Equity: Why Differential Item Functioning Analysis Should Be a Routine Part of Developing Conceptual Assessments

Czech Academy of Sciences Publication Activity Database

Martinková, Patrícia; Drabinová, Adéla; Liaw, Y.L.; Sanders, E.A.; McFarland, J.L.; Price, R.M.

2017-01-01

Roč. 16, č. 2 (2017), č. článku rm2. ISSN 1931-7913 R&D Projects: GA ČR GJ15-15856Y Grant - others:NSF(US) DUE-1043443 Institutional support: RVO:67985807 Keywords : differential item functioning * fairness * conceptual assessments * concept inventory * undergraduate education * bias Subject RIV: AM - Education OBOR OECD: Education , special (to gifted persons, those with learning disabilities) Impact factor: 3.930, year: 2016

[Age- and sex-specific reference intervals for 10 health examination items: mega-data from a Japanese Health Service Association].

Science.gov (United States)

Suka, Machi; Yoshida, Katsumi; Kawai, Tadashi; Aoki, Yoshikazu; Yamane, Noriyuki; Yamauchi, Kuniaki

2005-07-01

To determine age- and sex-specific reference intervals for 10 health examination items in Japanese adults. Health examination data were accumulated from 24 different prefectural health service associations affiliated with the Japan Association of Health Service. Those who were non-smokers, drank less than 7 days/week, and had a body mass index of 18.5-24.9kg/m2 were sampled as a reference population (n = 737,538; 224,947 men and 512,591 women). After classified by age and sex, reference intervals for 10 health examination items (systolic blood pressure, diastolic blood pressure, total cholesterol, triglyceride, glucose, uric acid, AST, ALT, gamma-GT, and hemoglobin) were estimated using the parametric and nonparametric methods. In every item except for hemoglobin, men had higher reference intervals than women. Systolic blood pressure, total cholesterol, and glucose showed an upward trend in values with increasing age. Hemoglobin showed a downward trend in values with increasing age. Triglyceride, ALT, and gamma-GT reached a peak in middle age. Overall, parametric estimates showed narrower reference intervals than non-parametric estimates. Reference intervals vary with age and sex. Age- and sex-specific reference intervals may contribute to better assessment of health examination data.

A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING

OpenAIRE

Temel, Tugrul T.

2001-01-01

This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test. The paper also develops a Mathematica Code for the test algorithm.

Improving measurement of injection drug risk behavior using item response theory.

Science.gov (United States)

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

Science.gov (United States)

Ghosh, Debashis; Chinnaiyan, Arul M

2009-01-01

In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

Nonparametric identification of copula structures

KAUST Repository

Li, Bo; Genton, Marc G.

2013-01-01

We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric

Surface Estimation, Variable Selection, and the Nonparametric Oracle Property.

Science.gov (United States)

Storlie, Curtis B; Bondell, Howard D; Reich, Brian J; Zhang, Hao Helen

2011-04-01

Variable selection for multivariate nonparametric regression is an important, yet challenging, problem due, in part, to the infinite dimensionality of the function space. An ideal selection procedure should be automatic, stable, easy to use, and have desirable asymptotic properties. In particular, we define a selection procedure to be nonparametric oracle (np-oracle) if it consistently selects the correct subset of predictors and at the same time estimates the smooth surface at the optimal nonparametric rate, as the sample size goes to infinity. In this paper, we propose a model selection procedure for nonparametric models, and explore the conditions under which the new method enjoys the aforementioned properties. Developed in the framework of smoothing spline ANOVA, our estimator is obtained via solving a regularization problem with a novel adaptive penalty on the sum of functional component norms. Theoretical properties of the new estimator are established. Additionally, numerous simulated and real examples further demonstrate that the new approach substantially outperforms other existing methods in the finite sample setting.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

Directory of Open Access Journals (Sweden)

Zahra Sharafi

2017-01-01

Full Text Available Background. The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods. The ordinal logistic regression (OLR and hierarchical ordinal logistic regression (HOLR were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™ 4.0 collected from 576 healthy school children were analyzed. Results. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

Recent Advances and Trends in Nonparametric Statistics

CERN Document Server

Akritas, MG

2003-01-01

The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection o

A nonparametric spatial scan statistic for continuous data.

Science.gov (United States)

Jung, Inkyung; Cho, Ho Jin

2015-10-20

Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.

Differential item functioning (DIF) in the EORTC QLQ-C30: a comparison of baseline, on-treatment and off-treatment data

DEFF Research Database (Denmark)

Scott, Neil W.; Fayers, Peter M.; Aaronson, Neil K.

2009-01-01

Differential item functioning (DIF) analyses can be used to explore translation, cultural, gender or other differences in the performance of quality of life (QoL) instruments. These analyses are commonly performed using "baseline" or pretreatment data. We previously reported DIF analyses to examine...

An item response theory analysis of Harter's Self-Perception Profile for Children or why strong clinical scales should be distrusted

NARCIS (Netherlands)

Egberink, Iris J. L.; Meijer, Rob R.

The authors investigated the psychometric properties of the subscales of the Self-Perception Profile for Children with item response theory (IRT) models using a sample of 611 children. Results from a nonparametric Mokken analysis and a parametric IRT approach for boys (n = 268) and girls (n = 343)

A ¤nonparametric dynamic additive regression model for longitudinal data

DEFF Research Database (Denmark)

Martinussen, T.; Scheike, T. H.

2000-01-01

dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models......dynamic linear models, estimating equations, least squares, longitudinal data, nonparametric methods, partly conditional mean models, time-varying-coefficient models...

Funcionamiento diferencial del item en la evaluación internacional PISA. Detección y comprensión. [Differential Item Functioning in the PISA Project: Detection and Understanding

Directory of Open Access Journals (Sweden)

Paula Elosua

2006-08-01

Full Text Available This report analyses the differential item functioning (DIF in the Programme for Indicators of Student Achievement PISA2000. The items studied are coming from the Reading Comprehension Test. We analyzed the released items from this year because we wanted to join the detection of DIF and its understanding. The reference group is the sample of United Kingdom and the focal group is the Spanish sample. The procedures of detection are Mantel-Haenszel, Logistic Regression and the standardized mean difference, and their extensions for polytomous items. Two items were flagged and the post-hoc analysis didn’t explain the causes of DIF entirely. Este trabajo analiza el funcionamiento diferencial del ítem (FDI de la prueba de comprensión lectora de la evaluación PISA2000 entre la muestras del Reino Unido y España. Se estudian los ítems liberados con el fin de aunar las fases de detección del FDI con la comprensión de sus causas. En la fase de detección se comparan los resultados de los procedimientos Mantel-Haenszel, Regresión Logística y Medias Estandarizadas en sus versiones para ítems dicotómicos y politómicos. Los resultados muestran que dos ítems presentan funcionamiento diferencial aunque el estudio post-hoc llevado a cabo sobre su contenido no ha podido precisar sus causas.

Nonparametric analysis of blocked ordered categories data: some examples revisited

Directory of Open Access Journals (Sweden)

O. Thas

2006-08-01

Full Text Available Nonparametric analysis for general block designs can be given by using the Cochran-Mantel-Haenszel (CMH statistics. We demonstrate this with four examples and note that several well-known nonparametric statistics are special cases of CMH statistics.

Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

Directory of Open Access Journals (Sweden)

Zhanchao Li

2013-01-01

Full Text Available The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model and change of sequence distribution law of nonparametric statistical model. On this basis, through the reduction of change point problem, the establishment of basic nonparametric change point model, and asymptotic analysis on test method of basic change point problem, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is created in consideration of the situation that in practice concrete dam crack behavior may have more abnormality points. And the nonparametric change point diagnosis method of concrete dam crack behavior abnormality is used in the actual project, demonstrating the effectiveness and scientific reasonableness of the method established. Meanwhile, the nonparametric change point diagnosis method of concrete dam crack behavior abnormality has a complete theoretical basis and strong practicality with a broad application prospect in actual project.

Nonparametric Mixture Models for Supervised Image Parcellation.

Science.gov (United States)

Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

2009-09-01

We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

Nonparametric Inference for Periodic Sequences

KAUST Repository

Sun, Ying

2012-02-01

This article proposes a nonparametric method for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator of integer periods. This estimator is investigated both theoretically and by simulation.We also propose a nonparametric test of the null hypothesis that the data have constantmean against the alternative that the sequence of means is periodic. Finally, our methodology is demonstrated on three well-known time series: the sunspots and lynx trapping data, and the El Niño series of sea surface temperatures. © 2012 American Statistical Association and the American Society for Quality.

Assessing the Straightforwardly-Worded Brief Fear of Negative Evaluation Scale for Differential Item Functioning Across Gender and Ethnicity.

Science.gov (United States)

Harpole, Jared K; Levinson, Cheri A; Woods, Carol M; Rodebaugh, Thomas L; Weeks, Justin W; Brown, Patrick J; Heimberg, Richard G; Menatti, Andrew R; Blanco, Carlos; Schneier, Franklin; Liebowitz, Michael

2015-06-01

The Brief Fear of Negative Evaluation Scale (BFNE; Leary Personality and Social Psychology Bulletin , 9, 371-375, 1983) assesses fear and worry about receiving negative evaluation from others. Rodebaugh et al. Psychological Assessment, 16 , 169-181, (2004) found that the BFNE is composed of a reverse-worded factor (BFNE-R) and straightforwardly-worded factor (BFNE-S). Further, they found the BFNE-S to have better psychometric properties and provide more information than the BFNE-R. Currently there is a lack of research regarding the measurement invariance of the BFNE-S across gender and ethnicity with respect to item thresholds. The present study uses item response theory (IRT) to test the BFNE-S for differential item functioning (DIF) related to gender and ethnicity (White, Asian, and Black). Six data sets consisting of clinical, community, and undergraduate participants were utilized ( N =2,109). The factor structure of the BFNE-S was confirmed using categorical confirmatory factor analysis, IRT model assumptions were tested, and the BFNE-S was evaluated for DIF. Item nine demonstrated significant non-uniform DIF between White and Black participants. No other items showed significant uniform or non-uniform DIF across gender or ethnicity. Results suggest the BFNE-S can be used reliably with men and women and Asian and White participants. More research is needed to understand the implications of using the BFNE-S with Black participants.

An item response theory analysis of Harter’s self-perception profile for children or why strong clinical scales should be distrusted

NARCIS (Netherlands)

Egberink, I.J.L.; Meijer, R.R.

2011-01-01

The authors investigated the psychometric properties of the subscales of the Self-Perception Profile for Children with item response theory (IRT) models using a sample of 611 children. Results from a nonparametric Mokken analysis and a parametric IRT approach for boys (n = 268) and girls (n = 343)

DPpackage: Bayesian Semi- and Nonparametric Modeling in R

Directory of Open Access Journals (Sweden)

Alejandro Jara

2011-04-01

Full Text Available Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison and for eliciting the precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling for each model is carried out using compiled C, C++ or Fortran code.

Item bias detection in the Hospital Anxiety and Depression Scale using structural equation modeling: comparison with other item bias detection methods

NARCIS (Netherlands)

Verdam, M.G.E.; Oort, F.J.; Sprangers, M.A.G.

Purpose Comparison of patient-reported outcomes may be invalidated by the occurrence of item bias, also known as differential item functioning. We show two ways of using structural equation modeling (SEM) to detect item bias: (1) multigroup SEM, which enables the detection of both uniform and

Non-parametric tests of productive efficiency with errors-in-variables

NARCIS (Netherlands)

Kuosmanen, T.K.; Post, T.; Scholtes, S.

2007-01-01

We develop a non-parametric test of productive efficiency that accounts for errors-in-variables, following the approach of Varian. [1985. Nonparametric analysis of optimizing behavior with measurement error. Journal of Econometrics 30(1/2), 445-458]. The test is based on the general Pareto-Koopmans

Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm

International Nuclear Information System (INIS)

Zhong, X.; Ichchou, M.; Saidi, A.

2010-01-01

Various parametric skewed distributions are widely used to model the time-to-failure (TTF) in the reliability analysis of mechatronic systems, where many items are unobservable due to the high cost of testing. Estimating the parameters of those distributions becomes a challenge. Previous research has failed to consider this problem due to the difficulty of dependency modeling. Recently the methodology of Bayesian networks (BNs) has greatly contributed to the reliability analysis of complex systems. In this paper, the problem of system reliability assessment (SRA) is formulated as a BN considering the parameter uncertainty. As the quantitative specification of BN, a normal distribution representing the stochastic nature of TTF distribution is learned to capture the interactions between the basic items and their output items. The approximation inference of our continuous BN model is performed by a modified version of nonparametric belief propagation (NBP) which can avoid using a junction tree that is inefficient for the mechatronic case because of the large treewidth. After reasoning, we obtain the marginal posterior density of each TTF model parameter. Other information from diverse sources and expert priors can be easily incorporated in this SRA model to achieve more accurate results. Simulation in simple and complex cases of mechatronic systems demonstrates that the posterior of the parameter network fits the data well and the uncertainty passes effectively through our BN based SRA model by using the modified NBP.

Nonparametric Monitoring for Geotechnical Structures Subject to Long-Term Environmental Change

Directory of Open Access Journals (Sweden)

Hae-Bum Yun

2011-01-01

Full Text Available A nonparametric, data-driven methodology of monitoring for geotechnical structures subject to long-term environmental change is discussed. Avoiding physical assumptions or excessive simplification of the monitored structures, the nonparametric monitoring methodology presented in this paper provides reliable performance-related information particularly when the collection of sensor data is limited. For the validation of the nonparametric methodology, a field case study was performed using a full-scale retaining wall, which had been monitored for three years using three tilt gauges. Using the very limited sensor data, it is demonstrated that important performance-related information, such as drainage performance and sensor damage, could be disentangled from significant daily, seasonal and multiyear environmental variations. Extensive literature review on recent developments of parametric and nonparametric data processing techniques for geotechnical applications is also presented.

Differential Item Functioning in While-Listening Performance Tests: The Case of the International English Language Testing System (IELTS) Listening Module

Science.gov (United States)

Aryadoust, Vahid

2012-01-01

This article investigates a version of the International English Language Testing System (IELTS) listening test for evidence of differential item functioning (DIF) based on gender, nationality, age, and degree of previous exposure to the test. Overall, the listening construct was found to be underrepresented, which is probably an important cause…

portfolio optimization based on nonparametric estimation methods

Directory of Open Access Journals (Sweden)

mahsa ghandehari

2017-03-01

Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.

Robustifying Bayesian nonparametric mixtures for count data.

Science.gov (United States)

Canale, Antonio; Prünster, Igor

2017-03-01

Our motivating application stems from surveys of natural populations and is characterized by large spatial heterogeneity in the counts, which makes parametric approaches to modeling local animal abundance too restrictive. We adopt a Bayesian nonparametric approach based on mixture models and innovate with respect to popular Dirichlet process mixture of Poisson kernels by increasing the model flexibility at the level both of the kernel and the nonparametric mixing measure. This allows to derive accurate and robust estimates of the distribution of local animal abundance and of the corresponding clusters. The application and a simulation study for different scenarios yield also some general methodological implications. Adding flexibility solely at the level of the mixing measure does not improve inferences, since its impact is severely limited by the rigidity of the Poisson kernel with considerable consequences in terms of bias. However, once a kernel more flexible than the Poisson is chosen, inferences can be robustified by choosing a prior more general than the Dirichlet process. Therefore, to improve the performance of Bayesian nonparametric mixtures for count data one has to enrich the model simultaneously at both levels, the kernel and the mixing measure. © 2016, The International Biometric Society.

Comparing parametric and nonparametric regression methods for panel data

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

Comparative analysis of automotive paints by laser induced breakdown spectroscopy and nonparametric permutation tests

International Nuclear Information System (INIS)

McIntee, Erin; Viglino, Emilie; Rinke, Caitlin; Kumor, Stephanie; Ni Liqiang; Sigman, Michael E.

2010-01-01

Laser-induced breakdown spectroscopy (LIBS) has been investigated for the discrimination of automobile paint samples. Paint samples from automobiles of different makes, models, and years were collected and separated into sets based on the color, presence or absence of effect pigments and the number of paint layers. Twelve LIBS spectra were obtained for each paint sample, each an average of a five single shot 'drill down' spectra from consecutive laser ablations in the same spot on the sample. Analyses by a nonparametric permutation test and a parametric Wald test were performed to determine the extent of discrimination within each set of paint samples. The discrimination power and Type I error were assessed for each data analysis method. Conversion of the spectral intensity to a log-scale (base 10) resulted in a higher overall discrimination power while observing the same significance level. Working on the log-scale, the nonparametric permutation tests gave an overall 89.83% discrimination power with a size of Type I error being 4.44% at the nominal significance level of 5%. White paint samples, as a group, were the most difficult to differentiate with the power being only 86.56% followed by 95.83% for black paint samples. Parametric analysis of the data set produced lower discrimination (85.17%) with 3.33% Type I errors, which is not recommended for both theoretical and practical considerations. The nonparametric testing method is applicable across many analytical comparisons, with the specific application described here being the pairwise comparison of automotive paint samples.

Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

Science.gov (United States)

Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

2017-06-30

Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

Science.gov (United States)

Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437

A 67-Item Stress Resilience item bank showing high content validity was developed in a psychosomatic sample.

Science.gov (United States)

Obbarius, Nina; Fischer, Felix; Obbarius, Alexander; Nolte, Sandra; Liegl, Gregor; Rose, Matthias

2018-04-10

To develop the first item bank to measure Stress Resilience (SR) in clinical populations. Qualitative item development resulted in an initial pool of 131 items covering a broad theoretical SR concept. These items were tested in n=521 patients at a psychosomatic outpatient clinic. Exploratory and Confirmatory Factor Analysis (CFA), as well as other state-of-the-art item analyses and IRT were used for item evaluation and calibration of the final item bank. Out of the initial item pool of 131 items, we excluded 64 items (54 factor loading .3, 2 non-discriminative Item Response Curves, 4 Differential Item Functioning). The final set of 67 items indicated sufficient model fit in CFA and IRT analyses. Additionally, a 10-item short form with high measurement precision (SE≤.32 in a theta range between -1.8 and +1.5) was derived. Both the SR item bank and the SR short form were highly correlated with an existing static legacy tool (Connor-Davidson Resilience Scale). The final SR item bank and 10-item short form showed good psychometric properties. When further validated, they will be ready to be used within a framework of Computer-Adaptive Tests for a comprehensive assessment of the Stress-Construct. Copyright © 2018. Published by Elsevier Inc.

An emotional functioning item bank of 24 items for computerized adaptive testing (CAT) was established

DEFF Research Database (Denmark)

Petersen, Morten Aa.; Gamper, Eva-Maria; Costantini, Anna

2016-01-01

of the widely used EORTC Quality of Life questionnaire (QLQ-C30). STUDY DESIGN AND SETTING: On the basis of literature search and evaluations by international samples of experts and cancer patients, 38 candidate items were developed. The psychometric properties of the items were evaluated in a large...... international sample of cancer patients. This included evaluations of dimensionality, item response theory (IRT) model fit, differential item functioning (DIF), and of measurement precision/statistical power. RESULTS: Responses were obtained from 1,023 cancer patients from four countries. The evaluations showed...... that 24 items could be included in a unidimensional IRT model. DIF did not seem to have any significant impact on the estimation of EF. Evaluations indicated that the CAT measure may reduce sample size requirements by up to 50% compared to the QLQ-C30 EF scale without reducing power. CONCLUSION...

Network structure exploration via Bayesian nonparametric models

International Nuclear Information System (INIS)

Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

2015-01-01

Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.

Science.gov (United States)

Teixeira, Ana P; Clemente, João J; Cunha, António E; Carrondo, Manuel J T; Oliveira, Rui

2006-01-01

This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin

2017-01-19

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

2017-01-01

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

Nonparametric methods for volatility density estimation

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2009-01-01

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

Quantal Response: Nonparametric Modeling

Science.gov (United States)

2017-01-01

capture the behavior of observed phenomena. Higher-order polynomial and finite-dimensional spline basis models allow for more complicated responses as the...flexibility as these are nonparametric (not constrained to any particular functional form). These should be useful in identifying nonstandard behavior via... deviance ∆ = −2 log(Lreduced/Lfull) is defined in terms of the likelihood function L. For normal error, Lfull = 1, and based on Eq. A-2, we have log

Speaker Linking and Applications using Non-Parametric Hashing Methods

Science.gov (United States)

2016-09-08

nonparametric estimate of a multivariate density function,” The Annals of Math- ematical Statistics , vol. 36, no. 3, pp. 1049–1051, 1965. [9] E. A. Patrick...Speaker Linking and Applications using Non-Parametric Hashing Methods† Douglas Sturim and William M. Campbell MIT Lincoln Laboratory, Lexington, MA...with many approaches [1, 2]. For this paper, we focus on using i-vectors [2], but the methods apply to any embedding. For the task of speaker QBE and

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

Science.gov (United States)

Park, Saerom; Lee, Jaewook; Son, Youngdoo

2016-01-01

Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

A symptom profile of depression among Asian Americans: is there evidence for differential item functioning of depressive symptoms?

Science.gov (United States)

Kalibatseva, Z; Leong, F T L; Ham, E H

2014-09-01

Theoretical and clinical publications suggest the existence of cultural differences in the expression and experience of depression. Measurement non-equivalence remains a potential methodological explanation for the lower prevalence of depression among Asian Americans compared to European Americans. This study compared DSM-IV depressive symptoms among Asian Americans and European Americans using secondary data analysis of the Collaborative Psychiatric Epidemiology Surveys (CPES). The Composite International Diagnostic Interview (CIDI) was used for the assessment of depressive symptoms. Of the entire sample, 310 Asian Americans and 1974 European Americans reported depressive symptoms and were included in the analyses. Measurement variance was examined with an item response theory differential item functioning (IRT DIF) analysis. χ2 analyses indicated that, compared to Asian Americans, European American participants more frequently endorsed affective symptoms such as 'feeling depressed', 'feeling discouraged' and 'cried more often'. The IRT analysis detected DIF for four out of the 15 depression symptom items. At equal levels of depression, Asian Americans endorsed feeling worthless and appetite changes more easily than European Americans, and European Americans endorsed feeling nervous and crying more often than Asian Americans. Asian Americans did not seem to over-report somatic symptoms; however, European Americans seemed to report more affective symptoms than Asian Americans. The results suggest that there was measurement variance in a few of the depression items.

Testing for constant nonparametric effects in general semiparametric regression models with interactions

KAUST Repository

Wei, Jiawei; Carroll, Raymond J.; Maity, Arnab

2011-01-01

We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work

UN ANÁLISIS NO PARAMÉTRICO DE ÍTEMS DE LA PRUEBA DEL BENDER/A NONPARAMETRIC ITEM ANALYSIS OF THE BENDER GESTALT TEST MODIFIED

Directory of Open Access Journals (Sweden)

César Merino Soto

2009-05-01

Full Text Available Resumen:La presente investigación hace un estudio psicométrico de un nuevo sistema de calificación de la Prueba Gestáltica del Bendermodificada para niños, que es el Sistema de Calificación Cualitativa (Brannigan y Brunner, 2002, en un muestra de 244 niñosingresantes a primer grado de primaria en cuatro colegios públicos, ubicados en Lima. El enfoque usado es un análisis noparamétrico de ítems mediante el programa Testgraf (Ramsay, 1991. Los resultados indican niveles apropiados deconsistencia interna, identificándose la unidimensionalidad, y el buen nivel discriminativo de las categorías de calificación deeste Sistema Cualitativo. No se hallaron diferencias demográficas respecto al género ni la edad. Se discuten los presenteshallazgos en el contexto del potencial uso del Sistema de Calificación Cualitativa y del análisis no paramétrico de ítems en lainvestigación psicométrica.AbstracThis research designs a psychometric study of a new scoring system of the Bender Gestalt test modified to children: it is theQualitative Scoring System (Brannigan & Brunner, 2002, in a sample of 244 first grade children of primary level, in four public school of Lima. The approach aplied is the nonparametric item analysis using The test graft computer program (Ramsay, 1991. Our findings point to good levels of internal consistency, unidimensionality and good discriminative level ofthe categories of scoring from the Qualitative Scoring System. There are not demographic differences between gender or age.We discuss our findings within the context of the potential use of the Qualitative Scoring System and of the nonparametricitem analysis approach in the psychometric research.

Nonparametric statistical inference

CERN Document Server

Gibbons, Jean Dickinson

2014-01-01

Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

Non-Parametric Estimation of Correlation Functions

DEFF Research Database (Denmark)

Brincker, Rune; Rytter, Anders; Krenk, Steen

In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...

Application of nonparametric statistic method for DNBR limit calculation

International Nuclear Information System (INIS)

Dong Bo; Kuang Bo; Zhu Xuenong

2013-01-01

Background: Nonparametric statistical method is a kind of statistical inference method not depending on a certain distribution; it calculates the tolerance limits under certain probability level and confidence through sampling methods. The DNBR margin is one important parameter of NPP design, which presents the safety level of NPP. Purpose and Methods: This paper uses nonparametric statistical method basing on Wilks formula and VIPER-01 subchannel analysis code to calculate the DNBR design limits (DL) of 300 MW NPP (Nuclear Power Plant) during the complete loss of flow accident, simultaneously compared with the DL of DNBR through means of ITDP to get certain DNBR margin. Results: The results indicate that this method can gain 2.96% DNBR margin more than that obtained by ITDP methodology. Conclusions: Because of the reduction of the conservation during analysis process, the nonparametric statistical method can provide greater DNBR margin and the increase of DNBR margin is benefited for the upgrading of core refuel scheme. (authors)

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

Directory of Open Access Journals (Sweden)

Saerom Park

Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

Science.gov (United States)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

A review of the effects on IRT item parameter estimates with a focus on misbehaving common items in test equating

Directory of Open Access Journals (Sweden)

Michalis P Michaelides

2010-10-01

Full Text Available Many studies have investigated the topic of change or drift in item parameter estimates in the context of Item Response Theory. Content effects, such as instructional variation and curricular emphasis, as well as context effects, such as the wording, position, or exposure of an item have been found to impact item parameter estimates. The issue becomes more critical when items with estimates exhibiting differential behavior across test administrations are used as common for deriving equating transformations. This paper reviews the types of effects on IRT item parameter estimates and focuses on the impact of misbehaving or aberrant common items on equating transformations. Implications relating to test validity and the judgmental nature of the decision to keep or discard aberrant common items are discussed, with recommendations for future research into more informed and formal ways of dealing with misbehaving common items.

A Review of the Effects on IRT Item Parameter Estimates with a Focus on Misbehaving Common Items in Test Equating.

Science.gov (United States)

Michaelides, Michalis P

2010-01-01

Many studies have investigated the topic of change or drift in item parameter estimates in the context of item response theory (IRT). Content effects, such as instructional variation and curricular emphasis, as well as context effects, such as the wording, position, or exposure of an item have been found to impact item parameter estimates. The issue becomes more critical when items with estimates exhibiting differential behavior across test administrations are used as common for deriving equating transformations. This paper reviews the types of effects on IRT item parameter estimates and focuses on the impact of misbehaving or aberrant common items on equating transformations. Implications relating to test validity and the judgmental nature of the decision to keep or discard aberrant common items are discussed, with recommendations for future research into more informed and formal ways of dealing with misbehaving common items.

Multi-sample nonparametric treatments comparison in medical ...

African Journals Online (AJOL)

Multi-sample nonparametric treatments comparison in medical follow-up study with unequal observation processes through simulation and bladder tumour case study. P. L. Tan, N.A. Ibrahim, M.B. Adam, J. Arasan ...

Nonparametric regression using the concept of minimum energy

International Nuclear Information System (INIS)

Williams, Mike

2011-01-01

It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

Robust estimation for ordinary differential equation models.

Science.gov (United States)

Cao, J; Wang, L; Xu, J

2011-12-01

Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.

Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

Science.gov (United States)

Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

2013-04-01

In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

Modeling animal movements using stochastic differential equations

Science.gov (United States)

Haiganoush K. Preisler; Alan A. Ager; Bruce K. Johnson; John G. Kie

2004-01-01

We describe the use of bivariate stochastic differential equations (SDE) for modeling movements of 216 radiocollared female Rocky Mountain elk at the Starkey Experimental Forest and Range in northeastern Oregon. Spatially and temporally explicit vector fields were estimated using approximating difference equations and nonparametric regression techniques. Estimated...

Essays on nonparametric econometrics of stochastic volatility

NARCIS (Netherlands)

Zu, Y.

2012-01-01

Volatility is a concept that describes the variation of financial returns. Measuring and modelling volatility dynamics is an important aspect of financial econometrics. This thesis is concerned with nonparametric approaches to volatility measurement and volatility model validation.

Non-parametric Tuning of PID Controllers A Modified Relay-Feedback-Test Approach

CERN Document Server

Boiko, Igor

2013-01-01

The relay feedback test (RFT) has become a popular and efficient  tool used in process identification and automatic controller tuning. Non-parametric Tuning of PID Controllers couples new modifications of classical RFT with application-specific optimal tuning rules to form a non-parametric method of test-and-tuning. Test and tuning are coordinated through a set of common parameters so that a PID controller can obtain the desired gain or phase margins in a system exactly, even with unknown process dynamics. The concept of process-specific optimal tuning rules in the nonparametric setup, with corresponding tuning rules for flow, level pressure, and temperature control loops is presented in the text.   Common problems of tuning accuracy based on parametric and non-parametric approaches are addressed. In addition, the text treats the parametric approach to tuning based on the modified RFT approach and the exact model of oscillations in the system under test using the locus of a perturbedrelay system (LPRS) meth...

A Psychometric Evaluation of the DSM-IV Criteria for Antisocial Personality Disorder: Dimensionality, Local Reliability, and Differential Item Functioning Across Gender.

Science.gov (United States)

Paap, Muirne C S; Braeken, Johan; Pedersen, Geir; Urnes, Øyvind; Karterud, Sigmund; Wilberg, Theresa; Hummelen, Benjamin

2017-12-01

This study aims at evaluating the psychometric properties of the antisocial personality disorder (ASPD) criteria in a large sample of patients, most of whom had one or more personality disorders (PD). PD diagnoses were assessed by experienced clinicians using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Axis II PDs. Analyses were performed within an item response theory framework. Results of the analyses indicated that ASPD is a unidimensional construct that can be measured reliably at the upper range of the latent trait scale. Differential item functioning across gender was restricted to two criteria and had little impact on the latent ASPD trait level. Patients fulfilling both the adult ASPD criteria and the conduct disorder criteria had similar latent trait distributions as patients fulfilling only the adult ASPD criteria. Overall, the ASPD items fit the purpose of a diagnostic instrument well, that is, distinguishing patients with moderate from those with high antisocial personality scores.

Nonparametric Bayes Modeling of Multivariate Categorical Data.

Science.gov (United States)

Dunson, David B; Xing, Chuanhua

2012-01-01

Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.

Dissociating the neural correlates of intra-item and inter-item working-memory binding.

Directory of Open Access Journals (Sweden)

Carinne Piekema

Full Text Available BACKGROUND: Integration of information streams into a unitary representation is an important task of our cognitive system. Within working memory, the medial temporal lobe (MTL has been conceptually linked to the maintenance of bound representations. In a previous fMRI study, we have shown that the MTL is indeed more active during working-memory maintenance of spatial associations as compared to non-spatial associations or single items. There are two explanations for this result, the mere presence of the spatial component activates the MTL, or the MTL is recruited to bind associations between neurally non-overlapping representations. METHODOLOGY/PRINCIPAL FINDINGS: The current fMRI study investigates this issue further by directly comparing intrinsic intra-item binding (object/colour, extrinsic intra-item binding (object/location, and inter-item binding (object/object. The three binding conditions resulted in differential activation of brain regions. Specifically, we show that the MTL is important for establishing extrinsic intra-item associations and inter-item associations, in line with the notion that binding of information processed in different brain regions depends on the MTL. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that different forms of working-memory binding rely on specific neural structures. In addition, these results extend previous reports indicating that the MTL is implicated in working-memory maintenance, challenging the classic distinction between short-term and long-term memory systems.

Nonparametric predictive inference in statistical process control

NARCIS (Netherlands)

Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

2000-01-01

New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on

Nonparametric instrumental regression with non-convex constraints

International Nuclear Information System (INIS)

Grasmair, M; Scherzer, O; Vanhems, A

2013-01-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition. (paper)

Nonparametric instrumental regression with non-convex constraints

Science.gov (United States)

Grasmair, M.; Scherzer, O.; Vanhems, A.

2013-03-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

Nonparametric conditional predictive regions for time series

NARCIS (Netherlands)

de Gooijer, J.G.; Zerom Godefay, D.

2000-01-01

Several nonparametric predictors based on the Nadaraya-Watson kernel regression estimator have been proposed in the literature. They include the conditional mean, the conditional median, and the conditional mode. In this paper, we consider three types of predictive regions for these predictors — the

Nonparametric e-Mixture Estimation.

Science.gov (United States)

Takano, Ken; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

2016-12-01

This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these auxiliary distributions-in other words, approximating the target distribution in a subspace spanned by a set of auxiliary distributions. Mixture modeling is one of the simplest ways to integrate information from the target and auxiliary distributions in order to express the target distribution as accurately as possible. There are two typical mixtures in the context of information geometry: the [Formula: see text]- and [Formula: see text]-mixtures. The [Formula: see text]-mixture is applied in a variety of research fields because of the presence of the well-known expectation-maximazation algorithm for parameter estimation, whereas the [Formula: see text]-mixture is rarely used because of its difficulty of estimation, particularly for nonparametric models. The [Formula: see text]-mixture, however, is a well-tempered distribution that satisfies the principle of maximum entropy. To model a target distribution with scarce observations accurately, this letter proposes a novel framework for a nonparametric modeling of the [Formula: see text]-mixture and a geometrically inspired estimation algorithm. As numerical examples of the proposed framework, a transfer learning setup is considered. The experimental results show that this framework works well for three types of synthetic data sets, as well as an EEG real-world data set.

Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot

Science.gov (United States)

Magis, David; Facon, Bruno

2013-01-01

Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…

Screen Wars, Star Wars, and Sequels: Nonparametric Reanalysis of Movie Profitability

OpenAIRE

W. D. Walls

2012-01-01

In this paper we use nonparametric statistical tools to quantify motion-picture profit. We quantify the unconditional distribution of profit, the distribution of profit conditional on stars and sequels, and we also model the conditional expectation of movie profits using a non- parametric data-driven regression model. The flexibility of the non-parametric approach accommodates the full range of possible relationships among the variables without prior specification of a functional form, thereb...

Nonparametric predictive inference in reliability

International Nuclear Information System (INIS)

Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.

2002-01-01

We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere

Nonparametric estimation in models for unobservable heterogeneity

OpenAIRE

Hohmann, Daniel

2014-01-01

Nonparametric models which allow for data with unobservable heterogeneity are studied. The first publication introduces new estimators and their asymptotic properties for conditional mixture models. The second publication considers estimation of a function from noisy observations of its Radon transform in a Gaussian white noise model.

Nonparametric estimation of location and scale parameters

KAUST Repository

Potgieter, C.J.; Lombard, F.

2012-01-01

Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal

A Bayesian Nonparametric Approach to Factor Analysis

DEFF Research Database (Denmark)

Piatek, Rémi; Papaspiliopoulos, Omiros

2018-01-01

This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

Panel data specifications in nonparametric kernel regression

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

Cross-cultural and sex differences in the Emotional Skills and Competence Questionnaire scales: Challenges of differential item functioning analyses

Directory of Open Access Journals (Sweden)

Bo Molander

2009-11-01

Full Text Available University students in Croatia, Slovenia, and Sweden (N = 1129 were examined by means of the Emotional Skills and Competence Questionnaire (Takšić, 1998. Results showed a significant effect for the sex factor only on the total-score scale, women scoring higher than men, but significant effects were obtained for country, as well as for sex, on the Express and Label (EL and Perceive and Understand (PU subscales. Sweden showed higher scores than Croatia and Slovenia on the EL scale, and Slovenia showed higher scores than Croatia and Sweden on the PU scale. In subsequent analyses of differential item functioning (DIF, comparisons were carried out for pairs of countries. The analyses revealed that a large proportion of the items in the total-score scale were potentially biased, most so for the Croatian-Swedish comparison, less for the Slovenian-Swedish comparison, and least for the Croatian-Slovenian comparison. These findings give doubts about the validity of mean score differences in comparisons of countries. However, DIF analyses of sex differences within each country show very few DIF items, indicating that the ESCQ instrument works well within each cultural/linguistic setting. Possible explanations of the findings are discussed, and improvements for future studies are suggested.

Analysis of Nonequivalent Assessments across Different Linguistic Groups Using a Mixed Methods Approach: Understanding the Causes of Differential Item Functioning by Cognitive Interviewing

Science.gov (United States)

Benítez, Isabel; Padilla, José-Luis

2014-01-01

Differential item functioning (DIF) can undermine the validity of cross-lingual comparisons. While a lot of efficient statistics for detecting DIF are available, few general findings have been found to explain DIF results. The objective of the article was to study DIF sources by using a mixed method design. The design involves a quantitative phase…

Examination of the PROMIS upper extremity item bank.

Science.gov (United States)

Hung, Man; Voss, Maren W; Bounsanga, Jerry; Crum, Anthony B; Tyser, Andrew R

Clinical measurement. The psychometric properties of the PROMIS v1.2 UE item bank were tested on various samples prior to its release, but have not been fully evaluated among the orthopaedic population. This study assesses the performance of the UE item bank within the UE orthopaedic patient population. The UE item bank was administered to 1197 adult patients presenting to a tertiary orthopaedic clinic specializing in hand and UE conditions and was examined using traditional statistics and Rasch analysis. The UE item bank fits a unidimensional model (outfit MNSQ range from 0.64 to 1.70) and has adequate reliabilities (person = 0.84; item = 0.82) and local independence (item residual correlations range from -0.37 to 0.34). Only one item exhibits gender differential item functioning. Most items target low levels of function. The UE item bank is a useful clinical assessment tool. Additional items covering higher functions are needed to enhance validity. Supplemental testing is recommended for patients at higher levels of function until more high function UE items are developed. 2c. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

An item response theory analysis of Harter's Self-Perception Profile for children or why strong clinical scales should be distrusted.

Science.gov (United States)

Egberink, Iris J L; Meijer, Rob R

2011-06-01

The authors investigated the psychometric properties of the subscales of the Self-Perception Profile for Children with item response theory (IRT) models using a sample of 611 children. Results from a nonparametric Mokken analysis and a parametric IRT approach for boys (n = 268) and girls (n = 343) were compared. The authors found that most scales formed weak scales and that measurement precision was relatively low and only present for latent trait values indicating low self-perception. The subscales Physical Appearance and Global Self-Worth formed one strong scale. Children seem to interpret Global Self-Worth items as if they measure Physical Appearance. Furthermore, the authors found that strong Mokken scales (such as Global Self-Worth) consisted mostly of items that repeat the same item content. They conclude that researchers should be very careful in interpreting the total scores on the different Self-Perception Profile for Children scales. Finally, implications for further research are discussed.

The emotional memory effect: differential processing or item distinctiveness?

Science.gov (United States)

Schmidt, Stephen R; Saari, Bonnie

2007-12-01

A color-naming task was followed by incidental free recall to investigate how emotional words affect attention and memory. We compared taboo, nonthreatening negative-affect, and neutral words across three experiments. As compared with neutral words, taboo words led to longer color-naming times and better memory in both within- and between-subjects designs. Color naming of negative-emotion nontaboo words was slower than color naming of neutral words only during block presentation and at relatively short interstimulus intervals (ISIs). The nontaboo emotion words were remembered better than neutral words following blocked and random presentation and at both long and short ISIs, but only in mixed-list designs. Our results support multifactor theories of the effects of emotion on attention and memory. As compared with neutral words, threatening stimuli received increased attention, poststimulus elaboration, and benefit from item distinctiveness, whereas nonthreatening emotional stimuli benefited only from increased item distinctiveness.

Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

OpenAIRE

Hiroyuki Kasahara; Katsumi Shimotsu

2006-01-01

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

Development of a brief version of the Social Phobia Inventory using item response theory: the Mini-SPIN-R.

Science.gov (United States)

Aderka, Idan M; Pollack, Mark H; Simon, Naomi M; Smits, Jasper A J; Van Ameringen, Michael; Stein, Murray B; Hofmann, Stefan G

2013-12-01

The Social Phobia Inventory (SPIN) is a widely used measure in mental health settings and a 3-item version (mini-SPIN) has been developed as a screening instrument for social anxiety disorder. In the present study, we examined the psychometric properties of the SPIN and developed a brief version (mini-SPIN-R) designed to assess social anxiety severity using item response theory. Our sample included 569 individuals with social anxiety disorder who participated in 2 clinical trials and filled out a battery of self-report measures. Using a nonparametric kernel smoothing method we identified the most sensitive items of the SPIN. These 3 items comprised the mini-SPIN-R, which was found to have greater internal consistency, and to capture a greater range of symptoms compared to the mini-SPIN. The mini-SPIN-R evidenced superior convergent validity compared to the mini-SPIN and both measures had similar divergent validity. Thus, the mini-SPIN-R is a promising brief measure of social anxiety severity. Copyright © 2013. Published by Elsevier Ltd.

Quality of life in infants and children with atopic dermatitis: Addressing issues of differential item functioning across countries in multinational clinical trials

Directory of Open Access Journals (Sweden)

Tennant Alan

2007-07-01

Full Text Available Abstract Background A previous study had identified 45 items assessing the impact of atopic dermatitis (AD on the whole family. From these it was intended to develop two separate scales, one assessing impact on carers and the other determining the effect on the child. Methods The 45 items were included in three clinical trials designed to test the efficacy of a new topical treatment (pimecrolimus, Elidel cream 1% in the treatment of AD in infants and children and in validation studies in the UK, US, Germany, France and the Netherlands. Rasch analyses were undertaken to determine whether an internationally valid, unidimensional scale could be developed that would inform on the direct impact of AD on the child. Results Rasch analyses applied to the data from the trials indicated that the draft measure consisted of two scales, one assessing the QoL of the carer and the other (consisting of 12 items measuring the impact of AD on the child. Three of the 12 potential items failed to fit the measurement model in Europe and five in the US. In addition, four items exhibiting differential item functioning (DIF by country were identified. After removing the misfitting items and controlling for DIF it was possible to derive a scale; The Childhood Impact of Atopic Dermatitis (CIAD with good item fit for each trial analysis. Analysis of the validation data from each of the different countries confirmed that the CIAD had adequate internal consistency, reproducibility and construct validity. The CIAD demonstrated the benefits of treatment with Elidel over placebo in the European trial. A similar (non-significant trend was found for the US trials. Conclusion The study represents a novel method of dealing with the problem of DIF associated with different cultures. Such problems are likely to arise in any multinational study involving patient-reported outcome measures, as items in the scales are likely to be valued differently in different cultures. However, where

Multivariate nonparametric regression and visualization with R and applications to finance

CERN Document Server

Klemelä, Jussi

2014-01-01

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functio

Using non-parametric methods in econometric production analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

2012-01-01

by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...

Nonparametric Bayesian density estimation on manifolds with applications to planar shapes.

Science.gov (United States)

Bhattacharya, Abhishek; Dunson, David B

2010-12-01

Statistical analysis on landmark-based shape spaces has diverse applications in morphometrics, medical diagnostics, machine vision and other areas. These shape spaces are non-Euclidean quotient manifolds. To conduct nonparametric inferences, one may define notions of centre and spread on this manifold and work with their estimates. However, it is useful to consider full likelihood-based methods, which allow nonparametric estimation of the probability density. This article proposes a broad class of mixture models constructed using suitable kernels on a general compact metric space and then on the planar shape space in particular. Following a Bayesian approach with a nonparametric prior on the mixing distribution, conditions are obtained under which the Kullback-Leibler property holds, implying large support and weak posterior consistency. Gibbs sampling methods are developed for posterior computation, and the methods are applied to problems in density estimation and classification with shape-based predictors. Simulation studies show improved estimation performance relative to existing approaches.

Cross-cultural differences in knee functional status outcomes in a polyglot society represented true disparities not biased by differential item functioning.

Science.gov (United States)

Deutscher, Daniel; Hart, Dennis L; Crane, Paul K; Dickstein, Ruth

2010-12-01

Comparative effectiveness research across cultures requires unbiased measures that accurately detect clinical differences between patient groups. The purpose of this study was to assess the presence and impact of differential item functioning (DIF) in knee functional status (FS) items administered using computerized adaptive testing (CAT) as a possible cause for observed differences in outcomes between 2 cultural patient groups in a polyglot society. This study was a secondary analysis of prospectively collected data. We evaluated data from 9,134 patients with knee impairments from outpatient physical therapy clinics in Israel. Items were analyzed for DIF related to sex, age, symptom acuity, surgical history, exercise history, and language used to complete the functional survey (Hebrew versus Russian). Several items exhibited DIF, but unadjusted FS estimates and FS estimates that accounted for DIF were essentially equal (intraclass correlation coefficient [2,1]>.999). No individual patient had a difference between unadjusted and adjusted FS estimates as large as the median standard error of the unadjusted estimates. Differences between groups defined by any of the covariates considered were essentially unchanged when using adjusted instead of unadjusted FS estimates. The greatest group-level impact was <0.3% of 1 standard deviation of the unadjusted FS estimates. Complete data where patients answered all items in the scale would have been preferred for DIF analysis, but only CAT data were available. Differences in FS outcomes between groups of patients with knee impairments who answered the knee CAT in Hebrew or Russian in Israel most likely reflected true differences that may reflect societal disparities in this health outcome.

Bayesian nonparametric system reliability using sets of priors

NARCIS (Netherlands)

Walter, G.M.; Aslett, L.J.M.; Coolen, F.P.A.

2016-01-01

An imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through bounds on the functioning probability. Given component level test

Examining Differential Math Performance by Gender and Opportunity to Learn

Science.gov (United States)

Albano, Anthony D.; Rodriguez, Michael C.

2013-01-01

Although a substantial amount of research has been conducted on differential item functioning in testing, studies have focused on detecting differential item functioning rather than on explaining how or why it may occur. Some recent work has explored sources of differential functioning using explanatory and multilevel item response models. This…

Teaching Nonparametric Statistics Using Student Instrumental Values.

Science.gov (United States)

Anderson, Jonathan W.; Diddams, Margaret

Nonparametric statistics are often difficult to teach in introduction to statistics courses because of the lack of real-world examples. This study demonstrated how teachers can use differences in the rankings and ratings of undergraduate and graduate values to discuss: (1) ipsative and normative scaling; (2) uses of the Mann-Whitney U-test; and…

Testing for constant nonparametric effects in general semiparametric regression models with interactions

KAUST Repository

Wei, Jiawei

2011-07-01

We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.

Use of differential item functioning (DIF analysis for bias analysis in test construction

Directory of Open Access Journals (Sweden)

Marié De Beer

2004-10-01

Opsomming Waar differensiële itemfunksioneringsprosedures (DIF-prosedures vir itemontleding gebaseer op itemresponsteorie (IRT tydens toetskonstruksie gebruik word, is dit moontlik om itemkarakteristiekekrommes vir dieselfde item vir verskillende subgroepe voor te stel. Hierdie krommes dui aan hoe elke item vir die verskillende subgroepe op verskillende vermoënsvlakke te funksioneer. DIF word aangetoon deur die area tussen die krommes. DIF is in die konstruksie van die 'Learning Potential Computerised Adaptive test (LPCAT' gebruik om die items te identifiseer wat sydigheid ten opsigte van geslag, kultuur, taal of opleidingspeil geopenbaar het. Items wat ’n voorafbepaalde vlak van DIF oorskry het, is uit die finale itembank weggelaat, ongeag die subgroep wat bevoordeel of benadeel is. Die proses en resultate van die DIF-ontleding word bespreek.

Smooth semi-nonparametric (SNP) estimation of the cumulative incidence function.

Science.gov (United States)

Duc, Anh Nguyen; Wolbers, Marcel

2017-08-15

This paper presents a novel approach to estimation of the cumulative incidence function in the presence of competing risks. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and the time to the event. The time to event distributions conditional on the event type are modeled using smooth semi-nonparametric densities. One strength of this approach is that it can handle arbitrary censoring and truncation while relying on mild parametric assumptions. A stepwise forward algorithm for model estimation and adaptive selection of smooth semi-nonparametric polynomial degrees is presented, implemented in the statistical software R, evaluated in a sequence of simulation studies, and applied to data from a clinical trial in cryptococcal meningitis. The simulations demonstrate that the proposed method frequently outperforms both parametric and nonparametric alternatives. They also support the use of 'ad hoc' asymptotic inference to derive confidence intervals. An extension to regression modeling is also presented, and its potential and challenges are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest.

Science.gov (United States)

Spencer, Mercedes; Cho, Sun-Joo; Cutting, Laurie E

2018-02-02

In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.

Validation of a mobility item bank for older patients in primary care.

Science.gov (United States)

Cabrero-García, Julio; Ramos-Pichardo, Juan Diego; Muñoz-Mendoza, Carmen Luz; Cabañero-Martínez, María José; González-Llopis, Lorena; Reig-Ferrer, Abilio

2012-12-05

To develop and validate an item bank to measure mobility in older people in primary care and to analyse differential item functioning (DIF) and differential bundle functioning (DBF) by sex. A pool of 48 mobility items was administered by interview to 593 older people attending primary health care practices. The pool contained four domains based on the International Classification of Functioning: changing and maintaining body position, carrying, lifting and pushing, walking and going up and down stairs. The Late Life Mobility item bank consisted of 35 items, and measured with a reliability of 0.90 or more across the full spectrum of mobility, except at the higher end of better functioning. No evidence was found of non-uniform DIF but uniform DIF was observed, mainly for items in the changing and maintaining body position and carrying, lifting and pushing domains. The walking domain did not display DBF, but the other three domains did, principally the carrying, lifting and pushing items. During the design and validation of an item bank to measure mobility in older people, we found that strength (carrying, lifting and pushing) items formed a secondary dimension that produced DBF. More research is needed to determine how best to include strength items in a mobility measure, or whether it would be more appropriate to design separate measures for each construct.

Nonparametric identification of copula structures

KAUST Repository

Li, Bo

2013-06-01

We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process.We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particularly when the sample size is moderately large. We illustrate our testing approach on two datasets. © 2013 American Statistical Association.

Detecting DIF in Polytomous Items Using MACS, IRT and Ordinal Logistic Regression

Science.gov (United States)

Elosua, Paula; Wells, Craig

2013-01-01

The purpose of the present study was to compare the Type I error rate and power of two model-based procedures, the mean and covariance structure model (MACS) and the item response theory (IRT), and an observed-score based procedure, ordinal logistic regression, for detecting differential item functioning (DIF) in polytomous items. A simulation…

Differential item functioning of pathological gambling criteria: an examination of gender, race/ethnicity, and age.

Science.gov (United States)

Sacco, Paul; Torres, Luis R; Cunningham-Williams, Renee M; Woods, Carol; Unick, G Jay

2011-06-01

This study tested for the presence of differential item functioning (DIF) in DSM-IV Pathological Gambling Disorder (PGD) criteria based on gender, race/ethnicity and age. Using a nationally representative sample of adults from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), indicating current gambling (n = 10,899), Multiple Indicator-Multiple Cause (MIMIC) models tested for DIF, controlling for income, education, and marital status. Compared to the reference groups (i.e., Male, Caucasian, and ages 25-59 years), women (OR = 0.62; P gambling to escape (Criterion 5) (OR = 2.22; P < .001) but young adults (OR = 0.62; P < .05) were less likely to endorse it. African Americans (OR = 2.50; P < .001) and Hispanics were more likely to endorse trying to cut back (Criterion 3) (OR = 2.01; P < .01). African Americans were more likely to endorse the suffering losses (OR = 2.27; P < .01) criterion. Young adults were more likely to endorse chasing losses (Criterion 9) (OR = 1.81; P < .01) while older adults were less likely to endorse this criterion (OR = 0.76; P < .05). Further research is needed to identify factors contributing to DIF, address criteria level bias, and examine differential test functioning.

The nonparametric bootstrap for the current status model

NARCIS (Netherlands)

Groeneboom, P.; Hendrickx, K.

2017-01-01

It has been proved that direct bootstrapping of the nonparametric maximum likelihood estimator (MLE) of the distribution function in the current status model leads to inconsistent confidence intervals. We show that bootstrapping of functionals of the MLE can however be used to produce valid

The Dif Identification in Constructed Response Items Using Partial Credit Model

OpenAIRE

Heri Retnawati

2017-01-01

The study was to identify the load, the type and the significance of differential item functioning (DIF) in constructed response item using the partial credit model (PCM). The data in the study were the students’ instruments and the students’ responses toward the PISA-like test items that had been completed by 386 ninth grade students and 460 tenth grade students who had been about 15 years old in the Province of Yogyakarta Special Region in Indonesia. The analysis toward the item characteris...

Psychometric analysis of the Generalized Anxiety Disorder scale (GAD-7) in primary care using modern item response theory.

Science.gov (United States)

Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

2017-01-01

The Generalized Anxiety Disorder scale (GAD-7) is one of the most frequently used diagnostic self-report scales for screening, diagnosis and severity assessment of anxiety disorder. Its psychometric properties from the view of the Item Response Theory paradigm have rarely been investigated. We aimed to close this gap by analyzing the GAD-7 within a large sample of primary care patients with respect to its psychometric properties and its implications for scoring using Item Response Theory. Robust, nonparametric statistics were used to check unidimensionality of the GAD-7. A graded response model was fitted using a Bayesian approach. The model fit was evaluated using posterior predictive p-values, item information functions were derived and optimal predictions of anxiety were calculated. The sample included N = 3404 primary care patients (60% female; mean age, 52,2; standard deviation 19.2) The analysis indicated no deviations of the GAD-7 scale from unidimensionality and a decent fit of a graded response model. The commonly suggested ultra-brief measure consisting of the first two items, the GAD-2, was supported by item information analysis. The first four items discriminated better than the last three items with respect to latent anxiety. The information provided by the first four items should be weighted more heavily. Moreover, estimates corresponding to low to moderate levels of anxiety show greater variability. The psychometric validity of the GAD-2 was supported by our analysis.

Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

Directory of Open Access Journals (Sweden)

Biqing Cai

2015-04-01

Full Text Available This paper discusses nonparametric kernel regression with the regressor being a \\(d\\-dimensional \\(\\beta\\-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \\(\\sqrt{n(Th^{d}}\\, where \\(n(T\\ is the number of regenerations for a \\(\\beta\\-null recurrent process and the limiting distribution (with proper normalization is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent. The finite sample performance of the estimate is quite reasonable when the leave-one-out cross validation method is used for bandwidth selection. We apply the proposed method to study the relationship of Federal funds rate with 3-month and 5-year T-bill rates and discover the existence of nonlinearity of the relationship. Furthermore, the in-sample and out-of-sample performance of the nonparametric model is far better than the linear model.

A Bayesian nonparametric estimation of distributions and quantiles

International Nuclear Information System (INIS)

Poern, K.

1988-11-01

The report describes a Bayesian, nonparametric method for the estimation of a distribution function and its quantiles. The method, presupposing random sampling, is nonparametric, so the user has to specify a prior distribution on a space of distributions (and not on a parameter space). In the current application, where the method is used to estimate the uncertainty of a parametric calculational model, the Dirichlet prior distribution is to a large extent determined by the first batch of Monte Carlo-realizations. In this case the results of the estimation technique is very similar to the conventional empirical distribution function. The resulting posterior distribution is also Dirichlet, and thus facilitates the determination of probability (confidence) intervals at any given point in the space of interest. Another advantage is that also the posterior distribution of a specified quantitle can be derived and utilized to determine a probability interval for that quantile. The method was devised for use in the PROPER code package for uncertainty and sensitivity analysis. (orig.)

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

Science.gov (United States)

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

Fitting a Mixture Rasch Model to English as a Foreign Language Listening Tests: The Role of Cognitive and Background Variables in Explaining Latent Differential Item Functioning

Science.gov (United States)

Aryadoust, Vahid

2015-01-01

The present study uses a mixture Rasch model to examine latent differential item functioning in English as a foreign language listening tests. Participants (n = 250) took a listening and lexico-grammatical test and completed the metacognitive awareness listening questionnaire comprising problem solving (PS), planning and evaluation (PE), mental…

A nonparametric empirical Bayes framework for large-scale multiple testing.

Science.gov (United States)

Martin, Ryan; Tokdar, Surya T

2012-07-01

We propose a flexible and identifiable version of the 2-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the nonnull cases. We use a computationally efficient predictive recursion (PR) marginal likelihood procedure to estimate the model parameters, even the nonparametric mixing distribution. This leads to a nonparametric empirical Bayes testing procedure, which we call PRtest, based on thresholding the estimated local false discovery rates. Simulations and real data examples demonstrate that, compared to existing approaches, PRtest's careful handling of the nonnull density can give a much better fit in the tails of the mixture distribution which, in turn, can lead to more realistic conclusions.

5 CFR 591.212 - How does OPM select survey items?

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false How does OPM select survey items? 591.212 Section 591.212 Administrative Personnel OFFICE OF PERSONNEL MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas Cost-Of-Living...

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study.

Science.gov (United States)

Lix, Lisa M; Wu, Xiuyun; Hopman, Wilma; Mayo, Nancy; Sajobi, Tolulope T; Liu, Juxin; Prior, Jerilynn C; Papaioannou, Alexandra; Josse, Robert G; Towheed, Tanveer E; Davison, K Shawn; Sawatzky, Richard

2016-01-01

Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36), can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF), which arises when population sub-groups with the same underlying (i.e., latent) level of health have different measured item response probabilities, may compromise the comparability of these measures. The purpose of this study was to test for DIF on the SF-36 physical functioning (PF) and mental health (MH) sub-scale items in a Canadian population-based sample. Study data were from the prospective Canadian Multicentre Osteoporosis Study (CaMos), which collected baseline data in 1996-1997. DIF was tested using a multiple indicators multiple causes (MIMIC) method. Confirmatory factor analysis defined the latent variable measurement model for the item responses and latent variable regression with demographic and health status covariates (i.e., sex, age group, body weight, self-perceived general health) produced estimates of the magnitude of DIF effects. The CaMos cohort consisted of 9423 respondents; 69.4% were female and 51.7% were less than 65 years. Eight of 10 items on the PF sub-scale and four of five items on the MH sub-scale exhibited DIF. Large DIF effects were observed on PF sub-scale items about vigorous and moderate activities, lifting and carrying groceries, walking one block, and bathing or dressing. On the MH sub-scale items, all DIF effects were small or moderate in size. SF-36 PF and MH sub-scale scores were not comparable across population sub-groups defined by demographic and health status variables due to the effects of DIF, although the magnitude of this bias was not large for most items. We recommend testing and adjusting for DIF to ensure comparability of the SF-36 in population-based investigations.

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study.

Directory of Open Access Journals (Sweden)

Lisa M Lix

Full Text Available Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36, can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF, which arises when population sub-groups with the same underlying (i.e., latent level of health have different measured item response probabilities, may compromise the comparability of these measures. The purpose of this study was to test for DIF on the SF-36 physical functioning (PF and mental health (MH sub-scale items in a Canadian population-based sample.Study data were from the prospective Canadian Multicentre Osteoporosis Study (CaMos, which collected baseline data in 1996-1997. DIF was tested using a multiple indicators multiple causes (MIMIC method. Confirmatory factor analysis defined the latent variable measurement model for the item responses and latent variable regression with demographic and health status covariates (i.e., sex, age group, body weight, self-perceived general health produced estimates of the magnitude of DIF effects.The CaMos cohort consisted of 9423 respondents; 69.4% were female and 51.7% were less than 65 years. Eight of 10 items on the PF sub-scale and four of five items on the MH sub-scale exhibited DIF. Large DIF effects were observed on PF sub-scale items about vigorous and moderate activities, lifting and carrying groceries, walking one block, and bathing or dressing. On the MH sub-scale items, all DIF effects were small or moderate in size.SF-36 PF and MH sub-scale scores were not comparable across population sub-groups defined by demographic and health status variables due to the effects of DIF, although the magnitude of this bias was not large for most items. We recommend testing and adjusting for DIF to ensure comparability of the SF-36 in population-based investigations.

Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure

DEFF Research Database (Denmark)

Effraimidis, Georgios; Dahl, Christian Møller

In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric...

Gender differences in national assessment of educational progress science items: What does i don't know really mean?

Science.gov (United States)

Linn, Marcia C.; de Benedictis, Tina; Delucchi, Kevin; Harris, Abigail; Stage, Elizabeth

The National Assessment of Educational Progress Science Assessment has consistently revealed small gender differences on science content items but not on science inquiry items. This assessment differs from others in that respondents can choose I don't know rather than guessing. This paper examines explanations for the gender differences including (a) differential prior instruction, (b) differential response to uncertainty and use of the I don't know response, (c) differential response to figurally presented items, and (d) different attitudes towards science. Of these possible explanations, the first two received support. Females are more likely to use the I don't know response, especially for items with physical science content or masculine themes such as football. To ameliorate this situation we need more effective science instruction and more gender-neutral assessment items.

Bayesian Non-Parametric Mixtures of GARCH(1,1 Models

Directory of Open Access Journals (Sweden)

John W. Lau

2012-01-01

Full Text Available Traditional GARCH models describe volatility levels that evolve smoothly over time, generated by a single GARCH regime. However, nonstationary time series data may exhibit abrupt changes in volatility, suggesting changes in the underlying GARCH regimes. Further, the number and times of regime changes are not always obvious. This article outlines a nonparametric mixture of GARCH models that is able to estimate the number and time of volatility regime changes by mixing over the Poisson-Kingman process. The process is a generalisation of the Dirichlet process typically used in nonparametric models for time-dependent data provides a richer clustering structure, and its application to time series data is novel. Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. The methodology is illustrated on the Standard and Poor's 500 financial index.

Single versus mixture Weibull distributions for nonparametric satellite reliability

International Nuclear Information System (INIS)

Castet, Jean-Francois; Saleh, Joseph H.

2010-01-01

Long recognized as a critical design attribute for space systems, satellite reliability has not yet received the proper attention as limited on-orbit failure data and statistical analyses can be found in the technical literature. To fill this gap, we recently conducted a nonparametric analysis of satellite reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we provide an advanced parametric fit, based on mixture of Weibull distributions, and compare it with the single Weibull distribution model obtained with the Maximum Likelihood Estimation (MLE) method. We demonstrate that both parametric fits are good approximations of the nonparametric satellite reliability, but that the mixture Weibull distribution provides significant accuracy in capturing all the failure trends in the failure data, as evidenced by the analysis of the residuals and their quasi-normal dispersion.

Modern nonparametric, robust and multivariate methods festschrift in honour of Hannu Oja

CERN Document Server

Taskinen, Sara

2015-01-01

Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

NARCIS (Netherlands)

Kuosmanen, T.K.

2005-01-01

Environmental Economics and Natural Resources Group at Wageningen University in The Netherlands Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion.

Psychometric properties of the Triarchic Psychopathy Measure: An item response theory approach.

Science.gov (United States)

Shou, Yiyun; Sellbom, Martin; Xu, Jing

2018-05-01

There is cumulative evidence for the cross-cultural validity of the Triarchic Psychopathy Measure (TriPM; Patrick, 2010) among non-Western populations. Recent studies using correlational and regression analyses show promising construct validity of the TriPM in Chinese samples. However, little is known about the efficiency of items in TriPM in assessing the proposed latent traits. The current study evaluated the psychometric properties of the Chinese TriPM at the item level using item response theory analyses. It also examined the measurement invariance of the TriPM between the Chinese and the U.S. student samples by applying differential item functioning analyses under the item response theory framework. The results supported the unidimensional nature of the Disinhibition and Meanness scales. Both scales had a greater level of precision in the respective underlying constructs at the positive ends. The two scales, however, had several items that were weakly associated with their respective latent traits in the Chinese student sample. Boldness, on the other hand, was found to be multidimensional, and reflected a more normally distributed range of variation. The examination of measurement bias via differential item functioning analyses revealed that a number of items of the TriPM were not equivalent across the Chinese and the U.S. Some modification and adaptation of items might be considered for improving the precision of the TriPM for Chinese participants. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Brief Report: Checklist for Autism Spectrum Disorder--Most Discriminating Items for Diagnosing Autism

Science.gov (United States)

Mayes, Susan D.

2018-01-01

The smallest subset of items from the 30-item Checklist for Autism Spectrum Disorder (CASD) that differentiated 607 referred children (3-17 years) with and without autism with 100% accuracy was identified. This 6-item subset (CASD-Short Form) was cross-validated on an independent sample of 397 referred children (1-18 years) with and without autism…

Factor Structure and Reliability of Test Items for Saudi Teacher Licence Assessment

Science.gov (United States)

Alsadaawi, Abdullah Saleh

2017-01-01

The Saudi National Assessment Centre administers the Computer Science Teacher Test for teacher certification. The aim of this study is to explore gender differences in candidates' scores, and investigate dimensionality, reliability, and differential item functioning using confirmatory factor analysis and item response theory. The confirmatory…

Non-Parametric Analysis of Rating Transition and Default Data

DEFF Research Database (Denmark)

Fledelius, Peter; Lando, David; Perch Nielsen, Jens

2004-01-01

We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...

Adaptive nonparametric Bayesian inference using location-scale mixture priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2010-01-01

We study location-scale mixture priors for nonparametric statistical problems, including multivariate regression, density estimation and classification. We show that a rate-adaptive procedure can be obtained if the prior is properly constructed. In particular, we show that adaptation is achieved if

Non-parametric analysis of production efficiency of poultry egg ...

African Journals Online (AJOL)

Non-parametric analysis of production efficiency of poultry egg farmers in Delta ... analysis of factors affecting the output of poultry farmers showed that stock ... should be put in place for farmers to learn the best farm practices carried out on the ...

A Nonparametric Bayesian Approach For Emission Tomography Reconstruction

International Nuclear Information System (INIS)

Barat, Eric; Dautremer, Thomas

2007-01-01

We introduce a PET reconstruction algorithm following a nonparametric Bayesian (NPB) approach. In contrast with Expectation Maximization (EM), the proposed technique does not rely on any space discretization. Namely, the activity distribution--normalized emission intensity of the spatial poisson process--is considered as a spatial probability density and observations are the projections of random emissions whose distribution has to be estimated. This approach is nonparametric in the sense that the quantity of interest belongs to the set of probability measures on R k (for reconstruction in k-dimensions) and it is Bayesian in the sense that we define a prior directly on this spatial measure. In this context, we propose to model the nonparametric probability density as an infinite mixture of multivariate normal distributions. As a prior for this mixture we consider a Dirichlet Process Mixture (DPM) with a Normal-Inverse Wishart (NIW) model as base distribution of the Dirichlet Process. As in EM-family reconstruction, we use a data augmentation scheme where the set of hidden variables are the emission locations for each observed line of response in the continuous object space. Thanks to the data augmentation, we propose a Markov Chain Monte Carlo (MCMC) algorithm (Gibbs sampler) which is able to generate draws from the posterior distribution of the spatial intensity. A difference with EM is that one step of the Gibbs sampler corresponds to the generation of emission locations while only the expected number of emissions per pixel/voxel is used in EM. Another key difference is that the estimated spatial intensity is a continuous function such that there is no need to compute a projection matrix. Finally, draws from the intensity posterior distribution allow the estimation of posterior functionnals like the variance or confidence intervals. Results are presented for simulated data based on a 2D brain phantom and compared to Bayesian MAP-EM

International Conference on Robust Rank-Based and Nonparametric Methods

CERN Document Server

McKean, Joseph

2016-01-01

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

Bayesian nonparametric dictionary learning for compressed sensing MRI.

Science.gov (United States)

Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

2014-12-01

We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

Assessment of Preference for Edible and Leisure Items in Individuals with Dementia

Science.gov (United States)

Ortega, Javier Virues; Iwata, Brian A.; Nogales-Gonzalez, Celia; Frades, Belen

2012-01-01

We conducted 2 studies on reinforcer preference in patients with dementia. Results of preference assessments yielded differential selections by 14 participants. Unlike prior studies with individuals with intellectual disabilities, all participants showed a noticeable preference for leisure items over edible items. Results of a subsequent analysis…

A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

Directory of Open Access Journals (Sweden)

Archer Kellie J

2008-02-01

Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

Comparing nonparametric Bayesian tree priors for clonal reconstruction of tumors.

Science.gov (United States)

Deshwar, Amit G; Vembu, Shankar; Morris, Quaid

2015-01-01

Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors. Here we describe the treeCRP, an extension of the Chinese restaurant process (CRP), a popular construction used in nonparametric mixture models, to infer the phylogeny and genotype of major subclonal lineages represented in the population of cancer cells. We also propose new split-merge updates tailored to the subclonal reconstruction problem that improve the mixing time of Markov chains. In comparisons with the tree-structured stick breaking prior used in PhyloSub, we demonstrate superior mixing and running time using the treeCRP with our new split-merge procedures. We also show that given the same number of samples, TSSB and treeCRP have similar ability to recover the subclonal structure of a tumor…

Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

Directory of Open Access Journals (Sweden)

Xin Tian

2017-06-01

Full Text Available We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online. Clustering is introduced for dictionary learning. A set of dictionaries could be generated, and each dictionary is used for one cluster’s sparse coding. In this way, the signals in one cluster could be well represented by their corresponding dictionaries. A nonparametric Bayesian dictionary learning method is used to learn the dictionaries, which naturally infers an appropriate dictionary size for each cluster. A uniform quantizer and an adaptive arithmetic coding algorithm are adopted to code the sparse coefficients. With comparisons to other state-of-the art approaches, the effectiveness of the proposed method could be validated in the experiments.

The processing of inter-item relations as a moderating factor of retrieval-induced forgetting

OpenAIRE

Tempel, Tobias; Wippich, Werner

2012-01-01

We investigated influences of item generation and emotional valence on retrieval-induced forgetting. Drawing on postulates of the three-factor theory of generation effects, generation tasks differentially affecting the processing of inter-item relations were applied. Whereas retrieval-induced forgetting of freely generated items was moderated by the emotional valence as well as retrieval-induced forgetting of read items, even though in the reverse direction (Experiment 1), fragment completion...

Decompounding random sums: A nonparametric approach

DEFF Research Database (Denmark)

Hansen, Martin Bøgsted; Pitts, Susan M.

Observations from sums of random variables with a random number of summands, known as random, compound or stopped sums arise within many areas of engineering and science. Quite often it is desirable to infer properties of the distribution of the terms in the random sum. In the present paper we...... review a number of applications and consider the nonlinear inverse problem of inferring the cumulative distribution function of the components in the random sum. We review the existing literature on non-parametric approaches to the problem. The models amenable to the analysis are generalized considerably...

Exploring differential item functioning (DIF) with the Rasch model: a comparison of gender differences on eighth grade science items in the United States and Spain.

Science.gov (United States)

Babiar, Tasha Calvert

2011-01-01

Traditionally, women and minorities have not been fully represented in science and engineering. Numerous studies have attributed these differences to gaps in science achievement as measured by various standardized tests. Rather than describe mean group differences in science achievement across multiple cultures, this study focused on an in-depth item-level analysis across two countries: Spain and the United States. This study investigated eighth-grade gender differences on science items across the two countries. A secondary purpose of the study was to explore the nature of gender differences using the many-faceted Rasch Model as a way to estimate gender DIF. A secondary analysis of data from the Third International Mathematics and Science Study (TIMSS) was used to address three questions: 1) Does gender DIF in science achievement exist? 2) Is there a relationship between gender DIF and characteristics of the science items? 3) Do the relationships between item characteristics and gender DIF in science items replicate across countries. Participants included 7,087 eight grade students from the United States and 3,855 students from Spain who participated in TIMSS. The Facets program (Linacre and Wright, 1992) was used to estimate gender DIF. The results of the analysis indicate that the content of the item seemed to be related to gender DIF. The analysis also suggests that there is a relationship between gender DIF and item format. No pattern of gender DIF related to cognitive demand was found. The general pattern of gender DIF was similar across the two countries used in the analysis. The strength of item-level analysis as opposed to group mean difference analysis is that gender differences can be detected at the item level, even when no mean differences can be detected at the group level.

Nonparametric modeling of dynamic functional connectivity in fmri data

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus

2015-01-01

dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...

Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

Czech Academy of Sciences Publication Activity Database

Kalina, Jan; Zvárová, Jana

2017-01-01

Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

Science.gov (United States)

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

The MIMIC Model as a Tool for Differential Bundle Functioning Detection

Science.gov (United States)

Finch, W. Holmes

2012-01-01

Increasingly, researchers interested in identifying potentially biased test items are encouraged to use a confirmatory, rather than exploratory, approach. One such method for confirmatory testing is rooted in differential bundle functioning (DBF), where hypotheses regarding potential differential item functioning (DIF) for sets of items (bundles)…

Compreensão da leitura: análise do funcionamento diferencial dos itens de um Teste de Cloze Reading comprehension: differential item functioning analysis of a Cloze Test

Directory of Open Access Journals (Sweden)

Katya Luciane Oliveira

2012-01-01

Full Text Available Este estudo teve por objetivos investigar o ajuste de um Teste de Cloze ao modelo Rasch e avaliar a dificuldade na resposta ao item em razão do gênero das pessoas (DIF. Participaram da pesquisa 573 alunos das 5ª a 8ª séries do ensino fundamental de escolas públicas estaduais dos estados de São Paulo e Minas Gerais. O teste de Cloze foi aplicado de forma coletiva. A análise do instrumento evidenciou um bom ajuste ao modelo Rasch, bem como os itens foram respondidos conforme o padrão esperado, demonstrando um bom ajuste, também. Quanto ao DIF, apenas três itens indicaram diferenciar o gênero. Com base nos dados, identificou-se que houve equilíbrio nas respostas dadas pelos meninos e meninas.The objectives of the present study were to investigate the adaptation of a Cloze test to the Rasch Model as well as to evaluate the Differential Item Functioning (DIF in relation to gender. The sample was composed by 573 students from 5th to 8th grades of public schools in the state of São Paulo. The cloze test was applied collectively. The analysis of the instrument revealed its adaptation to Rash Model and that the items were responded according to the expected pattern, showing good adjustment, as well. Regarding DIF, only three items were differentiated by gender. Based on the data, results indicated a balance in the answers given by boys and girls.

Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

Science.gov (United States)

Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

Nonparametric Mixture of Regression Models.

Science.gov (United States)

Huang, Mian; Li, Runze; Wang, Shaoli

2013-07-01

Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

Item Response Theory Analyses of the Cambridge Face Memory Test (CFMT)

Science.gov (United States)

Cho, Sun-Joo; Wilmer, Jeremy; Herzmann, Grit; McGugin, Rankin; Fiset, Daniel; Van Gulick, Ana E.; Ryan, Katie; Gauthier, Isabel

2014-01-01

We evaluated the psychometric properties of the Cambridge face memory test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bi-factor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and three specific factors clustered by targets of CFMT. However, the three specific factors appeared to be minor factors that can be ignored. Second, we fit a unidimensional item response model. This item response model showed that the CFMT items could discriminate individuals at different ability levels and covered a wide range of the ability continuum. We found the CFMT to be particularly precise for a wide range of ability levels. Third, we implemented item response theory (IRT) differential item functioning (DIF) analyses for each gender group and two age groups (Age ≤ 20 versus Age > 21). This DIF analysis suggested little evidence of consequential differential functioning on the CFMT for these groups, supporting the use of the test to compare older to younger, or male to female, individuals. Fourth, we tested for a gender difference on the latent facial recognition ability with an explanatory item response model. We found a significant but small gender difference on the latent ability for face recognition, which was higher for women than men by 0.184, at age mean 23.2, controlling for linear and quadratic age effects. Finally, we discuss the practical considerations of the use of total scores versus IRT scale scores in applications of the CFMT. PMID:25642930

Item Response Theory Applied to Factors Affecting the Patient Journey Towards Hearing Rehabilitation

Science.gov (United States)

Chenault, Michelene; Berger, Martijn; Kremer, Bernd; Anteunis, Lucien

2016-01-01

To develop a tool for use in hearing screening and to evaluate the patient journey towards hearing rehabilitation, responses to the hearing aid rehabilitation questionnaire scales aid stigma, pressure, and aid unwanted addressing respectively hearing aid stigma, experienced pressure from others; perceived hearing aid benefit were evaluated with item response theory. The sample was comprised of 212 persons aged 55 years or more; 63 were hearing aid users, 64 with and 85 persons without hearing impairment according to guidelines for hearing aid reimbursement in the Netherlands. Bias was investigated relative to hearing aid use and hearing impairment within the differential test functioning framework. Items compromising model fit or demonstrating differential item functioning were dropped. The aid stigma scale was reduced from 6 to 4, the pressure scale from 7 to 4, and the aid unwanted scale from 5 to 4 items. This procedure resulted in bias-free scales ready for screening purposes and application to further understand the help-seeking process of the hearing impaired. PMID:28028428

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology

Directory of Open Access Journals (Sweden)

Mohamed Chikhi

2018-02-01

Full Text Available This paper analyses cyclical behaviour of Orange stock price listed in French stock exchange over 01/03/2000 to 02/02/2017 by testing the nonlinearities through a class of conditional heteroscedastic nonparametric models. The linearity and Gaussianity assumptions are rejected for Orange Stock returns and informational shocks have transitory effects on returns and volatility. The forecasting results show that Orange stock prices are short-term predictable and nonparametric NAR-ARCH model has better performance over parametric MA-APARCH model for short horizons. Plus, the estimates of this model are also better comparing to the predictions of the random walk model. This finding provides evidence for weak form of inefficiency in Paris stock market with limited rationality, thus it emerges arbitrage opportunities.

Gender Differences in Figural Matrices: The Moderating Role of Item Design Features

Science.gov (United States)

Arendasy, Martin E.; Sommer, Markus

2012-01-01

There is a heated debate on whether observed gender differences in some figural matrices in adults can be attributed to gender differences in inductive reasoning/G[subscript f] or differential item functioning and/or test bias. Based on previous studies we hypothesized that three specific item design features moderate the effect size of the gender…

On the robust nonparametric regression estimation for a functional regressor

OpenAIRE

Azzedine , Nadjia; Laksaci , Ali; Ould-Saïd , Elias

2009-01-01

On the robust nonparametric regression estimation for a functional regressor correspondance: Corresponding author. (Ould-Said, Elias) (Azzedine, Nadjia) (Laksaci, Ali) (Ould-Said, Elias) Departement de Mathematiques--> , Univ. Djillali Liabes--> , BP 89--> , 22000 Sidi Bel Abbes--> - ALGERIA (Azzedine, Nadjia) Departement de Mathema...

Bayesian Nonparametric Clustering for Positive Definite Matrices.

Science.gov (United States)

Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2016-05-01

Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used. As is well-known, these algorithms need the number of clusters to be specified, which is difficult when the dataset scales. To address this issue, we resort to the classical nonparametric Bayesian framework by modeling the data as a mixture model using the Dirichlet process (DP) prior. Since these matrices do not conform to the Euclidean geometry, rather belongs to a curved Riemannian manifold,existing DP models cannot be directly applied. Thus, in this paper, we propose a novel DP mixture model framework for SPD matrices. Using the log-determinant divergence as the underlying dissimilarity measure to compare these matrices, and further using the connection between this measure and the Wishart distribution, we derive a novel DPM model based on the Wishart-Inverse-Wishart conjugate pair. We apply this model to several applications in computer vision. Our experiments demonstrate that our model is scalable to the dataset size and at the same time achieves superior accuracy compared to several state-of-the-art parametric and nonparametric clustering algorithms.

A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data.

Science.gov (United States)

Hu, Pingsha; Maiti, Tapabrata

2011-01-01

Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships. We present a non-parametric mean-variance smoothing method (NPMVS) to analyze differentially expressed genes. In this method, a nonlinear smoothing curve is fitted to estimate the relationship between mean and variance. Inference is then made upon shrinkage estimation of posterior means assuming variances are known. Different methods have been applied to simulated datasets, in which a variety of mean and variance relationships were imposed. The simulation study showed that NPMVS outperformed the other two popular shrinkage estimation methods in some mean-variance relationships; and NPMVS was competitive with the two methods in other relationships. A real biological dataset, in which a cold stress transcription factor gene, CBF2, was overexpressed, has also been analyzed with the three methods. Gene ontology and cis-element analysis showed that NPMVS identified more cold and stress responsive genes than the other two methods did. The good performance of NPMVS is mainly due to its shrinkage estimation for both means and variances. In addition, NPMVS exploits a non-parametric regression between mean and variance, instead of assuming a specific parametric relationship between mean and variance. The source code written in R is available from the authors on request.

Nonparametric decision tree: The impact of ISO 9000 on certified and non certified companies Nonparametric decision tree: The impact of ISO 9000 on certified and non certified companies Nonparametric decision tree: The impact of ISO 9000 on certified and non certified companies

Directory of Open Access Journals (Sweden)

Joaquín Texeira Quirós

2013-09-01

Full Text Available Purpose: This empirical study analyzes a questionnaire answered by a sample of ISO 9000 certified companies and a control sample of companies which have not been certified, using a multivariate predictive model. With this approach, we assess which quality practices are associated to the likelihood of the firm being certified. Design/methodology/approach: We implemented nonparametric decision trees, in order to see which variables influence more the fact that the company be certified or not, i.e., the motivations that lead companies to make sure. Findings: The results show that only four questionnaire items are sufficient to predict if a firm is certified or not. It is shown that companies in which the respondent manifests greater concern with respect to customers relations; motivations of the employees and strategic planning have higher likelihood of being certified. Research implications: the reader should note that this study is based on data from a single country and, of course, these results capture many idiosyncrasies if its economic and corporate environment. It would be of interest to understand if this type of analysis reveals some regularities across different countries. Practical implications: companies should look for a set of practices congruent with total quality management and ISO 9000 certified. Originality/value: This study contributes to the literature on the internal motivation of companies to achieve certification under the ISO 9000 standard, by performing a comparative analysis of questionnaires answered by a sample of certified companies and a control sample of companies which have not been certified. In particular, we assess how the manager’s perception on the intensity in which quality practices are deployed in their firms is associated to the likelihood of the firm being certified.Purpose: This empirical study analyzes a questionnaire answered by a sample of ISO 9000 certified companies and a control sample of companies

Semiparametric mixed-effects analysis of PK/PD models using differential equations.

Science.gov (United States)

Wang, Yi; Eskridge, Kent M; Zhang, Shunpu

2008-08-01

Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new semiparametric modeling approach to address potential structural model misspecification for population pharmacokinetic/pharmacodynamic (PK/PD) analysis. Specifically, we use a set of ordinary differential equations (ODEs) with form dx/dt = A(t)x + B(t) where B(t) is a nonparametric function that is estimated using penalized splines. The inclusion of a nonparametric function in the ODEs makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies. The resulting model will be implemented in a nonlinear mixed-effects modeling setup for population analysis. We illustrate the method with an application to cefamandole data and evaluate its performance through simulations.

Nonparametric combinatorial sequence models.

Science.gov (United States)

Wauthier, Fabian L; Jordan, Michael I; Jojic, Nebojsa

2011-11-01

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three biological sequence families which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution over sequence representations induced by the prior. By integrating out the posterior, our method compares favorably to leading binding predictors.

Non-parametric production analysis of pesticides use in the Netherlands

NARCIS (Netherlands)

Oude Lansink, A.G.J.M.; Silva, E.

2004-01-01

Many previous empirical studies on the productivity of pesticides suggest that pesticides are under-utilized in agriculture despite the general held believe that these inputs are substantially over-utilized. This paper uses data envelopment analysis (DEA) to calculate non-parametric measures of the

Item Response Theory Analysis of the Psychopathic Personality Inventory-Revised.

Science.gov (United States)

Eichenbaum, Alexander E; Marcus, David K; French, Brian F

2017-06-01

This study examined item and scale functioning in the Psychopathic Personality Inventory-Revised (PPI-R) using an item response theory analysis. PPI-R protocols from 1,052 college student participants (348 male, 704 female) were analyzed. Analyses were conducted on the 131 self-report items comprising the PPI-R's eight content scales, using a graded response model. Scales collected a majority of their information about respondents possessing higher than average levels of the traits being measured. Each scale contained at least some items that evidenced limited ability to differentiate between respondents with differing levels of the trait being measured. Moreover, 80 items (61.1%) yielded significantly different responses between men and women presumably possessing similar levels of the trait being measured. Item performance was also influenced by the scoring format (directly scored vs. reverse-scored) of the items. Overall, the results suggest that the PPI-R, despite identifying psychopathic personality traits in individuals possessing high levels of those traits, may not identify these traits equally well for men and women, and scores are likely influenced by the scoring format of the individual item and scale.

Genomic breeding value estimation using nonparametric additive regression models

Directory of Open Access Journals (Sweden)

Solberg Trygve

2009-01-01

Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

DEFF Research Database (Denmark)

Høg, Esben

In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

DEFF Research Database (Denmark)

Høg, Esben

2003-01-01

In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

Science.gov (United States)

Yau, Christopher; Holmes, Chris

2011-07-01

We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

Item validity vs. item discrimination index: a redundancy?

Science.gov (United States)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.

Using response-time constraints in item selection to control for differential speededness in computerized adaptive testing

NARCIS (Netherlands)

van der Linden, Willem J.; Scrams, David J.; Schnipke, Deborah L.

2003-01-01

This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has

Development and Evaluation of the PROMIS® Pediatric Positive Affect Item Bank, Child-Report and Parent-Proxy Editions.

Science.gov (United States)

Forrest, Christopher B; Ravens-Sieberer, Ulrike; Devine, Janine; Becker, Brandon D; Teneralli, Rachel; Moon, JeanHee; Carle, Adam; Tucker, Carole A; Bevans, Katherine B

2018-03-01

The purpose of this study is to describe the psychometric evaluation and item response theory calibration of the PROMIS Pediatric Positive Affect item bank, child-report and parent-proxy editions. The initial item pool comprising 53 items, previously developed using qualitative methods, was administered to 1,874 children 8-17 years old and 909 parents of children 5-17 years old. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning, and construct validity. A total of 14 items were deleted, because of poor psychometric performance, and an 8-item short form constructed from the remaining 39 items was administered to a national sample of 1,004 children 8-17 years old, and 1,306 parents of children 5-17 years old. The combined sample was used in item response theory (IRT) calibration analyses. The final item bank appeared unidimensional, the items appeared locally independent, and the items were free from differential item functioning. The scales showed excellent reliability and convergent and discriminant validity. Positive affect decreased with children's age and was lower for those with a special health care need. After IRT calibration, we found that 4 and 8 item short forms had a high degree of precision (reliability) across a wide range of the latent trait (>4 SD units). The PROMIS Pediatric Positive Affect item bank and its short forms provide an efficient, precise, and valid assessment of positive affect in children and youth.

A Nonparametric Test for Seasonal Unit Roots

OpenAIRE

Kunst, Robert M.

2009-01-01

Abstract: We consider a nonparametric test for the null of seasonal unit roots in quarterly time series that builds on the RUR (records unit root) test by Aparicio, Escribano, and Sipols. We find that the test concept is more promising than a formalization of visual aids such as plots by quarter. In order to cope with the sensitivity of the original RUR test to autocorrelation under its null of a unit root, we suggest an augmentation step by autoregression. We present some evidence on the siz...

NONPARAMETRIC FIXED EFFECT PANEL DATA MODELS: RELATIONSHIP BETWEEN AIR POLLUTION AND INCOME FOR TURKEY

Directory of Open Access Journals (Sweden)

Rabia Ece OMAY

2013-06-01

Full Text Available In this study, relationship between gross domestic product (GDP per capita and sulfur dioxide (SO2 and particulate matter (PM10 per capita is modeled for Turkey. Nonparametric fixed effect panel data analysis is used for the modeling. The panel data covers 12 territories, in first level of Nomenclature of Territorial Units for Statistics (NUTS, for period of 1990-2001. Modeling of the relationship between GDP and SO2 and PM10 for Turkey, the non-parametric models have given good results.

Developing an immigration policy for Germany on the basis of a nonparametric labor market classification

OpenAIRE

Froelich, Markus; Puhani, Patrick

2004-01-01

Based on a nonparametrically estimated model of labor market classifications, this paper makes suggestions for immigration policy using data from western Germany in the 1990s. It is demonstrated that nonparametric regression is feasible in higher dimensions with only a few thousand observations. In sum, labor markets able to absorb immigrants are characterized by above average age and by professional occupations. On the other hand, labor markets for young workers in service occupations are id...

A comparative study of non-parametric models for identification of ...

African Journals Online (AJOL)

However, the frequency response method using random binary signals was good for unpredicted white noise characteristics and considered the best method for non-parametric system identifica-tion. The autoregressive external input (ARX) model was very useful for system identification, but on applicati-on, few input ...

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

1st Conference of the International Society for Nonparametric Statistics

CERN Document Server

Lahiri, S; Politis, Dimitris

2014-01-01

This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for NonParametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI, and other organizations. M.G. Akritas, S.N. Lahiri, and D.N. Politis are the first executive committee members of ISNPS, and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao, and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world.   The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the wo...

On Parametric (and Non-Parametric Variation

Directory of Open Access Journals (Sweden)

Neil Smith

2009-11-01

Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.

Item response theory applied to factors affecting the patient journey towards hearing rehabilitation

Directory of Open Access Journals (Sweden)

Michelene Chenault

2016-11-01

Full Text Available To develop a tool for use in hearing screening and to evaluate the patient journey towards hearing rehabilitation, responses to the hearing aid rehabilitation questionnaire scales aid stigma, pressure, and aid unwanted addressing respectively hearing aid stigma, experienced pressure from others; perceived hearing aid benefit were evaluated with item response theory. The sample was comprised of 212 persons aged 55 years or more; 63 were hearing aid users, 64 with and 85 persons without hearing impairment according to guidelines for hearing aid reimbursement in the Netherlands. Bias was investigated relative to hearing aid use and hearing impairment within the differential test functioning framework. Items compromising model fit or demonstrating differential item functioning were dropped. The aid stigma scale was reduced from 6 to 4, the pressure scale from 7 to 4, and the aid unwanted scale from 5 to 4 items. This procedure resulted in bias-free scales ready for screening purposes and application to further understand the help-seeking process of the hearing impaired.

Non-parametric estimation of the individual's utility map

OpenAIRE

Noguchi, Takao; Sanborn, Adam N.; Stewart, Neil

2013-01-01

Models of risky choice have attracted much attention in behavioural economics. Previous research has repeatedly demonstrated that individuals' choices are not well explained by expected utility theory, and a number of alternative models have been examined using carefully selected sets of choice alternatives. The model performance however, can depend on which choice alternatives are being tested. Here we develop a non-parametric method for estimating the utility map over the wide range of choi...

Nonparametric Bayesian models through probit stick-breaking processes.

Science.gov (United States)

Rodríguez, Abel; Dunson, David B

2011-03-01

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology.

Glaucoma Monitoring in a Clinical Setting Glaucoma Progression Analysis vs Nonparametric Progression Analysis in the Groningen Longitudinal Glaucoma Study

NARCIS (Netherlands)

Wesselink, Christiaan; Heeg, Govert P.; Jansonius, Nomdo M.

Objective: To compare prospectively 2 perimetric progression detection algorithms for glaucoma, the Early Manifest Glaucoma Trial algorithm (glaucoma progression analysis [GPA]) and a nonparametric algorithm applied to the mean deviation (MD) (nonparametric progression analysis [NPA]). Methods:

A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models.

Science.gov (United States)

Fronczyk, Kassandra; Kottas, Athanasios

2014-03-01

We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature. © 2013, The International Biometric Society.

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Science.gov (United States)

Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

2011-05-01

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

Kernel bandwidth estimation for non-parametric density estimation: a comparative study

CSIR Research Space (South Africa)

Van der Walt, CM

2013-12-01

Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...

A general approach to posterior contraction in nonparametric inverse problems

NARCIS (Netherlands)

Knapik, Bartek; Salomond, Jean Bernard

In this paper, we propose a general method to derive an upper bound for the contraction rate of the posterior distribution for nonparametric inverse problems. We present a general theorem that allows us to derive contraction rates for the parameter of interest from contraction rates of the related

The Dif Identification in Constructed Response Items Using Partial Credit Model

Directory of Open Access Journals (Sweden)

Heri Retnawati

2017-10-01

Full Text Available The study was to identify the load, the type and the significance of differential item functioning (DIF in constructed response item using the partial credit model (PCM. The data in the study were the students’ instruments and the students’ responses toward the PISA-like test items that had been completed by 386 ninth grade students and 460 tenth grade students who had been about 15 years old in the Province of Yogyakarta Special Region in Indonesia. The analysis toward the item characteristics through the student categorization based on their class was conducted toward the PCM using CONQUEST software. Furthermore, by applying these items characteristics, the researcher draw the category response function (CRF graphic in order to identify whether the type of DIF content had been in uniform or non-uniform. The significance of DIF was identified by comparing the discrepancy between the difficulty level parameter and the error in the CONQUEST output results. The results of the analysis showed that from 18 items that had been analyzed there were 4 items which had not been identified load DIF, there were 5 items that had been identified containing DIF but not statistically significant and there were 9 items that had been identified containing DIF significantly. The causes of items containing DIF were discussed.

A comparison of parametric and nonparametric methods for normalising cDNA microarray data.

Science.gov (United States)

Khondoker, Mizanur R; Glasbey, Chris A; Worton, Bruce J

2007-12-01

Normalisation is an essential first step in the analysis of most cDNA microarray data, to correct for effects arising from imperfections in the technology. Loess smoothing is commonly used to correct for trends in log-ratio data. However, parametric models, such as the additive plus multiplicative variance model, have been preferred for scale normalisation, though the variance structure of microarray data may be of a more complex nature than can be accommodated by a parametric model. We propose a new nonparametric approach that incorporates location and scale normalisation simultaneously using a Generalised Additive Model for Location, Scale and Shape (GAMLSS, Rigby and Stasinopoulos, 2005, Applied Statistics, 54, 507-554). We compare its performance in inferring differential expression with Huber et al.'s (2002, Bioinformatics, 18, 96-104) arsinh variance stabilising transformation (AVST) using real and simulated data. We show GAMLSS to be as powerful as AVST when the parametric model is correct, and more powerful when the model is wrong. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Application of Item Response Theory to Tests of Substance-related Associative Memory

Science.gov (United States)

Shono, Yusuke; Grenard, Jerry L.; Ames, Susan L.; Stacy, Alan W.

2015-01-01

A substance-related word association test (WAT) is one of the commonly used indirect tests of substance-related implicit associative memory and has been shown to predict substance use. This study applied an item response theory (IRT) modeling approach to evaluate psychometric properties of the alcohol- and marijuana-related WATs and their items among 775 ethnically diverse at-risk adolescents. After examining the IRT assumptions, item fit, and differential item functioning (DIF) across gender and age groups, the original 18 WAT items were reduced to 14- and 15-items in the alcohol- and marijuana-related WAT, respectively. Thereafter, unidimensional one- and two-parameter logistic models (1PL and 2PL models) were fitted to the revised WAT items. The results demonstrated that both alcohol- and marijuana-related WATs have good psychometric properties. These results were discussed in light of the framework of a unified concept of construct validity (Messick, 1975, 1989, 1995). PMID:25134051

Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures.

Science.gov (United States)

Filippi, Sarah; Holmes, Chris C; Nieto-Barajas, Luis E

2016-11-16

In this article we propose novel Bayesian nonparametric methods using Dirichlet Process Mixture (DPM) models for detecting pairwise dependence between random variables while accounting for uncertainty in the form of the underlying distributions. A key criteria is that the procedures should scale to large data sets. In this regard we find that the formal calculation of the Bayes factor for a dependent-vs.-independent DPM joint probability measure is not feasible computationally. To address this we present Bayesian diagnostic measures for characterising evidence against a "null model" of pairwise independence. In simulation studies, as well as for a real data analysis, we show that our approach provides a useful tool for the exploratory nonparametric Bayesian analysis of large multivariate data sets.

A non-parametric method for correction of global radiation observations

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Perers, Bengt

2013-01-01

in the observations are corrected. These are errors such as: tilt in the leveling of the sensor, shadowing from surrounding objects, clipping and saturation in the signal processing, and errors from dirt and wear. The method is based on a statistical non-parametric clear-sky model which is applied to both...

Development and psychometric evaluation of the PROMIS Pediatric Life Satisfaction item banks, child-report, and parent-proxy editions.

Science.gov (United States)

Forrest, Christopher B; Devine, Janine; Bevans, Katherine B; Becker, Brandon D; Carle, Adam C; Teneralli, Rachel E; Moon, JeanHee; Tucker, Carole A; Ravens-Sieberer, Ulrike

2018-01-01

To describe the psychometric evaluation and item response theory calibration of the PROMIS Pediatric Life Satisfaction item banks, child-report, and parent-proxy editions. A pool of 55 life satisfaction items was administered to 1992 children 8-17 years old and 964 parents of children 5-17 years old. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning, and assessment of construct validity. Thirteen items were deleted because of poor psychometric performance. An 8-item short form was administered to a national sample of 996 children 8-17 years old, and 1294 parents of children 5-17 years old. The combined sample (2988 children and 2258 parents) was used in item response theory (IRT) calibration analyses. The final item banks were unidimensional, the items were locally independent, and the items were free from impactful differential item functioning. The 8-item and 4-item short form scales showed excellent reliability, convergent validity, and discriminant validity. Life satisfaction decreased with declining socio-economic status, presence of a special health care need, and increasing age for girls, but not boys. After IRT calibration, we found that 4- and 8-item short forms had a high degree of precision (reliability) across a wide range (>4 SD units) of the latent variable. The PROMIS Pediatric Life Satisfaction item banks and their short forms provide efficient, precise, and valid assessments of life satisfaction in children and youth.

Parametric Bayesian Estimation of Differential Entropy and Relative Entropy

Directory of Open Access Journals (Sweden)

Maya Gupta

2010-04-01

Full Text Available Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian estimates, depend on the accuracy of the prior parameters, but example simulations show that the performance can be substantially improved compared to maximum likelihood or state-of-the-art nonparametric estimators.

Application of nonparametric statistics to material strength/reliability assessment

International Nuclear Information System (INIS)

Arai, Taketoshi

1992-01-01

An advanced material technology requires data base on a wide variety of material behavior which need to be established experimentally. It may often happen that experiments are practically limited in terms of reproducibility or a range of test parameters. Statistical methods can be applied to understanding uncertainties in such a quantitative manner as required from the reliability point of view. Statistical assessment involves determinations of a most probable value and the maximum and/or minimum value as one-sided or two-sided confidence limit. A scatter of test data can be approximated by a theoretical distribution only if the goodness of fit satisfies a test criterion. Alternatively, nonparametric statistics (NPS) or distribution-free statistics can be applied. Mathematical procedures by NPS are well established for dealing with most reliability problems. They handle only order statistics of a sample. Mathematical formulas and some applications to engineering assessments are described. They include confidence limits of median, population coverage of sample, required minimum number of a sample, and confidence limits of fracture probability. These applications demonstrate that a nonparametric statistical estimation is useful in logical decision making in the case a large uncertainty exists. (author)

CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

Science.gov (United States)

Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.

Exact nonparametric inference for detection of nonlinear determinism

OpenAIRE

Luo, Xiaodong; Zhang, Jie; Small, Michael; Moroz, Irene

2005-01-01

We propose an exact nonparametric inference scheme for the detection of nonlinear determinism. The essential fact utilized in our scheme is that, for a linear stochastic process with jointly symmetric innovations, its ordinary least square (OLS) linear prediction error is symmetric about zero. Based on this viewpoint, a class of linear signed rank statistics, e.g. the Wilcoxon signed rank statistic, can be derived with the known null distributions from the prediction error. Thus one of the ad...

Network Reconstruction From High-Dimensional Ordinary Differential Equations.

Science.gov (United States)

Chen, Shizhe; Shojaie, Ali; Witten, Daniela M

2017-01-01

We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.

Promotion time cure rate model with nonparametric form of covariate effects.

Science.gov (United States)

Chen, Tianlei; Du, Pang

2018-05-10

Survival data with a cured portion are commonly seen in clinical trials. Motivated from a biological interpretation of cancer metastasis, promotion time cure model is a popular alternative to the mixture cure rate model for analyzing such data. The existing promotion cure models all assume a restrictive parametric form of covariate effects, which can be incorrectly specified especially at the exploratory stage. In this paper, we propose a nonparametric approach to modeling the covariate effects under the framework of promotion time cure model. The covariate effect function is estimated by smoothing splines via the optimization of a penalized profile likelihood. Point-wise interval estimates are also derived from the Bayesian interpretation of the penalized profile likelihood. Asymptotic convergence rates are established for the proposed estimates. Simulations show excellent performance of the proposed nonparametric method, which is then applied to a melanoma study. Copyright © 2018 John Wiley & Sons, Ltd.

Using automatic item generation to create multiple-choice test items.

Science.gov (United States)

Gierl, Mark J; Lai, Hollis; Turner, Simon R

2012-08-01

Many tests of medical knowledge, from the undergraduate level to the level of certification and licensure, contain multiple-choice items. Although these are efficient in measuring examinees' knowledge and skills across diverse content areas, multiple-choice items are time-consuming and expensive to create. Changes in student assessment brought about by new forms of computer-based testing have created the demand for large numbers of multiple-choice items. Our current approaches to item development cannot meet this demand. We present a methodology for developing multiple-choice items based on automatic item generation (AIG) concepts and procedures. We describe a three-stage approach to AIG and we illustrate this approach by generating multiple-choice items for a medical licensure test in the content area of surgery. To generate multiple-choice items, our method requires a three-stage process. Firstly, a cognitive model is created by content specialists. Secondly, item models are developed using the content from the cognitive model. Thirdly, items are generated from the item models using computer software. Using this methodology, we generated 1248 multiple-choice items from one item model. Automatic item generation is a process that involves using models to generate items using computer technology. With our method, content specialists identify and structure the content for the test items, and computer technology systematically combines the content to generate new test items. By combining these outcomes, items can be generated automatically. © Blackwell Publishing Ltd 2012.

Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

Science.gov (United States)

Kumar, Sricharan; Srivistava, Ashok N.

2012-01-01

Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems.

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks

Science.gov (United States)

Gray-Davies, Tristan; Holmes, Chris C.; Caron, François

2018-01-01

We present a novel Bayesian nonparametric regression model for covariates X and continuous response variable Y ∈ ℝ. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the stochastic ordering of the conditional distributions F (y|x). By adopting an approximate composite likelihood approach, we show that the resulting posterior inference can be decoupled for the separate components of the model. This procedure can scale to very large datasets and allows for the use of standard, existing, software from Bayesian nonparametric density estimation and Plackett-Luce ranking estimation to be applied. As an illustration, we show an application of our approach to a US Census dataset, with over 1,300,000 data points and more than 100 covariates. PMID:29623150

A comparison of discriminant logistic regression and Item Response Theory Likelihood-Ratio Tests for Differential Item Functioning (IRTLRDIF) in polytomous short tests.

Science.gov (United States)

Hidalgo, María D; López-Martínez, María D; Gómez-Benito, Juana; Guilera, Georgina

2016-01-01

Short scales are typically used in the social, behavioural and health sciences. This is relevant since test length can influence whether items showing DIF are correctly flagged. This paper compares the relative effectiveness of discriminant logistic regression (DLR) and IRTLRDIF for detecting DIF in polytomous short tests. A simulation study was designed. Test length, sample size, DIF amount and item response categories number were manipulated. Type I error and power were evaluated. IRTLRDIF and DLR yielded Type I error rates close to nominal level in no-DIF conditions. Under DIF conditions, Type I error rates were affected by test length DIF amount, degree of test contamination, sample size and number of item response categories. DLR showed a higher Type I error rate than did IRTLRDIF. Power rates were affected by DIF amount and sample size, but not by test length. DLR achieved higher power rates than did IRTLRDIF in very short tests, although the high Type I error rate involved means that this result cannot be taken into account. Test length had an important impact on the Type I error rate. IRTLRDIF and DLR showed a low power rate in short tests and with small sample sizes.

Nonparametric statistics a step-by-step approach

CERN Document Server

Corder, Gregory W

2014-01-01

"…a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.  It also deserves a place in libraries of all institutions where introductory statistics courses are taught."" -CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical powerSPSS® (Version 21) software and updated screen ca

A structural nonparametric reappraisal of the CO2 emissions-income relationship

NARCIS (Netherlands)

Azomahou, T.T.; Goedhuys - Degelin, Micheline; Nguyen-Van, P.

Relying on a structural nonparametric estimation, we show that co2 emissions clearly increase with income at low income levels. For higher income levels, we observe a decreasing relationship, though not significant. We also find thatco2 emissions monotonically increases with energy use at a

Nonparametric estimation of the stationary M/G/1 workload distribution function

DEFF Research Database (Denmark)

Hansen, Martin Bøgsted

2005-01-01

In this paper it is demonstrated how a nonparametric estimator of the stationary workload distribution function of the M/G/1-queue can be obtained by systematic sampling the workload process. Weak convergence results and bootstrap methods for empirical distribution functions for stationary associ...

Transformation-invariant and nonparametric monotone smooth estimation of ROC curves.

Science.gov (United States)

Du, Pang; Tang, Liansheng

2009-01-30

When a new diagnostic test is developed, it is of interest to evaluate its accuracy in distinguishing diseased subjects from non-diseased subjects. The accuracy of the test is often evaluated by receiver operating characteristic (ROC) curves. Smooth ROC estimates are often preferable for continuous test results when the underlying ROC curves are in fact continuous. Nonparametric and parametric methods have been proposed by various authors to obtain smooth ROC curve estimates. However, there are certain drawbacks with the existing methods. Parametric methods need specific model assumptions. Nonparametric methods do not always satisfy the inherent properties of the ROC curves, such as monotonicity and transformation invariance. In this paper we propose a monotone spline approach to obtain smooth monotone ROC curves. Our method ensures important inherent properties of the underlying ROC curves, which include monotonicity, transformation invariance, and boundary constraints. We compare the finite sample performance of the newly proposed ROC method with other ROC smoothing methods in large-scale simulation studies. We illustrate our method through a real life example. Copyright (c) 2008 John Wiley & Sons, Ltd.

Impulse response identification with deterministic inputs using non-parametric methods

International Nuclear Information System (INIS)

Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

1985-01-01

This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

Measuring everyday functional competence using the Rasch assessment of everyday activity limitations (REAL) item bank.

Science.gov (United States)

Oude Voshaar, Martijn A H; Ten Klooster, Peter M; Vonkeman, Harald E; van de Laar, Mart A F J

2017-11-01

Traditional patient-reported physical function instruments often poorly differentiate patients with mild-to-moderate disability. We describe the development and psychometric evaluation of a generic item bank for measuring everyday activity limitations in outpatient populations. Seventy-two items generated from patient interviews and mapped to the International Classification of Functioning, Disability and Health (ICF) domestic life chapter were administered to 1128 adults representative of the Dutch population. The partial credit model was fitted to the item responses and evaluated with respect to its assumptions, model fit, and differential item functioning (DIF). Measurement performance of a computerized adaptive testing (CAT) algorithm was compared with the SF-36 physical functioning scale (PF-10). A final bank of 41 items was developed. All items demonstrated acceptable fit to the partial credit model and measurement invariance across age, sex, and educational level. Five- and ten-item CAT simulations were shown to have high measurement precision, which exceeded that of SF-36 physical functioning scale across the physical function continuum. Floor effects were absent for a 10-item empirical CAT simulation, and ceiling effects were low (13.5%) compared with SF-36 physical functioning (38.1%). CAT also discriminated better than SF-36 physical functioning between age groups, number of chronic conditions, and respondents with or without rheumatic conditions. The Rasch assessment of everyday activity limitations (REAL) item bank will hopefully prove a useful instrument for assessing everyday activity limitations. T-scores obtained using derived measures can be used to benchmark physical function outcomes against the general Dutch adult population.

Harmonizing Measures of Cognitive Performance Across International Surveys of Aging Using Item Response Theory.

Science.gov (United States)

Chan, Kitty S; Gross, Alden L; Pezzin, Liliana E; Brandt, Jason; Kasper, Judith D

2015-12-01

To harmonize measures of cognitive performance using item response theory (IRT) across two international aging studies. Data for persons ≥65 years from the Health and Retirement Study (HRS, N = 9,471) and the English Longitudinal Study of Aging (ELSA, N = 5,444). Cognitive performance measures varied (HRS fielded 25, ELSA 13); 9 were in common. Measurement precision was examined for IRT scores based on (a) common items, (b) common items adjusted for differential item functioning (DIF), and (c) DIF-adjusted all items. Three common items (day of date, immediate word recall, and delayed word recall) demonstrated DIF by survey. Adding survey-specific items improved precision but mainly for HRS respondents at lower cognitive levels. IRT offers a feasible strategy for harmonizing cognitive performance measures across other surveys and for other multi-item constructs of interest in studies of aging. Practical implications depend on sample distribution and the difficulty mix of in-common and survey-specific items. © The Author(s) 2015.

Item response analysis on an examination in anesthesiology for medical students in Taiwan: A comparison of one- and two-parameter logistic models

Directory of Open Access Journals (Sweden)

Yu-Feng Huang

2013-06-01

Conclusion: Item response models are useful for medical test analyses and provide valuable information about model comparisons and identification of differential items other than test reliability, item difficulty, and examinee's ability.

A nonparametric approach to medical survival data: Uncertainty in the context of risk in mortality analysis

International Nuclear Information System (INIS)

Janurová, Kateřina; Briš, Radim

2014-01-01

Medical survival right-censored data of about 850 patients are evaluated to analyze the uncertainty related to the risk of mortality on one hand and compare two basic surgery techniques in the context of risk of mortality on the other hand. Colorectal data come from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either traditional (open) or minimally invasive (laparoscopic). Basic question arising at the colectomy operation is, which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify probability of mortality with uncertainties. In fact, complement of the probability to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan–Meier estimator of survival function in connection with Greenwood's formula and the Nelson–Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been compared to evaluate risk of mortality in the context of mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Both nonparametric approaches led to the same conclusion, that the minimally invasive operating technique guarantees the patient significantly longer survival time in comparison with the traditional operating technique

Nonparametric Estimation of Interval Reliability for Discrete-Time Semi-Markov Systems

DEFF Research Database (Denmark)

Georgiadis, Stylianos; Limnios, Nikolaos

2016-01-01

In this article, we consider a repairable discrete-time semi-Markov system with finite state space. The measure of the interval reliability is given as the probability of the system being operational over a given finite-length time interval. A nonparametric estimator is proposed for the interval...

Assessing pupil and school performance by non-parametric and parametric techniques

NARCIS (Netherlands)

de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.

2010-01-01

This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall

Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

NARCIS (Netherlands)

Yoo, W.W.; Ghosal, S

2016-01-01

In the setting of nonparametric multivariate regression with unknown error variance, we study asymptotic properties of a Bayesian method for estimating a regression function f and its mixed partial derivatives. We use a random series of tensor product of B-splines with normal basis coefficients as a

A non-parametric hierarchical model to discover behavior dynamics from tracks

NARCIS (Netherlands)

Kooij, J.F.P.; Englebienne, G.; Gavrila, D.M.

2012-01-01

We present a novel non-parametric Bayesian model to jointly discover the dynamics of low-level actions and high-level behaviors of tracked people in open environments. Our model represents behaviors as Markov chains of actions which capture high-level temporal dynamics. Actions may be shared by

Symptom endorsement in men versus women with a diagnosis of depression: A differential item functioning approach.

Science.gov (United States)

Cavanagh, Anna; Wilson, Coralie J; Caputi, Peter; Kavanagh, David J

2016-09-01

There is some evidence that, in contrast to depressed women, depressed men tend to report alternative symptoms that are not listed as standard diagnostic criteria. This may possibly lead to an under- or misdiagnosis of depression in men. This study aims to clarify whether depressed men and women report different symptoms. This study used data from the 2007 Australian National Survey of Mental Health and Wellbeing that was collected using the World Health Organization's Composite International Diagnostic Interview. Participants with a diagnosis of a depressive disorder with 12-month symptoms (n = 663) were identified and included in this study. Differential item functioning (DIF) was used to test whether depressed men and women endorse different features associated with their condition. Gender-related DIF was present for three symptoms associated with depression. Depressed women were more likely to report 'appetite/weight disturbance', whereas depressed men were more likely to report 'alcohol misuse' and 'substance misuse'. While the results may reflect a greater risk of co-occurring alcohol and substance misuse in men, inclusion of these features in assessments may improve the detection of depression in men, especially if standard depressive symptoms are under-reported. © The Author(s) 2016.

On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests

Directory of Open Access Journals (Sweden)

Aaditya Ramdas

2017-01-01

Full Text Available Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich, with a wide variety of statistics having being designed and analyzed, both for the unidimensional and the multivariate setting. Inthisshortsurvey,wefocusonteststatisticsthatinvolvetheWassersteindistance. Usingan entropic smoothing of the Wasserstein distance, we connect these to very different tests including multivariate methods involving energy statistics and kernel based maximum mean discrepancy and univariate methods like the Kolmogorov–Smirnov test, probability or quantile (PP/QQ plots and receiver operating characteristic or ordinal dominance (ROC/ODC curves. Some observations are implicit in the literature, while others seem to have not been noticed thus far. Given nonparametric two-sample testing’s classical and continued importance, we aim to provide useful connections for theorists and practitioners familiar with one subset of methods but not others.

A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: ordinal logistic regression, Rasch analysis and the Mantel chi-square procedure.

Science.gov (United States)

Cameron, Isobel M; Scott, Neil W; Adler, Mats; Reid, Ian C

2014-12-01

It is important for clinical practice and research that measurement scales of well-being and quality of life exhibit only minimal differential item functioning (DIF). DIF occurs where different groups of people endorse items in a scale to different extents after being matched by the intended scale attribute. We investigate the equivalence or otherwise of common methods of assessing DIF. Three methods of measuring age- and sex-related DIF (ordinal logistic regression, Rasch analysis and Mantel χ(2) procedure) were applied to Hospital Anxiety Depression Scale (HADS) data pertaining to a sample of 1,068 patients consulting primary care practitioners. Three items were flagged by all three approaches as having either age- or sex-related DIF with a consistent direction of effect; a further three items identified did not meet stricter criteria for important DIF using at least one method. When applying strict criteria for significant DIF, ordinal logistic regression was slightly less sensitive. Ordinal logistic regression, Rasch analysis and contingency table methods yielded consistent results when identifying DIF in the HADS depression and HADS anxiety scales. Regardless of methods applied, investigators should use a combination of statistical significance, magnitude of the DIF effect and investigator judgement when interpreting the results.

DISC Predictive Scales (DPS): Factor Structure and Uniform Differential Item Functioning Across Gender and Three Racial/Ethnic Groups for ADHD, Conduct Disorder, and Oppositional Defiant Disorder Symptoms

OpenAIRE

Wiesner, Margit; Kanouse, David E.; Elliott, Marc N.; Windle, Michael; Schuster, Mark A.

2015-01-01

The factor structure and potential uniform differential item functioning (DIF) among gender and three racial/ethnic groups of adolescents (African American, Latino, White) were evaluated for attention deficit/hyperactivity disorder (ADHD), conduct disorder (CD), and oppositional defiant disorder (ODD) symptom scores of the DISC Predictive Scales (DPS; Leung et al., 2005; Lucas et al., 2001). Primary caregivers reported on DSM–IV ADHD, CD, and ODD symptoms for a probability sample of 4,491 chi...

Using non-parametric methods in econometric production analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...

Estimation of Stochastic Volatility Models by Nonparametric Filtering

DEFF Research Database (Denmark)

Kanaya, Shin; Kristensen, Dennis

2016-01-01

/estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases...... and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties...

Nonparametric Bayesian inference in biostatistics

CERN Document Server

Müller, Peter

2015-01-01

As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...

A comparison of Rasch item-fit and Cronbach's alpha item reduction analysis for the development of a Quality of Life scale for children and adolescents.

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Erhart, M; Hagquist, C; Auquier, P; Rajmil, L; Power, M; Ravens-Sieberer, U

2010-07-01

This study compares item reduction analysis based on classical test theory (maximizing Cronbach's alpha - approach A), with analysis based on the Rasch Partial Credit Model item-fit (approach B), as applied to children and adolescents' health-related quality of life (HRQoL) items. The reliability and structural, cross-cultural and known-group validity of the measures were examined. Within the European KIDSCREEN project, 3019 children and adolescents (8-18 years) from seven European countries answered 19 HRQoL items of the Physical Well-being dimension of a preliminary KIDSCREEN instrument. The Cronbach's alpha and corrected item total correlation (approach A) were compared with infit mean squares and the Q-index item-fit derived according to a partial credit model (approach B). Cross-cultural differential item functioning (DIF ordinal logistic regression approach), structural validity (confirmatory factor analysis and residual correlation) and relative validity (RV) for socio-demographic and health-related factors were calculated for approaches (A) and (B). Approach (A) led to the retention of 13 items, compared with 11 items with approach (B). The item overlap was 69% for (A) and 78% for (B). The correlation coefficient of the summated ratings was 0.93. The Cronbach's alpha was similar for both versions [0.86 (A); 0.85 (B)]. Both approaches selected some items that are not strictly unidimensional and items displaying DIF. RV ratios favoured (A) with regard to socio-demographic aspects. Approach (B) was superior in RV with regard to health-related aspects. Both types of item reduction analysis should be accompanied by additional analyses. Neither of the two approaches was universally superior with regard to cultural, structural and known-group validity. However, the results support the usability of the Rasch method for developing new HRQoL measures for children and adolescents.

Hadron Energy Reconstruction for ATLAS Barrel Combined Calorimeter Using Non-Parametrical Method

CERN Document Server

Kulchitskii, Yu A

2000-01-01

Hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter in the framework of the non-parametrical method is discussed. The non-parametrical method utilizes only the known e/h ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to fast energy reconstruction in a first level trigger. The reconstructed mean values of the hadron energies are within \\pm1% of the true values and the fractional energy resolution is [(58\\pm 3)%{\\sqrt{GeV}}/\\sqrt{E}+(2.5\\pm0.3)%]\\bigoplus(1.7\\pm0.2) GeV/E. The value of the e/h ratio obtained for the electromagnetic compartment of the combined calorimeter is 1.74\\pm0.04. Results of a study of the longitudinal hadronic shower development are also presented.

Bayesian nonparametric estimation of continuous monotone functions with applications to dose-response analysis.

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Bornkamp, Björn; Ickstadt, Katja

2009-03-01

In this article, we consider monotone nonparametric regression in a Bayesian framework. The monotone function is modeled as a mixture of shifted and scaled parametric probability distribution functions, and a general random probability measure is assumed as the prior for the mixing distribution. We investigate the choice of the underlying parametric distribution function and find that the two-sided power distribution function is well suited both from a computational and mathematical point of view. The model is motivated by traditional nonlinear models for dose-response analysis, and provides possibilities to elicitate informative prior distributions on different aspects of the curve. The method is compared with other recent approaches to monotone nonparametric regression in a simulation study and is illustrated on a data set from dose-response analysis.

Low default credit scoring using two-class non-parametric kernel density estimation

CSIR Research Space (South Africa)

Rademeyer, E

2016-12-01

Full Text Available This paper investigates the performance of two-class classification credit scoring data sets with low default ratios. The standard two-class parametric Gaussian and non-parametric Parzen classifiers are extended, using Bayes’ rule, to include either...

The Role of Item Models in Automatic Item Generation

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Gierl, Mark J.; Lai, Hollis

2012-01-01

Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

Science.gov (United States)

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Problems with the factor analysis of items: Solutions based on item response theory and item parcelling

Directory of Open Access Journals (Sweden)

Gideon P. De Bruin

2004-10-01

Full Text Available The factor analysis of items often produces spurious results in the sense that unidimensional scales appear multidimensional. This may be ascribed to failure in meeting the assumptions of linearity and normality on which factor analysis is based. Item response theory is explicitly designed for the modelling of the non-linear relations between ordinal variables and provides a strong alternative to the factor analysis of items. Items may also be combined in parcels that are more likely to satisfy the assumptions of factor analysis than do the items. The use of the Rasch rating scale model and the factor analysis of parcels is illustrated with data obtained with the Locus of Control Inventory. The results of these analyses are compared with the results obtained through the factor analysis of items. It is shown that the Rasch rating scale model and the factoring of parcels produce superior results to the factor analysis of items. Recommendations for the analysis of scales are made. Opsomming Die faktorontleding van items lewer dikwels misleidende resultate op, veral in die opsig dat eendimensionele skale as meerdimensioneel voorkom. Hierdie resultate kan dikwels daaraan toegeskryf word dat daar nie aan die aannames van lineariteit en normaliteit waarop faktorontleding berus, voldoen word nie. Itemresponsteorie, wat eksplisiet vir die modellering van die nie-liniêre verbande tussen ordinale items ontwerp is, bied ’n aantreklike alternatief vir die faktorontleding van items. Items kan ook in pakkies gegroepeer word wat meer waarskynlik aan die aannames van faktorontleding voldoen as individuele items. Die gebruik van die Rasch beoordelingskaalmodel en die faktorontleding van pakkies word aan die hand van data wat met die Lokus van Beheervraelys verkry is, gedemonstreer. Die resultate van hierdie ontledings word vergelyk met die resultate wat deur ‘n faktorontleding van die individuele items verkry is. Die resultate dui daarop dat die Rasch

Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

DEFF Research Database (Denmark)

Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...

DISC Predictive Scales (DPS): Factor structure and uniform differential item functioning across gender and three racial/ethnic groups for ADHD, conduct disorder, and oppositional defiant disorder symptoms.

Science.gov (United States)

Wiesner, Margit; Windle, Michael; Kanouse, David E; Elliott, Marc N; Schuster, Mark A

2015-12-01

The factor structure and potential uniform differential item functioning (DIF) among gender and three racial/ethnic groups of adolescents (African American, Latino, White) were evaluated for attention deficit/hyperactivity disorder (ADHD), conduct disorder (CD), and oppositional defiant disorder (ODD) symptom scores of the DISC Predictive Scales (DPS; Leung et al., 2005; Lucas et al., 2001). Primary caregivers reported on DSM-IV ADHD, CD, and ODD symptoms for a probability sample of 4,491 children from three geographical regions who took part in the Healthy Passages study (mean age = 12.60 years, SD = 0.66). Confirmatory factor analysis indicated that the expected 3-factor structure was tenable for the data. Multiple indicators multiple causes (MIMIC) modeling revealed uniform DIF for three ADHD and 9 ODD item scores, but not for any of the CD item scores. Uniform DIF was observed predominantly as a function of child race/ethnicity, but minimally as a function of child gender. On the positive side, uniform DIF had little impact on latent mean differences of ADHD, CD, and ODD symptomatology among gender and racial/ethnic groups. Implications of the findings for researchers and practitioners are discussed. (c) 2015 APA, all rights reserved).

Numerical Differentiation Methods for Computing Error Covariance Matrices in Item Response Theory Modeling: An Evaluation and a New Proposal

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Tian, Wei; Cai, Li; Thissen, David; Xin, Tao

2013-01-01

In item response theory (IRT) modeling, the item parameter error covariance matrix plays a critical role in statistical inference procedures. When item parameters are estimated using the EM algorithm, the parameter error covariance matrix is not an automatic by-product of item calibration. Cai proposed the use of Supplemented EM algorithm for…

Differential geometry and mathematical physics

CERN Document Server

Rudolph, Gerd

Starting from an undergraduate level, this book systematically develops the basics of • Calculus on manifolds, vector bundles, vector fields and differential forms, • Lie groups and Lie group actions, • Linear symplectic algebra and symplectic geometry, • Hamiltonian systems, symmetries and reduction, integrable systems and Hamilton-Jacobi theory. The topics listed under the first item are relevant for virtually all areas of mathematical physics. The second and third items constitute the link between abstract calculus and the theory of Hamiltonian systems. The last item provides an introduction to various aspects of this theory, including Morse families, the Maslov class and caustics. The book guides the reader from elementary differential geometry to advanced topics in the theory of Hamiltonian systems with the aim of making current research literature accessible. The style is that of a mathematical textbook,with full proofs given in the text or as exercises. The material is illustrated by numerous d...

Disparities in Sense of Community: True Race Differences or Differential Item Functioning?

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Coffman, Donna L.; BeLue, Rhonda

2009-01-01

The sense of community index (SCI) has been widely used to measure psychological sense of community (SOC). Furthermore, SOC has been found to differ among racial groups. Because different ethnic groups have different cultural and historical experiences that may lead to different interpretations of measurement items, it is important to know whether…

Item information and discrimination functions for trinary PCM items

NARCIS (Netherlands)

Akkermans, Wies; Muraki, Eiji

1997-01-01

For trinary partial credit items the shape of the item information and the item discrimination function is examined in relation to the item parameters. In particular, it is shown that these functions are unimodal if δ2 – δ1 < 4 ln 2 and bimodal otherwise. The locations and values of the maxima are

Using Likert-type and ipsative/forced choice items in sequence to generate a preference.

Science.gov (United States)

Ried, L Douglas

2014-01-01

Collaboration and implementation of a minimum, standardized set of core global educational and professional competencies seems appropriate given the expanding international evolution of pharmacy practice. However, winnowing down hundreds of competencies from a plethora of local, national and international competency frameworks to select the most highly preferred to be included in the core set is a daunting task. The objective of this paper is to describe a combination of strategies used to ascertain the most highly preferred items among a large number of disparate items. In this case, the items were >100 educational and professional competencies that might be incorporated as the core components of new and existing competency frameworks. Panelists (n = 30) from the European Union (EU) and United States (USA) were chosen to reflect a variety of practice settings. Each panelist completed two electronic surveys. The first survey presented competencies in a Likert-type format and the second survey presented many of the same competencies in an ipsative/forced choice format. Item mean scores were calculated for each competency, the competencies were ranked, and non-parametric statistical tests were used to ascertain the consistency in the rankings achieved by the two strategies. This exploratory study presented over 100 competencies to the panelists in the beginning. The two methods provided similar results, as indicated by the significant correlation between the rankings (Spearman's rho = 0.30, P < 0.09). A two-step strategy using Likert-type and ipsative/forced choice formats in sequence, appears to be useful in a situation where a clear preference is required from among a large number of choices. The ipsative/forced choice format resulted in some differences in the competency preferences because the panelists could not rate them equally by design. While this strategy was used for the selection of professional educational competencies in this exploratory study, it is

A multi-instrument non-parametric reconstruction of the electron pressure profile in the galaxy cluster CLJ1226.9+3332

Science.gov (United States)

Romero, C.; McWilliam, M.; Macías-Pérez, J.-F.; Adam, R.; Ade, P.; André, P.; Aussel, H.; Beelen, A.; Benoît, A.; Bideaud, A.; Billot, N.; Bourrion, O.; Calvo, M.; Catalano, A.; Coiffard, G.; Comis, B.; de Petris, M.; Désert, F.-X.; Doyle, S.; Goupy, J.; Kramer, C.; Lagache, G.; Leclercq, S.; Lestrade, J.-F.; Mauskopf, P.; Mayet, F.; Monfardini, A.; Pascale, E.; Perotto, L.; Pisano, G.; Ponthieu, N.; Revéret, V.; Ritacco, A.; Roussel, H.; Ruppin, F.; Schuster, K.; Sievers, A.; Triqueneaux, S.; Tucker, C.; Zylka, R.

2018-04-01

Context. In the past decade, sensitive, resolved Sunyaev-Zel'dovich (SZ) studies of galaxy clusters have become common. Whereas many previous SZ studies have parameterized the pressure profiles of galaxy clusters, non-parametric reconstructions will provide insights into the thermodynamic state of the intracluster medium. Aim. We seek to recover the non-parametric pressure profiles of the high redshift (z = 0.89) galaxy cluster CLJ 1226.9+3332 as inferred from SZ data from the MUSTANG, NIKA, Bolocam, and Planck instruments, which all probe different angular scales. Methods: Our non-parametric algorithm makes use of logarithmic interpolation, which under the assumption of ellipsoidal symmetry is analytically integrable. For MUSTANG, NIKA, and Bolocam we derive a non-parametric pressure profile independently and find good agreement among the instruments. In particular, we find that the non-parametric profiles are consistent with a fitted generalized Navaro-Frenk-White (gNFW) profile. Given the ability of Planck to constrain the total signal, we include a prior on the integrated Compton Y parameter as determined by Planck. Results: For a given instrument, constraints on the pressure profile diminish rapidly beyond the field of view. The overlap in spatial scales probed by these four datasets is therefore critical in checking for consistency between instruments. By using multiple instruments, our analysis of CLJ 1226.9+3332 covers a large radial range, from the central regions to the cluster outskirts: 0.05 R500 generation of SZ instruments such as NIKA2 and MUSTANG2.

Analyzing cost efficient production behavior under economies of scope : A nonparametric methodology

NARCIS (Netherlands)

Cherchye, L.J.H.; de Rock, B.; Vermeulen, F.M.P.

2008-01-01

In designing a production model for firms that generate multiple outputs, we take as a starting point that such multioutput production refers to economies of scope, which in turn originate from joint input use and input externalities. We provide a nonparametric characterization of cost-efficient

A multi-level differential item functioning analysis of trends in international mathematics and science study: Potential sources of gender and minority difference among U.S. eighth graders' science achievement

Science.gov (United States)

Qian, Xiaoyu

Science is an area where a large achievement gap has been observed between White and minority, and between male and female students. The science minority gap has continued as indicated by the National Assessment of Educational Progress and the Trends in International Mathematics and Science Studies (TIMSS). TIMSS also shows a gender gap favoring males emerging at the eighth grade. Both gaps continue to be wider in the number of doctoral degrees and full professorships awarded (NSF, 2008). The current study investigated both minority and gender achievement gaps in science utilizing a multi-level differential item functioning (DIF) methodology (Kamata, 2001) within fully Bayesian framework. All dichotomously coded items from TIMSS 2007 science assessment at eighth grade were analyzed. Both gender DIF and minority DIF were studied. Multi-level models were employed to identify DIF items and sources of DIF at both student and teacher levels. The study found that several student variables were potential sources of achievement gaps. It was also found that gender DIF favoring male students was more noticeable in the content areas of physics and earth science than biology and chemistry. In terms of item type, the majority of these gender DIF items were multiple choice than constructed response items. Female students also performed less well on items requiring visual-spatial ability. Minority students performed significantly worse on physics and earth science items as well. A higher percentage of minority DIF items in earth science and biology were constructed response than multiple choice items, indicating that literacy may be the cause of minority DIF. Three-level model results suggested that some teacher variables may be the cause of DIF variations from teacher to teacher. It is essential for both middle school science teachers and science educators to find instructional methods that work more effectively to improve science achievement of both female and minority students

A non-parametric Bayesian approach to decompounding from high frequency data

NARCIS (Netherlands)

Gugushvili, Shota; van der Meulen, F.H.; Spreij, Peter

2016-01-01

Given a sample from a discretely observed compound Poisson process, we consider non-parametric estimation of the density f0 of its jump sizes, as well as of its intensity λ0. We take a Bayesian approach to the problem and specify the prior on f0 as the Dirichlet location mixture of normal densities.

Item level diagnostics and model - data fit in item response theory ...

African Journals Online (AJOL)

Item response theory (IRT) is a framework for modeling and analyzing item response data. Item-level modeling gives IRT advantages over classical test theory. The fit of an item score pattern to an item response theory (IRT) models is a necessary condition that must be assessed for further use of item and models that best fit ...

Evaluating HIV Knowledge Questionnaires Among Men Who Have Sex with Men: A Multi-Study Item Response Theory Analysis.

Science.gov (United States)

Janulis, Patrick; Newcomb, Michael E; Sullivan, Patrick; Mustanski, Brian

2018-01-01

Knowledge about the transmission, prevention, and treatment of HIV remains a critical element in psychosocial models of HIV risk behavior and is commonly used as an outcome in HIV prevention interventions. However, most HIV knowledge questions have not undergone rigorous psychometric testing such as using item response theory. The current study used data from six studies of men who have sex with men (MSM; n = 3565) to (1) examine the item properties of HIV knowledge questions, (2) test for differential item functioning on commonly studied characteristics (i.e., age, race/ethnicity, and HIV risk behavior), (3) select items with the optimal item characteristics, and (4) leverage this combined dataset to examine the potential moderating effect of age on the relationship between condomless anal sex (CAS) and HIV knowledge. Findings indicated that existing questions tend to poorly differentiate those with higher levels of HIV knowledge, but items were relatively robust across diverse individuals. Furthermore, age moderated the relationship between CAS and HIV knowledge with older MSM having the strongest association. These findings suggest that additional items are required in order to capture a more nuanced understanding of HIV knowledge and that the association between CAS and HIV knowledge may vary by age.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

Science.gov (United States)

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

kruX: matrix-based non-parametric eQTL discovery.

Science.gov (United States)

Qi, Jianlong; Asl, Hassan Foroughi; Björkegren, Johan; Michoel, Tom

2014-01-14

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure and is freely available from http://krux.googlecode.com.

Bayes Factor Covariance Testing in Item Response Models.

Science.gov (United States)

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Using Explanatory Item Response Models to Evaluate Complex Scientific Tasks Designed for the Next Generation Science Standards

Science.gov (United States)

Chiu, Tina

This dissertation includes three studies that analyze a new set of assessment tasks developed by the Learning Progressions in Middle School Science (LPS) Project. These assessment tasks were designed to measure science content knowledge on the structure of matter domain and scientific argumentation, while following the goals from the Next Generation Science Standards (NGSS). The three studies focus on the evidence available for the success of this design and its implementation, generally labelled as "validity" evidence. I use explanatory item response models (EIRMs) as the overarching framework to investigate these assessment tasks. These models can be useful when gathering validity evidence for assessments as they can help explain student learning and group differences. In the first study, I explore the dimensionality of the LPS assessment by comparing the fit of unidimensional, between-item multidimensional, and Rasch testlet models to see which is most appropriate for this data. By applying multidimensional item response models, multiple relationships can be investigated, and in turn, allow for a more substantive look into the assessment tasks. The second study focuses on person predictors through latent regression and differential item functioning (DIF) models. Latent regression models show the influence of certain person characteristics on item responses, while DIF models test whether one group is differentially affected by specific assessment items, after conditioning on latent ability. Finally, the last study applies the linear logistic test model (LLTM) to investigate whether item features can help explain differences in item difficulties.

Evaluation of the Fecal Incontinence Quality of Life Scale (FIQL) using item response theory reveals limitations and suggests revisions.

Science.gov (United States)

Peterson, Alexander C; Sutherland, Jason M; Liu, Guiping; Crump, R Trafford; Karimuddin, Ahmer A

2018-06-01

The Fecal Incontinence Quality of Life Scale (FIQL) is a commonly used patient-reported outcome measure for fecal incontinence, often used in clinical trials, yet has not been validated in English since its initial development. This study uses modern methods to thoroughly evaluate the psychometric characteristics of the FIQL and its potential for differential functioning by gender. This study analyzed prospectively collected patient-reported outcome data from a sample of patients prior to colorectal surgery. Patients were recruited from 14 general and colorectal surgeons in Vancouver Coastal Health hospitals in Vancouver, Canada. Confirmatory factor analysis was used to assess construct validity. Item response theory was used to evaluate test reliability, describe item-level characteristics, identify local item dependence, and test for differential functioning by gender. 236 patients were included for analysis, with mean age 58 and approximately half female. Factor analysis failed to identify the lifestyle, coping, depression, and embarrassment domains, suggesting lack of construct validity. Items demonstrated low difficulty, indicating that the test has the highest reliability among individuals who have low quality of life. Five items are suggested for removal or replacement. Differential test functioning was minimal. This study has identified specific improvements that can be made to each domain of the Fecal Incontinence Quality of Life Scale and to the instrument overall. Formatting, scoring, and instructions may be simplified, and items with higher difficulty developed. The lifestyle domain can be used as is. The embarrassment domain should be significantly revised before use.

Linking Existing Instruments to Develop an Activity of Daily Living Item Bank.

Science.gov (United States)

Li, Chih-Ying; Romero, Sergio; Bonilha, Heather S; Simpson, Kit N; Simpson, Annie N; Hong, Ickpyo; Velozo, Craig A

2018-03-01

This study examined dimensionality and item-level psychometric properties of an item bank measuring activities of daily living (ADL) across inpatient rehabilitation facilities and community living centers. Common person equating method was used in the retrospective veterans data set. This study examined dimensionality, model fit, local independence, and monotonicity using factor analyses and fit statistics, principal component analysis (PCA), and differential item functioning (DIF) using Rasch analysis. Following the elimination of invalid data, 371 veterans who completed both the Functional Independence Measure (FIM) and minimum data set (MDS) within 6 days were retained. The FIM-MDS item bank demonstrated good internal consistency (Cronbach's α = .98) and met three rating scale diagnostic criteria and three of the four model fit statistics (comparative fit index/Tucker-Lewis index = 0.98, root mean square error of approximation = 0.14, and standardized root mean residual = 0.07). PCA of Rasch residuals showed the item bank explained 94.2% variance. The item bank covered the range of θ from -1.50 to 1.26 (item), -3.57 to 4.21 (person) with person strata of 6.3. The findings indicated the ADL physical function item bank constructed from FIM and MDS measured a single latent trait with overall acceptable item-level psychometric properties, suggesting that it is an appropriate source for developing efficient test forms such as short forms and computerized adaptive tests.

Exact nonparametric confidence bands for the survivor function.

Science.gov (United States)

Matthews, David

2013-10-12

A method to produce exact simultaneous confidence bands for the empirical cumulative distribution function that was first described by Owen, and subsequently corrected by Jager and Wellner, is the starting point for deriving exact nonparametric confidence bands for the survivor function of any positive random variable. We invert a nonparametric likelihood test of uniformity, constructed from the Kaplan-Meier estimator of the survivor function, to obtain simultaneous lower and upper bands for the function of interest with specified global confidence level. The method involves calculating a null distribution and associated critical value for each observed sample configuration. However, Noe recursions and the Van Wijngaarden-Decker-Brent root-finding algorithm provide the necessary tools for efficient computation of these exact bounds. Various aspects of the effect of right censoring on these exact bands are investigated, using as illustrations two observational studies of survival experience among non-Hodgkin's lymphoma patients and a much larger group of subjects with advanced lung cancer enrolled in trials within the North Central Cancer Treatment Group. Monte Carlo simulations confirm the merits of the proposed method of deriving simultaneous interval estimates of the survivor function across the entire range of the observed sample. This research was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada. It was begun while the author was visiting the Department of Statistics, University of Auckland, and completed during a subsequent sojourn at the Medical Research Council Biostatistics Unit in Cambridge. The support of both institutions, in addition to that of NSERC and the University of Waterloo, is greatly appreciated.

Evaluating the quality of medical multiple-choice items created with automated processes.

Science.gov (United States)

Gierl, Mark J; Lai, Hollis

2013-07-01

Computerised assessment raises formidable challenges because it requires large numbers of test items. Automatic item generation (AIG) can help address this test development problem because it yields large numbers of new items both quickly and efficiently. To date, however, the quality of the items produced using a generative approach has not been evaluated. The purpose of this study was to determine whether automatic processes yield items that meet standards of quality that are appropriate for medical testing. Quality was evaluated firstly by subjecting items created using both AIG and traditional processes to rating by a four-member expert medical panel using indicators of multiple-choice item quality, and secondly by asking the panellists to identify which items were developed using AIG in a blind review. Fifteen items from the domain of therapeutics were created in three different experimental test development conditions. The first 15 items were created by content specialists using traditional test development methods (Group 1 Traditional). The second 15 items were created by the same content specialists using AIG methods (Group 1 AIG). The third 15 items were created by a new group of content specialists using traditional methods (Group 2 Traditional). These 45 items were then evaluated for quality by a four-member panel of medical experts and were subsequently categorised as either Traditional or AIG items. Three outcomes were reported: (i) the items produced using traditional and AIG processes were comparable on seven of eight indicators of multiple-choice item quality; (ii) AIG items can be differentiated from Traditional items by the quality of their distractors, and (iii) the overall predictive accuracy of the four expert medical panellists was 42%. Items generated by AIG methods are, for the most part, equivalent to traditionally developed items from the perspective of expert medical reviewers. While the AIG method produced comparatively fewer plausible

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Science.gov (United States)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Directory of Open Access Journals (Sweden)

Jinchao Feng

2018-03-01

Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Concreteness effects in short-term memory: a test of the item-order hypothesis.

Science.gov (United States)

Roche, Jaclynn; Tolan, G Anne; Tehan, Gerald

2011-12-01

The following experiments explore word length and concreteness effects in short-term memory within an item-order processing framework. This framework asserts order memory is better for those items that are relatively easy to process at the item level. However, words that are difficult to process benefit at the item level for increased attention/resources being applied. The prediction of the model is that differential item and order processing can be detected in episodic tasks that differ in the degree to which item or order memory are required by the task. The item-order account has been applied to the word length effect such that there is a short word advantage in serial recall but a long word advantage in item recognition. The current experiment considered the possibility that concreteness effects might be explained within the same framework. In two experiments, word length (Experiment 1) and concreteness (Experiment 2) are examined using forward serial recall, backward serial recall, and item recognition. These results for word length replicate previous studies showing the dissociation in item and order tasks. The same was not true for the concreteness effect. In all three tasks concrete words were better remembered than abstract words. The concreteness effect cannot be explained in terms of an item-order trade off. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Analyzing Cost Efficient Production Behavior Under Economies of Scope : A Nonparametric Methodology

NARCIS (Netherlands)

Cherchye, L.J.H.; de Rock, B.; Vermeulen, F.M.P.

2006-01-01

In designing a production model for firms that generate multiple outputs, we take as a starting point that such multi-output production refers to economies of scope, which in turn originate from joint input use and input externalities. We provide a nonparametric characterization of cost efficient

Digital spectral analysis parametric, non-parametric and advanced methods

CERN Document Server

Castanié, Francis

2013-01-01

Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

KAUST Repository

Dai, Wenlin; Tong, Tiejun; Zhu, Lixing

2017-01-01

Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

KAUST Repository

Dai, Wenlin

2017-09-01

Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data

OpenAIRE

CORNELIS A. LOS

2004-01-01

The efficiency of speculative markets, as represented by Fama's 1970 fair game model, is tested on weekly price index data of six Asian stock markets - Hong Kong, Indonesia, Malaysia, Singapore, Taiwan and Thailand - using Sherry's (1992) non-parametric methods. These scientific testing methods were originally developed to analyze the information processing efficiency of nervous systems. In particular, the stationarity and independence of the price innovations are tested over ten years, from ...

Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors

Directory of Open Access Journals (Sweden)

Xibin Zhang

2016-04-01

Full Text Available This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density. The error density is approximated by the kernel density estimator of the unobserved errors, while the regression function is estimated using the Nadaraya-Watson estimator admitting continuous and discrete regressors. We derive an approximate likelihood and posterior for bandwidth parameters, followed by a sampling algorithm. Simulation results show that the proposed approach typically leads to better accuracy of the resulting estimates than cross-validation, particularly for smaller sample sizes. This bandwidth estimation approach is applied to nonparametric regression model of the Australian All Ordinaries returns and the kernel density estimation of gross domestic product (GDP growth rates among the organisation for economic co-operation and development (OECD and non-OECD countries.

deltaPlotR: An R Package for Di?erential Item Functioning Analysis with Ango? s Delta Plot

OpenAIRE

David Magis; Bruno Facon

2014-01-01

Angoff's delta plot is a straightforward and not computationally intensive method to identify differential item functioning (DIF) among dichotomously scored items. This approach was recently improved by proposing an optimal threshold selection and by considering several item purification processes. Moreover, to support practical DIF analyses with the delta plot and these improvements, the R package deltaPlotR was also developed. The purpose of this paper is twofold: to outline the delta plot ...

Estimation of the limit of detection with a bootstrap-derived standard error by a partly non-parametric approach. Application to HPLC drug assays

DEFF Research Database (Denmark)

Linnet, Kristian

2005-01-01

Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...

Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

Directory of Open Access Journals (Sweden)

Ibsen Chivatá Cárdenas

2008-05-01

Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

Beneficial effects of semantic memory support on older adults' episodic memory: Differential patterns of support of item and associative information.

Science.gov (United States)

Mohanty, Praggyan Pam; Naveh-Benjamin, Moshe; Ratneshwar, Srinivasan

2016-02-01

The effects of two types of semantic memory support-meaningfulness of an item and relatedness between items-in mitigating age-related deficits in item and associative, memory are examined in a marketing context. In Experiment 1, participants studied less (vs. more) meaningful brand logo graphics (pictures) paired with meaningful brand names (words) and later were assessed by item (old/new) and associative (intact/recombined) memory recognition tests. Results showed that meaningfulness of items eliminated age deficits in item memory, while equivalently boosting associative memory for older and younger adults. Experiment 2, in which related and unrelated brand logo graphics and brand name pairs served as stimuli, revealed that relatedness between items eliminated age deficits in associative memory, while improving to the same degree item memory in older and younger adults. Experiment 2 also provided evidence for a probable boundary condition that could reconcile seemingly contradictory extant results. Overall, these experiments provided evidence that although the two types of semantic memory support can improve both item and associative memory in older and younger adults, older adults' memory deficits can be eliminated when the type of support provided is compatible with the type of information required to perform well on the test. (c) 2016 APA, all rights reserved).

Nonparametric estimation of location and scale parameters

KAUST Repository

Potgieter, C.J.

2012-12-01

Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.

Nonparametric Analyses of Log-Periodic Precursors to Financial Crashes

Science.gov (United States)

Zhou, Wei-Xing; Sornette, Didier

We apply two nonparametric methods to further test the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The term "parametric" refers here to the use of the log-periodic power law formula to fit the data; in contrast, "nonparametric" refers to the use of general tools such as Fourier transform, and in the present case the Hilbert transform and the so-called (H, q)-analysis. The analysis using the (H, q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln(tc-t) variable, where tc is the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05 corresponding to the scaling ratio λ=2.67±0.12. These values are in very good agreement with those obtained in earlier works with different parametric techniques. This note is extracted from a long unpublished report with 58 figures available at , which extensively describes the evidence we have accumulated on these seven time series, in particular by presenting all relevant details so that the reader can judge for himself or herself the validity and robustness of the results.

Local context effects during emotional item directed forgetting in younger and older adults.

Science.gov (United States)

Gallant, Sara N; Dyson, Benjamin J; Yang, Lixia

2017-09-01

This paper explored the differential sensitivity young and older adults exhibit to the local context of items entering memory. We examined trial-to-trial performance during an item directed forgetting task for positive, negative, and neutral (or baseline) words each cued as either to-be-remembered (TBR) or to-be-forgotten (TBF). This allowed us to focus on how variations in emotional valence (independent of arousal) and instruction (TBR vs. TBF) of the previous item (trial n-1) impacted memory for the current item (trial n) during encoding. Different from research showing impairing effects of emotional arousal, both age groups showed a memorial boost for stimuli when preceded by items high in positive or negative valence relative to those preceded by neutral items. This advantage was particularly prominent for neutral trial n items that followed emotional items suggesting that, regardless of age, neutral memories may be strengthened by a local context that is high in valence. A trending age difference also emerged with older adults showing greater sensitivity when encoding instructions changed between trial n-1 and n. Results are discussed in light of age-related theories of cognitive and emotional processing, highlighting the need to consider the dynamic, moment-to-moment fluctuations of these systems.

Hyperspectral image segmentation using a cooperative nonparametric approach

Science.gov (United States)

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

Science.gov (United States)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Item Response Theory analysis of Fagerström Test for Cigarette Dependence.

Science.gov (United States)

Svicher, Andrea; Cosci, Fiammetta; Giannini, Marco; Pistelli, Francesco; Fagerström, Karl

2018-02-01

The Fagerström Test for Cigarette Dependence (FTCD) and the Heaviness of Smoking Index (HSI) are the gold standard measures to assess cigarette dependence. However, FTCD reliability and factor structure have been questioned and HSI psychometric properties are in need of further investigations. The present study examined the psychometrics properties of the FTCD and the HSI via the Item Response Theory. The study was a secondary analysis of data collected in 862 Italian daily smokers. Confirmatory factor analysis was run to evaluate the dimensionality of FTCD. A Grade Response Model was applied to FTCD and HSI to verify the fit to the data. Both item and test functioning were analyzed and item statistics, Test Information Function, and scale reliabilities were calculated. Mokken Scale Analysis was applied to estimate homogeneity and Loevinger's coefficients were calculated. The FTCD showed unidimensionality and homogeneity for most of the items and for the total score. It also showed high sensitivity and good reliability from medium to high levels of cigarette dependence, although problems related to some items (i.e., items 3 and 5) were evident. HSI had good homogeneity, adequate item functioning, and high reliability from medium to high levels of cigarette dependence. Significant Differential Item Functioning was found for items 1, 4, 5 of the FTCD and for both items of HSI. HSI seems highly recommended in clinical settings addressed to heavy smokers while FTCD would be better used in smokers with a level of cigarette dependence ranging between low and high. Copyright © 2017 Elsevier Ltd. All rights reserved.

STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

International Nuclear Information System (INIS)

David, Hugh

1990-01-01

1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

Non-parametric system identification from non-linear stochastic response

DEFF Research Database (Denmark)

Rüdinger, Finn; Krenk, Steen

2001-01-01

An estimation method is proposed for identification of non-linear stiffness and damping of single-degree-of-freedom systems under stationary white noise excitation. Non-parametric estimates of the stiffness and damping along with an estimate of the white noise intensity are obtained by suitable...... of the energy at mean-level crossings, which yields the damping relative to white noise intensity. Finally, an estimate of the noise intensity is extracted by estimating the absolute damping from the autocovariance functions of a set of modified phase plane variables at different energy levels. The method...

Testing a parametric function against a nonparametric alternative in IV and GMM settings

DEFF Research Database (Denmark)

Gørgens, Tue; Wurtz, Allan

This paper develops a specification test for functional form for models identified by moment restrictions, including IV and GMM settings. The general framework is one where the moment restrictions are specified as functions of data, a finite-dimensional parameter vector, and a nonparametric real ...

A simple non-parametric goodness-of-fit test for elliptical copulas

Directory of Open Access Journals (Sweden)

Jaser Miriam

2017-12-01

Full Text Available In this paper, we propose a simple non-parametric goodness-of-fit test for elliptical copulas of any dimension. It is based on the equality of Kendall’s tau and Blomqvist’s beta for all bivariate margins. Nominal level and power of the proposed test are investigated in a Monte Carlo study. An empirical application illustrates our goodness-of-fit test at work.

Methodology for the development and calibration of the SCI-QOL item banks.

Science.gov (United States)

Tulsky, David S; Kisala, Pamela A; Victorson, David; Choi, Seung W; Gershon, Richard; Heinemann, Allen W; Cella, David

2015-05-01

To develop a comprehensive, psychometrically sound, and conceptually grounded patient reported outcomes (PRO) measurement system for individuals with spinal cord injury (SCI). Individual interviews (n=44) and focus groups (n=65 individuals with SCI and n=42 SCI clinicians) were used to select key domains for inclusion and to develop PRO items. Verbatim items from other cutting-edge measurement systems (i.e. PROMIS, Neuro-QOL) were included to facilitate linkage and cross-population comparison. Items were field tested in a large sample of individuals with traumatic SCI (n=877). Dimensionality was assessed with confirmatory factor analysis. Local item dependence and differential item functioning were assessed, and items were calibrated using the item response theory (IRT) graded response model. Finally, computer adaptive tests (CATs) and short forms were administered in a new sample (n=245) to assess test-retest reliability and stability. A calibration sample of 877 individuals with traumatic SCI across five SCI Model Systems sites and one Department of Veterans Affairs medical center completed SCI-QOL items in interview format. We developed 14 unidimensional calibrated item banks and 3 calibrated scales across physical, emotional, and social health domains. When combined with the five Spinal Cord Injury--Functional Index physical function banks, the final SCI-QOL system consists of 22 IRT-calibrated item banks/scales. Item banks may be administered as CATs or short forms. Scales may be administered in a fixed-length format only. The SCI-QOL measurement system provides SCI researchers and clinicians with a comprehensive, relevant and psychometrically robust system for measurement of physical-medical, physical-functional, emotional, and social outcomes. All SCI-QOL instruments are freely available on Assessment CenterSM.

European regional efficiency and geographical externalities: a spatial nonparametric frontier analysis

Science.gov (United States)

Ramajo, Julián; Cordero, José Manuel; Márquez, Miguel Ángel

2017-10-01

This paper analyses region-level technical efficiency in nine European countries over the 1995-2007 period. We propose the application of a nonparametric conditional frontier approach to account for the presence of heterogeneous conditions in the form of geographical externalities. Such environmental factors are beyond the control of regional authorities, but may affect the production function. Therefore, they need to be considered in the frontier estimation. Specifically, a spatial autoregressive term is included as an external conditioning factor in a robust order- m model. Thus we can test the hypothesis of non-separability (the external factor impacts both the input-output space and the distribution of efficiencies), demonstrating the existence of significant global interregional spillovers into the production process. Our findings show that geographical externalities affect both the frontier level and the probability of being more or less efficient. Specifically, the results support the fact that the spatial lag variable has an inverted U-shaped non-linear impact on the performance of regions. This finding can be interpreted as a differential effect of interregional spillovers depending on the size of the neighboring economies: positive externalities for small values, possibly related to agglomeration economies, and negative externalities for high values, indicating the possibility of production congestion. Additionally, evidence of the existence of a strong geographic pattern of European regional efficiency is reported and the levels of technical efficiency are acknowledged to have converged during the period under analysis.

Nonparametric inference of network structure and dynamics

Science.gov (United States)

Peixoto, Tiago P.

The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among

Development of the PROMIS positive emotional and sensory expectancies of smoking item banks.

Science.gov (United States)

Tucker, Joan S; Shadel, William G; Edelen, Maria Orlando; Stucky, Brian D; Li, Zhen; Hansen, Mark; Cai, Li

2014-09-01

The positive emotional and sensory expectancies of cigarette smoking include improved cognitive abilities, positive affective states, and pleasurable sensorimotor sensations. This paper describes development of Positive Emotional and Sensory Expectancies of Smoking item banks that will serve to standardize the assessment of this construct among daily and nondaily cigarette smokers. Data came from daily (N = 4,201) and nondaily (N =1,183) smokers who completed an online survey. To identify a unidimensional set of items, we conducted item factor analyses, item response theory analyses, and differential item functioning analyses. Additionally, we evaluated the performance of fixed-item short forms (SFs) and computer adaptive tests (CATs) to efficiently assess the construct. Eighteen items were included in the item banks (15 common across daily and nondaily smokers, 1 unique to daily, 2 unique to nondaily). The item banks are strongly unidimensional, highly reliable (reliability = 0.95 for both), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.86). Results from simulated CATs indicated that, on average, less than 8 items are needed to assess the construct with adequate precision using the item banks. These analyses identified a new set of items that can assess the positive emotional and sensory expectancies of smoking in a reliable and standardized manner. Considerable efficiency in assessing this construct can be achieved by using the item bank SF, employing computer adaptive tests, or selecting subsets of items tailored to specific research or clinical purposes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Converging evidence for control of color-word Stroop interference at the item level.

Science.gov (United States)

Bugg, Julie M; Hutchison, Keith A

2013-04-01

Prior studies have shown that cognitive control is implemented at the list and context levels in the color-word Stroop task. At first blush, the finding that Stroop interference is reduced for mostly incongruent items as compared with mostly congruent items (i.e., the item-specific proportion congruence [ISPC] effect) appears to provide evidence for yet a third level of control, which modulates word reading at the item level. However, evidence to date favors the view that ISPC effects reflect the rapid prediction of high-contingency responses and not item-specific control. In Experiment 1, we first show that an ISPC effect is obtained when the relevant dimension (i.e., color) signals proportion congruency, a problematic pattern for theories based on differential response contingencies. In Experiment 2, we replicate and extend this pattern by showing that item-specific control settings transfer to new stimuli, ruling out alternative frequency-based accounts. In Experiment 3, we revert to the traditional design in which the irrelevant dimension (i.e., word) signals proportion congruency. Evidence for item-specific control, including transfer of the ISPC effect to new stimuli, is apparent when 4-item sets are employed but not when 2-item sets are employed. We attribute this pattern to the absence of high-contingency responses on incongruent trials in the 4-item set. These novel findings provide converging evidence for reactive control of color-word Stroop interference at the item level, reveal theoretically important factors that modulate reliance on item-specific control versus contingency learning, and suggest an update to the item-specific control account (Bugg, Jacoby, & Chanani, 2011).

An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA-seq.

Science.gov (United States)

Xu, Maoqi; Chen, Liang

2018-01-01

The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models

OpenAIRE

GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.

2008-01-01

In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.

Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches

OpenAIRE

Wang, Wenshuo; Xi, Junqiang; Zhao, Ding

2017-01-01

Analysis and recognition of driving styles are profoundly important to intelligent transportation and vehicle calibration. This paper presents a novel driving style analysis framework using the primitive driving patterns learned from naturalistic driving data. In order to achieve this, first, a Bayesian nonparametric learning method based on a hidden semi-Markov model (HSMM) is introduced to extract primitive driving patterns from time series driving data without prior knowledge of the number...

Nonparametric Change Point Diagnosis Method of Concrete Dam Crack Behavior Abnormality

OpenAIRE

Li, Zhanchao; Gu, Chongshi; Wu, Zhongru

2013-01-01

The study on diagnosis method of concrete crack behavior abnormality has always been a hot spot and difficulty in the safety monitoring field of hydraulic structure. Based on the performance of concrete dam crack behavior abnormality in parametric statistical model and nonparametric statistical model, the internal relation between concrete dam crack behavior abnormality and statistical change point theory is deeply analyzed from the model structure instability of parametric statistical model ...

The cultural fairness of the 12-item General Health Questionnaire among diverse adolescents.

Science.gov (United States)

Bowe, Anica

2017-01-01

The 12-item general health questionnaire (GHQ-12) was used in the Longitudinal Study of Young People in England (LSYPE; N = 15,770) to collect measures on adolescent mental health. Given the debate in current literature regarding the dimensionality of the GHQ-12, this study examined the cultural sensitivity of the instrument at the item level for each of the 7 major ethnic groups within the database. This study used a hybrid approach of ordinal logistic regression and item response theory (IRT) to examine the presence of differential item functioning (DIF) on the questionnaire. Results demonstrated that uniform, nonuniform, and overall DIF were present on items between White and Asian adolescents (7 items), White and Black Caribbean adolescents (1 item), and White and Black African adolescents (7 items), however all McFadden's pseudo R² effect size estimates indicated that the DIF was negligible. Overall, there were cumulative small scale level effects for the Mixed/Biracial, Asian, and Black African groups, but in each case the bias was only marginal. Findings demonstrate that the GHQ-12 can be considered culturally sensitive for adolescents from diverse ethnic groups in England, but follow-up studies are necessary. Implications for future education and health policies as well as the use of IR-based approaches for psychological instruments are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A non-parametric framework for estimating threshold limit values

Directory of Open Access Journals (Sweden)

Ulm Kurt

2005-11-01

Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

Evaluation of the Psychometric Properties of the Asian Adolescent Depression Scale and Construction of a Short Form: An Item Response Theory Analysis.

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Lo, Barbara Chuen Yee; Zhao, Yue; Kwok, Alice Wai Yee; Chan, Wai; Chan, Calais Kin Yuen

2017-07-01

The present study applied item response theory to examine the psychometric properties of the Asian Adolescent Depression Scale and to construct a short form among 1,084 teenagers recruited from secondary schools in Hong Kong. Findings suggested that some items of the full form reflected higher levels of severity and were more discriminating than others, and the Asian Adolescent Depression Scale was useful in measuring a broad range of depressive severity in community youths. Differential item functioning emerged in several items where females reported higher depressive severity than males. In the short form construction, preliminary validation suggested that, relative to the 20-item full form, our derived short form offered significantly greater diagnostic performance and stronger discriminatory ability in differentiating depressed and nondepressed groups, and simultaneously maintained adequate measurement precision with a reduced response burden in assessing depression in the Asian adolescents. Cultural variance in depressive symptomatology and clinical implications are discussed.

Development and psychometric characteristics of the SCI-QOL Ability to Participate and Satisfaction with Social Roles and Activities item banks and short forms.

Science.gov (United States)

Heinemann, Allen W; Kisala, Pamela A; Hahn, Elizabeth A; Tulsky, David S

2015-05-01

To develop a spinal cord injury (SCI)-focused version of PROMIS and Neuro-QOL social domain item banks; evaluate the psychometric properties of items developed for adults with SCI; and report information to facilitate clinical and research use. We used a mixed-methods design to develop and evaluate Ability to Participate in Social Roles and Activities and Satisfaction with Social Roles and Activities items. Focus groups helped define the constructs; cognitive interviews helped revise items; and confirmatory factor analysis and item response theory methods helped calibrate item banks and evaluate differential item functioning related to demographic and injury characteristics. Five SCI Model System sites and one Veterans Administration medical center. The calibration sample consisted of 641 individuals; a reliability sample consisted of 245 individuals residing in the community. A subset of 27 Ability to Participate and 35 Satisfaction items demonstrated good measurement properties and negligible differential item functioning related to demographic and injury characteristics. The SCI-specific measures correlate strongly with the PROMIS and Neuro-QOL versions. Ten item short forms correlate >0.96 with the full banks. Variable-length CATs with a minimum of 4 items, variable-length CATs with a minimum of 8 items, fixed-length CATs of 10 items, and the 10-item short forms demonstrate construct coverage and measurement error that is comparable to the full item bank. The Ability to Participate and Satisfaction with Social Roles and Activities CATs and short forms demonstrate excellent psychometric properties and are suitable for clinical and research applications.

Development of a subjective cognitive decline questionnaire using item response theory: a pilot study.

Science.gov (United States)

Gifford, Katherine A; Liu, Dandan; Romano, Raymond; Jones, Richard N; Jefferson, Angela L

2015-12-01

Subjective cognitive decline (SCD) may indicate unhealthy cognitive changes, but no standardized SCD measurement exists. This pilot study aims to identify reliable SCD questions. 112 cognitively normal (NC, 76±8 years, 63% female), 43 mild cognitive impairment (MCI; 77±7 years, 51% female), and 33 diagnostically ambiguous participants (79±9 years, 58% female) were recruited from a research registry and completed 57 self-report SCD questions. Psychometric methods were used for item-reduction. Factor analytic models assessed unidimensionality of the latent trait (SCD); 19 items were removed with extreme response distribution or trait-fit. Item response theory (IRT) provided information about question utility; 17 items with low information were dropped. Post-hoc simulation using computerized adaptive test (CAT) modeling selected the most commonly used items (n=9 of 21 items) that represented the latent trait well (r=0.94) and differentiated NC from MCI participants (F(1,146)=8.9, p=0.003). Item response theory and computerized adaptive test modeling identified nine reliable SCD items. This pilot study is a first step toward refining SCD assessment in older adults. Replication of these findings and validation with Alzheimer's disease biomarkers will be an important next step for the creation of a SCD screener.

Assessment of the psychometrics of a PROMIS item bank: self-efficacy for managing daily activities.

Science.gov (United States)

Hong, Ickpyo; Velozo, Craig A; Li, Chih-Ying; Romero, Sergio; Gruber-Baldini, Ann L; Shulman, Lisa M

2016-09-01

The aim of this study is to investigate the psychometrics of the Patient-Reported Outcomes Measurement Information System self-efficacy for managing daily activities item bank. The item pool was field tested on a sample of 1087 participants via internet (n = 250) and in-clinic (n = 837) surveys. All participants reported having at least one chronic health condition. The 35 item pool was investigated for dimensionality (confirmatory factor analyses, CFA and exploratory factor analysis, EFA), item-total correlations, local independence, precision, and differential item functioning (DIF) across gender, race, ethnicity, age groups, data collection modes, and neurological chronic conditions (McFadden Pseudo R (2) less than 10 %). The item pool met two of the four CFA fit criteria (CFI = 0.952 and SRMR = 0.07). EFA analysis found a dominant first factor (eigenvalue = 24.34) and the ratio of first to second eigenvalue was 12.4. The item pool demonstrated good item-total correlations (0.59-0.85) and acceptable internal consistency (Cronbach's alpha = 0.97). The item pool maintained its precision (reliability over 0.90) across a wide range of theta (3.70), and there was no significant DIF. The findings indicated the item pool has sound psychometric properties and the test items are eligible for development of computerized adaptive testing and short forms.

Does Private Tutoring Work? The Effectiveness of Private Tutoring: A Nonparametric Bounds Analysis

Science.gov (United States)

Hof, Stefanie

2014-01-01

Private tutoring has become popular throughout the world. However, evidence for the effect of private tutoring on students' academic outcome is inconclusive; therefore, this paper presents an alternative framework: a nonparametric bounds method. The present examination uses, for the first time, a large representative data-set in a European setting…

Data analysis with small samples and non-normal data nonparametrics and other strategies

CERN Document Server

Siebert, Carl F

2017-01-01

Written in everyday language for non-statisticians, this book provides all the information needed to successfully conduct nonparametric analyses. This ideal reference book provides step-by-step instructions to lead the reader through each analysis, screenshots of the software and output, and case scenarios to illustrate of all the analytic techniques.

Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach

International Nuclear Information System (INIS)

Wang, H.; Ang, B.W.; Wang, Q.W.; Zhou, P.

2017-01-01

Evaluating economy-wide energy performance is an integral part of assessing the effectiveness of a country's energy efficiency policy. Non-parametric frontier approach has been widely used by researchers for such a purpose. This paper proposes an extended non-parametric frontier approach to studying economy-wide energy efficiency and productivity performances by accounting for sectoral heterogeneity. Relevant techniques in index number theory are incorporated to quantify the driving forces behind changes in the economy-wide energy productivity index. The proposed approach facilitates flexible modelling of different sectors' production processes, and helps to examine sectors' impact on the aggregate energy performance. A case study of China's economy-wide energy efficiency and productivity performances in its 11th five-year plan period (2006–2010) is presented. It is found that sectoral heterogeneities in terms of energy performance are significant in China. Meanwhile, China's economy-wide energy productivity increased slightly during the study period, mainly driven by the technical efficiency improvement. A number of other findings have also been reported. - Highlights: • We model economy-wide energy performance by considering sectoral heterogeneity. • The proposed approach can identify sectors' impact on the aggregate energy performance. • Obvious sectoral heterogeneities are identified in evaluating China's energy performance.

Effects of Learning Experience on Forgetting Rates of Item and Associative Memories

Science.gov (United States)

Yang, Jiongjiong; Zhan, Lexia; Wang, Yingying; Du, Xiaoya; Zhou, Wenxi; Ning, Xueling; Sun, Qing; Moscovitch, Morris

2016-01-01

Are associative memories forgotten more quickly than item memories, and does the level of original learning differentially influence forgetting rates? In this study, we addressed these questions by having participants learn single words and word pairs once (Experiment 1), three times (Experiment 2), and six times (Experiment 3) in a massed…

The effects of value on context-item associative memory in younger and older adults.

Science.gov (United States)

Hennessee, Joseph P; Knowlton, Barbara J; Castel, Alan D

2018-02-01

Valuable items are often remembered better than items that are less valuable by both older and younger adults, but older adults typically show deficits in binding. Here, we examine whether value affects the quality of recognition memory and the binding of incidental details to valuable items. In Experiment 1, participants learned English words each associated with a point-value they earned for correct recognition with the goal of maximizing their score. In Experiment 2, value was manipulated by presenting items that were either congruent or incongruent with an imagined state of physiological need (e.g., hunger). In Experiment 1, point-value was associated with enhanced recollection in both age groups. Memory for the color associated with the word was in fact reduced for high-value recollected items compared with low-value recollected items, suggesting value selectively enhances binding of task-relevant details. In Experiment 2, memory for learned images was enhanced by value in both age groups. However, value differentially enhanced binding of an imagined context to the item in younger and older adults, with a strong trend for increased binding in younger adults only. These findings suggest that value enhances episodic encoding in both older and younger adults but that binding of associated details may be reduced for valuable items compared to less valuable items, particularly in older adults. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Calibration of the PROMIS physical function item bank in Dutch patients with rheumatoid arthritis.

Directory of Open Access Journals (Sweden)

Martijn A H Oude Voshaar

Full Text Available OBJECTIVE: To calibrate the Dutch-Flemish version of the PROMIS physical function (PF item bank in patients with rheumatoid arthritis (RA and to evaluate cross-cultural measurement equivalence with US general population and RA data. METHODS: Data were collected from RA patients enrolled in the Dutch DREAM registry. An incomplete longitudinal anchored design was used where patients completed all 121 items of the item bank over the course of three waves of data collection. Item responses were fit to a generalized partial credit model adapted for longitudinal data and the item parameters were examined for differential item functioning (DIF across country, age, and sex. RESULTS: In total, 690 patients participated in the study at time point 1 (T2, N = 489; T3, N = 311. The item bank could be successfully fitted to a generalized partial credit model, with the number of misfitting items falling within acceptable limits. Seven items demonstrated DIF for sex, while 5 items showed DIF for age in the Dutch RA sample. Twenty-five (20% items were flagged for cross-cultural DIF compared to the US general population. However, the impact of observed DIF on total physical function estimates was negligible. DISCUSSION: The results of this study showed that the PROMIS PF item bank adequately fit a unidimensional IRT model which provides support for applications that require invariant estimates of physical function, such as computer adaptive testing and targeted short forms. More studies are needed to further investigate the cross-cultural applicability of the US-based PROMIS calibration and standardized metric.

Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

Science.gov (United States)

Siciliani, Luigi

2006-01-01

Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

Categorical and nonparametric data analysis choosing the best statistical technique

CERN Document Server

Nussbaum, E Michael

2014-01-01

Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so readers can explain

Detecting Differential Person Functioning in Emotional Intelligence

Science.gov (United States)

Alsmadi, Yahia M.; Alsmadi, Abdalla A.

2009-01-01

Differential Item Functioning (DIF) is a widely used term in test development literature. It is very important to analyze test's data for DIF because It is a serious threat to validity. If the same data matrix was transposed, similar analysis can be carried for Differential Person Functioning (DPF). The purpose of this paper is to introduce and…

Adaptive nonparametric estimation for L\\'evy processes observed at low frequency

OpenAIRE

Kappus, Johanna

2013-01-01

This article deals with adaptive nonparametric estimation for L\\'evy processes observed at low frequency. For general linear functionals of the L\\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of convergence under regularity assumptions. Our focus lies on the adaptive choice of the bandwidth, using model selection techniques. We face here a non-standard problem of model selection with unknown variance. A new approach towards this problem is proposed, ...

A nonparametric statistical method for determination of a confidence interval for the mean of a set of results obtained in a laboratory intercomparison

International Nuclear Information System (INIS)

Veglia, A.

1981-08-01

In cases where sets of data are obviously not normally distributed, the application of a nonparametric method for the estimation of a confidence interval for the mean seems to be more suitable than some other methods because such a method requires few assumptions about the population of data. A two-step statistical method is proposed which can be applied to any set of analytical results: elimination of outliers by a nonparametric method based on Tchebycheff's inequality, and determination of a confidence interval for the mean by a non-parametric method based on binominal distribution. The method is appropriate only for samples of size n>=10

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

Science.gov (United States)

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Solving Differential Equations Analytically. Elementary Differential Equations. Modules and Monographs in Undergraduate Mathematics and Its Applications Project. UMAP Unit 335.

Science.gov (United States)

Goldston, J. W.

This unit introduces analytic solutions of ordinary differential equations. The objective is to enable the student to decide whether a given function solves a given differential equation. Examples of problems from biology and chemistry are covered. Problem sets, quizzes, and a model exam are included, and answers to all items are provided. The…

Testing the Item-Order Account of Design Effects Using the Production Effect

Science.gov (United States)

Jonker, Tanya R.; Levene, Merrick; MacLeod, Colin M.

2014-01-01

A number of memory phenomena evident in recall in within-subject, mixed-lists designs are reduced or eliminated in between-subject, pure-list designs. The item-order account (McDaniel & Bugg, 2008) proposes that differential retention of order information might underlie this pattern. According to this account, order information may be encoded…

Distinguishing Differential Testlet Functioning from Differential Bundle Functioning Using the Multilevel Measurement Model

Science.gov (United States)

Beretvas, S. Natasha; Walker, Cindy M.

2012-01-01

This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…

Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

Science.gov (United States)

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-03-12

Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

DEFF Research Database (Denmark)

Tan, Qihua; Thomassen, Mads; Burton, Mark

2017-01-01

the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

The differential item functioning and structural equivalence of a nonverbal cognitive ability test for five language groups

Directory of Open Access Journals (Sweden)

Pieter Schaap

2011-10-01

Research purpose: The aim of the study was to determine the differential item functioning (DIF and structural equivalence of a nonverbal cognitive ability test (the PiB/SpEEx Observance test [401] for five South African language groups. Motivation for study: Cultural and language group sensitive tests can lead to unfair discrimination and is a contentious workplace issue in South Africa today. Misconceptions about psychometric testing in industry can cause tests to lose credibility if industries do not use a scientifically sound test-by-test evaluation approach. Research design, approach and method: The researcher used a quasi-experimental design and factor analytic and logistic regression techniques to meet the research aims. The study used a convenience sample drawn from industry and an educational institution. Main findings: The main findings of the study show structural equivalence of the test at a holistic level and nonsignificant DIF effect sizes for most of the comparisons that the researcher made. Practical/managerial implications: This research shows that the PIB/SpEEx Observance Test (401 is not completely language insensitive. One should see it rather as a language-reduced test when people from different language groups need testing. Contribution/value-add: The findings provide supporting evidence that nonverbal cognitive tests are plausible alternatives to verbal tests when one compares people from different language groups.

MEASURING DARK MATTER PROFILES NON-PARAMETRICALLY IN DWARF SPHEROIDALS: AN APPLICATION TO DRACO

International Nuclear Information System (INIS)

Jardel, John R.; Gebhardt, Karl; Fabricius, Maximilian H.; Williams, Michael J.; Drory, Niv

2013-01-01

We introduce a novel implementation of orbit-based (or Schwarzschild) modeling that allows dark matter density profiles to be calculated non-parametrically in nearby galaxies. Our models require no assumptions to be made about velocity anisotropy or the dark matter profile. The technique can be applied to any dispersion-supported stellar system, and we demonstrate its use by studying the Local Group dwarf spheroidal galaxy (dSph) Draco. We use existing kinematic data at larger radii and also present 12 new radial velocities within the central 13 pc obtained with the VIRUS-W integral field spectrograph on the 2.7 m telescope at McDonald Observatory. Our non-parametric Schwarzschild models find strong evidence that the dark matter profile in Draco is cuspy for 20 ≤ r ≤ 700 pc. The profile for r ≥ 20 pc is well fit by a power law with slope α = –1.0 ± 0.2, consistent with predictions from cold dark matter simulations. Our models confirm that, despite its low baryon content relative to other dSphs, Draco lives in a massive halo.

Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements

KAUST Repository

Ryu, Duchwan

2010-09-28

We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.

Lawton IADL scale in dementia: can item response theory make it more informative?

Science.gov (United States)

McGrory, Sarah; Shenkin, Susan D; Austin, Elizabeth J; Starr, John M

2014-07-01

impairment of functional abilities represents a crucial component of dementia diagnosis. Current functional measures rely on the traditional aggregate method of summing raw scores. While this summary score provides a quick representation of a person's ability, it disregards useful information on the item level. to use item response theory (IRT) methods to increase the interpretive power of the Lawton Instrumental Activities of Daily Living (IADL) scale by establishing a hierarchy of item 'difficulty' and 'discrimination'. this cross-sectional study applied IRT methods to the analysis of IADL outcomes. Participants were 202 members of the Scottish Dementia Research Interest Register (mean age = 76.39, range = 56-93, SD = 7.89 years) with complete itemised data available. a Mokken scale with good reliability (Molenaar Sijtsama statistic 0.79) was obtained, satisfying the IRT assumption that the items comprise a single unidimensional scale. The eight items in the scale could be placed on a hierarchy of 'difficulty' (H coefficient = 0.55), with 'Shopping' being the most 'difficult' item and 'Telephone use' being the least 'difficult' item. 'Shopping' was the most discriminatory item differentiating well between patients of different levels of ability. IRT methods are capable of providing more information about functional impairment than a summed score. 'Shopping' and 'Telephone use' were identified as items that reveal key information about a patient's level of ability, and could be useful screening questions for clinicians. © The Author 2013. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@ oup.com.

Panel data nonparametric estimation of production risk and risk preferences

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

approaches for obtaining firm-specific measures of risk attitudes. We found that Polish dairy farmers are risk averse regarding production risk and price uncertainty. According to our results, Polish dairy farmers perceive the production risk as being more significant than the risk related to output price......We apply nonparametric panel data kernel regression to investigate production risk, out-put price uncertainty, and risk attitudes of Polish dairy farms based on a firm-level unbalanced panel data set that covers the period 2004–2010. We compare different model specifications and different...

Evaluation of item candidates for a diabetic retinopathy quality of life item bank.

Science.gov (United States)

Fenwick, Eva K; Pesudovs, Konrad; Khadka, Jyoti; Rees, Gwyn; Wong, Tien Y; Lamoureux, Ecosse L

2013-09-01

We are developing an item bank assessing the impact of diabetic retinopathy (DR) on quality of life (QoL) using a rigorous multi-staged process combining qualitative and quantitative methods. We describe here the first two qualitative phases: content development and item evaluation. After a comprehensive literature review, items were generated from four sources: (1) 34 previously validated patient-reported outcome measures; (2) five published qualitative articles; (3) eight focus groups and 18 semi-structured interviews with 57 DR patients; and (4) seven semi-structured interviews with diabetes or ophthalmic experts. Items were then evaluated during 3 stages, namely binning (grouping) and winnowing (reduction) based on key criteria and panel consensus; development of item stems and response options; and pre-testing of items via cognitive interviews with patients. The content development phase yielded 1,165 unique items across 7 QoL domains. After 3 sessions of binning and winnowing, items were reduced to a minimally representative set (n = 312) across 9 domains of QoL: visual symptoms; ocular surface symptoms; activity limitation; mobility; emotional; health concerns; social; convenience; and economic. After 8 cognitive interviews, 42 items were amended resulting in a final set of 314 items. We have employed a systematic approach to develop items for a DR-specific QoL item bank. The psychometric properties of the nine QoL subscales will be assessed using Rasch analysis. The resulting validated item bank will allow clinicians and researchers to better understand the QoL impact of DR and DR therapies from the patient's perspective.

Measuring everyday functional competence using the Rasch assessment of everyday activity limitations (REAL) item bank

NARCIS (Netherlands)

Oude Voshaar, Martijn A.H.; Ten Klooster, Peter M.; Vonkeman, Harald E.; van de Laar, Mart A.F.J.

2017-01-01

Objective: Traditional patient-reported physical function instruments often poorly differentiate patients with mild-to-moderate disability. We describe the development and psychometric evaluation of a generic item bank for measuring everyday activity limitations in outpatient populations. Study

A signal detection-item response theory model for evaluating neuropsychological measures.

Science.gov (United States)

Thomas, Michael L; Brown, Gregory G; Gur, Ruben C; Moore, Tyler M; Patt, Virginie M; Risbrough, Victoria B; Baker, Dewleen G

2018-02-05

Models from signal detection theory are commonly used to score neuropsychological test data, especially tests of recognition memory. Here we show that certain item response theory models can be formulated as signal detection theory models, thus linking two complementary but distinct methodologies. We then use the approach to evaluate the validity (construct representation) of commonly used research measures, demonstrate the impact of conditional error on neuropsychological outcomes, and evaluate measurement bias. Signal detection-item response theory (SD-IRT) models were fitted to recognition memory data for words, faces, and objects. The sample consisted of U.S. Infantry Marines and Navy Corpsmen participating in the Marine Resiliency Study. Data comprised item responses to the Penn Face Memory Test (PFMT; N = 1,338), Penn Word Memory Test (PWMT; N = 1,331), and Visual Object Learning Test (VOLT; N = 1,249), and self-report of past head injury with loss of consciousness. SD-IRT models adequately fitted recognition memory item data across all modalities. Error varied systematically with ability estimates, and distributions of residuals from the regression of memory discrimination onto self-report of past head injury were positively skewed towards regions of larger measurement error. Analyses of differential item functioning revealed little evidence of systematic bias by level of education. SD-IRT models benefit from the measurement rigor of item response theory-which permits the modeling of item difficulty and examinee ability-and from signal detection theory-which provides an interpretive framework encompassing the experimentally validated constructs of memory discrimination and response bias. We used this approach to validate the construct representation of commonly used research measures and to demonstrate how nonoptimized item parameters can lead to erroneous conclusions when interpreting neuropsychological test data. Future work might include the

Nonparametric Estimation of Distributions in Random Effects Models

KAUST Repository

Hart, Jeffrey D.

2011-01-01

We propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.

Multi-Directional Non-Parametric Analysis of Agricultural Efficiency

DEFF Research Database (Denmark)

Balezentis, Tomas

This thesis seeks to develop methodologies for assessment of agricultural efficiency and employ them to Lithuanian family farms. In particular, we focus on three particular objectives throughout the research: (i) to perform a fully non-parametric analysis of efficiency effects, (ii) to extend...... to the Multi-Directional Efficiency Analysis approach when the proposed models were employed to analyse empirical data of Lithuanian family farm performance, we saw substantial differences in efficiencies associated with different inputs. In particular, assets appeared to be the least efficiently used input...... relative to labour, intermediate consumption and land (in some cases land was not treated as a discretionary input). These findings call for further research on relationships among financial structure, investment decisions, and efficiency in Lithuanian family farms. Application of different techniques...

The role of attention in item-item binding in visual working memory.

Science.gov (United States)

Peterson, Dwight J; Naveh-Benjamin, Moshe

2017-09-01

An important yet unresolved question regarding visual working memory (VWM) relates to whether or not binding processes within VWM require additional attentional resources compared with processing solely the individual components comprising these bindings. Previous findings indicate that binding of surface features (e.g., colored shapes) within VWM is not demanding of resources beyond what is required for single features. However, it is possible that other types of binding, such as the binding of complex, distinct items (e.g., faces and scenes), in VWM may require additional resources. In 3 experiments, we examined VWM item-item binding performance under no load, articulatory suppression, and backward counting using a modified change detection task. Binding performance declined to a greater extent than single-item performance under higher compared with lower levels of concurrent load. The findings from each of these experiments indicate that processing item-item bindings within VWM requires a greater amount of attentional resources compared with single items. These findings also highlight an important distinction between the role of attention in item-item binding within VWM and previous studies of long-term memory (LTM) where declines in single-item and binding test performance are similar under divided attention. The current findings provide novel evidence that the specific type of binding is an important determining factor regarding whether or not VWM binding processes require attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.

Science.gov (United States)

Wang, Tianyu; Nabavi, Sheida

2018-04-24

Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote the development of new methods for identifying differentially expressed (DE) genes. In this study, we proposed a new method, SigEMD, that combines a data imputation approach, a logistic regression model and a nonparametric method based on the Earth Mover's Distance, to precisely and efficiently identify DE genes in scRNAseq data. The regression model and data imputation are used to reduce the impact of large amounts of zero counts, and the nonparametric method is used to improve the sensitivity of detecting DE genes from multimodal scRNAseq data. By additionally employing gene interaction network information to adjust the final states of DE genes, we further reduce the false positives of calling DE genes. We used simulated datasets and real datasets to evaluate the detection accuracy of the proposed method and to compare its performance with those of other differential expression analysis methods. Results indicate that the proposed method has an overall powerful performance in terms of precision in detection, sensitivity, and specificity. Copyright © 2018 Elsevier Inc. All rights reserved.

A multitemporal and non-parametric approach for assessing the impacts of drought on vegetation greenness

DEFF Research Database (Denmark)

Carrao, Hugo; Sepulcre, Guadalupe; Horion, Stéphanie Marie Anne F

2013-01-01

This study evaluates the relationship between the frequency and duration of meteorological droughts and the subsequent temporal changes on the quantity of actively photosynthesizing biomass (greenness) estimated from satellite imagery on rainfed croplands in Latin America. An innovative non-parametric...... and non-supervised approach, based on the Fisher-Jenks optimal classification algorithm, is used to identify multi-scale meteorological droughts on the basis of empirical cumulative distributions of 1, 3, 6, and 12-monthly precipitation totals. As input data for the classifier, we use the gridded GPCC...... for the period between 1998 and 2010. The time-series analysis of vegetation greenness is performed during the growing season with a non-parametric method, namely the seasonal Relative Greenness (RG) of spatially accumulated fAPAR. The Global Land Cover map of 2000 and the GlobCover maps of 2005/2006 and 2009...

The Effects of Item Format and Cognitive Domain on Students' Science Performance in TIMSS 2011

Science.gov (United States)

Liou, Pey-Yan; Bulut, Okan

2017-12-01

The purpose of this study was to examine eighth-grade students' science performance in terms of two test design components, item format, and cognitive domain. The portion of Taiwanese data came from the 2011 administration of the Trends in International Mathematics and Science Study (TIMSS), one of the major international large-scale assessments in science. The item difficulty analysis was initially applied to show the proportion of correct items. A regression-based cumulative link mixed modeling (CLMM) approach was further utilized to estimate the impact of item format, cognitive domain, and their interaction on the students' science scores. The results of the proportion-correct statistics showed that constructed-response items were more difficult than multiple-choice items, and that the reasoning cognitive domain items were more difficult compared to the items in the applying and knowing domains. In terms of the CLMM results, students tended to obtain higher scores when answering constructed-response items as well as items in the applying cognitive domain. When the two predictors and the interaction term were included together, the directions and magnitudes of the predictors on student science performance changed substantially. Plausible explanations for the complex nature of the effects of the two test-design predictors on student science performance are discussed. The results provide practical, empirical-based evidence for test developers, teachers, and stakeholders to be aware of the differential function of item format, cognitive domain, and their interaction in students' science performance.

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

Science.gov (United States)

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Bayesian nonparametric approach to causal inference on quantiles.

Science.gov (United States)

Xu, Dandan; Daniels, Michael J; Winterstein, Almut G

2018-02-25

We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.

Debt and growth: A non-parametric approach

Science.gov (United States)

Brida, Juan Gabriel; Gómez, David Matesanz; Seijas, Maria Nela

2017-11-01

In this study, we explore the dynamic relationship between public debt and economic growth by using a non-parametric approach based on data symbolization and clustering methods. The study uses annual data of general government consolidated gross debt-to-GDP ratio and gross domestic product for sixteen countries between 1977 and 2015. Using symbolic sequences, we introduce a notion of distance between the dynamical paths of different countries. Then, a Minimal Spanning Tree and a Hierarchical Tree are constructed from time series to help detecting the existence of groups of countries sharing similar economic performance. The main finding of the study appears for the period 2008-2016 when several countries surpassed the 90% debt-to-GDP threshold. During this period, three groups (clubs) of countries are obtained: high, mid and low indebted countries, suggesting that the employed debt-to-GDP threshold drives economic dynamics for the selected countries.

Bayesian Nonparametric Longitudinal Data Analysis.

Science.gov (United States)

Quintana, Fernando A; Johnson, Wesley O; Waetjen, Elaine; Gold, Ellen

2016-01-01

Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.

Calibration of the Dutch-Flemish PROMIS Pain Behavior item bank in patients with chronic pain.

Science.gov (United States)

Crins, M H P; Roorda, L D; Smits, N; de Vet, H C W; Westhovens, R; Cella, D; Cook, K F; Revicki, D; van Leeuwen, J; Boers, M; Dekker, J; Terwee, C B

2016-02-01

The aims of the current study were to calibrate the item parameters of the Dutch-Flemish PROMIS Pain Behavior item bank using a sample of Dutch patients with chronic pain and to evaluate cross-cultural validity between the Dutch-Flemish and the US PROMIS Pain Behavior item banks. Furthermore, reliability and construct validity of the Dutch-Flemish PROMIS Pain Behavior item bank were evaluated. The 39 items in the bank were completed by 1042 Dutch patients with chronic pain. To evaluate unidimensionality, a one-factor confirmatory factor analysis (CFA) was performed. A graded response model (GRM) was used to calibrate the items. To evaluate cross-cultural validity, Differential item functioning (DIF) for language (Dutch vs. English) was evaluated. Reliability of the item bank was also examined and construct validity was studied using several legacy instruments, e.g. the Roland Morris Disability Questionnaire. CFA supported the unidimensionality of the Dutch-Flemish PROMIS Pain Behavior item bank (CFI = 0.960, TLI = 0.958), the data also fit the GRM, and demonstrated good coverage across the pain behavior construct (threshold parameters range: -3.42 to 3.54). Analysis showed good cross-cultural validity (only six DIF items), reliability (Cronbach's α = 0.95) and construct validity (all correlations ≥0.53). The Dutch-Flemish PROMIS Pain Behavior item bank was found to have good cross-cultural validity, reliability and construct validity. The development of the Dutch-Flemish PROMIS Pain Behavior item bank will serve as the basis for Dutch-Flemish PROMIS short forms and computer adaptive testing (CAT). © 2015 European Pain Federation - EFIC®

Análise do funcionamento diferencial dos itens do Exame Nacional do Estudante (ENADE de psicologia de 2006 Differential item functioning of the national student exam for psychology (ENADE 2006

Directory of Open Access Journals (Sweden)

Ricardo Primi

2010-12-01

Full Text Available Parte do Sistema Nacional de Avaliação das Instituições de Educação Superior considera o desempenho dos estudantes por meio do ENADE. Neste artigo efetuou-se uma análise dos itens da prova do ENADE de psicologia aplicada em 2006 tentando-se detectar itens com funcionamento diferencial (DIF, isto é, itens com problema de equivalência ao medir ingressantes e concluintes e estudantes de instituições públicas e privada. Analisou-se uma amostra de 26.613 estudantes ingressantes e concluintes representativa de todos os cursos do país. Empregou-se a análise de Rasch e regressão logística para se detectar o DIF. Onze itens dos 30 que compunham a prova apresentaram DIF. Dois tipos de DIF ocorreram, um tipo em itens com baixa discriminação e outro em itens com alta discriminação. O subgrupo mais relevante tende a favorecer alunos de instituições públicas. Discute-se também a questão da discriminação elevada como indicativo de DIF.Part of the National Assessment of Institutions of Higher Education considers student performance through ENADE. In this article we performed differential item function analysis of the ENADE that took place in 2006 trying to detect items with problems in measurement equivalence in the assessment of freshman and senior students and from public and private institutions. We analyzed a sample of 26,613 freshmen and seniors representative of all the courses in the country. We used the Rasch analysis and logistic regression to detect DIF. Eleven of the 30 items composing the test showed DIF. Two types of DIF were observed, one occurring in less discriminating items and the other in more discriminating items. The most relevant subgroup of items tends to favor students from public institutions. We also discuss the issue of discrimination parameter being an indicator of DIF.

Using item response theory to address vulnerabilities in FFQ.

Science.gov (United States)

Kazman, Josh B; Scott, Jonathan M; Deuster, Patricia A

2017-09-01

The limitations for self-reporting of dietary patterns are widely recognised as a major vulnerability of FFQ and the dietary screeners/scales derived from FFQ. Such instruments can yield inconsistent results to produce questionable interpretations. The present article discusses the value of psychometric approaches and standards in addressing these drawbacks for instruments used to estimate dietary habits and nutrient intake. We argue that a FFQ or screener that treats diet as a 'latent construct' can be optimised for both internal consistency and the value of the research results. Latent constructs, a foundation for item response theory (IRT)-based scales (e.g. Patient Reported Outcomes Measurement Information System) are typically introduced in the design stage of an instrument to elicit critical factors that cannot be observed or measured directly. We propose an iterative approach that uses such modelling to refine FFQ and similar instruments. To that end, we illustrate the benefits of psychometric modelling by using items and data from a sample of 12 370 Soldiers who completed the 2012 US Army Global Assessment Tool (GAT). We used factor analysis to build the scale incorporating five out of eleven survey items. An IRT-driven assessment of response category properties indicates likely problems in the ordering or wording of several response categories. Group comparisons, examined with differential item functioning (DIF), provided evidence of scale validity across each Army sub-population (sex, service component and officer status). Such an approach holds promise for future FFQ.

Do Self Concept Tests Test Self Concept? An Evaluation of the Validity of Items on the Piers Harris and Coopersmith Measures.

Science.gov (United States)

Lynch, Mervin D.; Chaves, John

Items from Peirs-Harris and Coopersmith self-concept tests were evaluated against independent measures on three self-constructs, idealized, empathic, and worth. Construct measurements were obtained with the semantic differential and D statistic. Ratings were obtained from 381 children, grades 4-6. For each test, item ratings and construct measures…

The Protective Behavioral Strategies for Marijuana Scale: Further examination using item response theory.

Science.gov (United States)

Pedersen, Eric R; Huang, Wenjing; Dvorak, Robert D; Prince, Mark A; Hummer, Justin F

2017-08-01

Given recent state legislation legalizing marijuana for recreational purposes and majority popular opinion favoring these laws, we developed the Protective Behavioral Strategies for Marijuana scale (PBSM) to identify strategies that may mitigate the harms related to marijuana use among those young people who choose to use the drug. In the current study, we expand on the initial exploratory study of the PBSM to further validate the measure with a large and geographically diverse sample (N = 2,117; 60% women, 30% non-White) of college students from 11 different universities across the United States. We sought to develop a psychometrically sound item bank for the PBSM and to create a short assessment form that minimizes respondent burden and time. Quantitative item analyses, including exploratory and confirmatory factor analyses with item response theory (IRT) and evaluation of differential item functioning (DIF), revealed an item bank of 36 items that was examined for unidimensionality and good content coverage, as well as a short form of 17 items that is free of bias in terms of gender (men vs. women), race (White vs. non-White), ethnicity (Hispanic vs. non-Hispanic), and recreational marijuana use legal status (state recreational marijuana was legal for 25.5% of participants). We also provide a scoring table for easy transformation from sum scores to IRT scale scores. The PBSM item bank and short form associated strongly and negatively with past month marijuana use and consequences. The measure may be useful to researchers and clinicians conducting intervention and prevention programs with young adults. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The comparability of English, French and Dutch scores on the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F: an assessment of differential item functioning in patients with systemic sclerosis.

Directory of Open Access Journals (Sweden)

Linda Kwakkenbos

Full Text Available The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F is commonly used to assess fatigue in rheumatic diseases, and has shown to discriminate better across levels of the fatigue spectrum than other commonly used measures. The aim of this study was to assess the cross-language measurement equivalence of the English, French, and Dutch versions of the FACIT-F in systemic sclerosis (SSc patients.The FACIT-F was completed by 871 English-speaking Canadian, 238 French-speaking Canadian and 230 Dutch SSc patients. Confirmatory factor analysis was used to assess the factor structure in the three samples. The Multiple-Indicator Multiple-Cause (MIMIC model was utilized to assess differential item functioning (DIF, comparing English versus French and versus Dutch patient responses separately.A unidimensional factor model showed good fit in all samples. Comparing French versus English patients, statistically significant, but small-magnitude DIF was found for 3 of 13 items. French patients had 0.04 of a standard deviation (SD lower latent fatigue scores than English patients and there was an increase of only 0.03 SD after accounting for DIF. For the Dutch versus English comparison, 4 items showed small, but statistically significant, DIF. Dutch patients had 0.20 SD lower latent fatigue scores than English patients. After correcting for DIF, there was a reduction of 0.16 SD in this difference.There was statistically significant DIF in several items, but the overall effect on fatigue scores was minimal. English, French and Dutch versions of the FACIT-F can be reasonably treated as having equivalent scoring metrics.

The Role of Medial Temporal Lobe Regions in Incidental and Intentional Retrieval of Item and Relational Information in Aging.

Science.gov (United States)

Wang, Wei-Chun; Giovanello, Kelly S

2016-06-01

Considerable neuropsychological and neuroimaging work indicates that the medial temporal lobes are critical for both item and relational memory retrieval. However, there remain outstanding issues in the literature, namely the extent to which medial temporal lobe regions are differentially recruited during incidental and intentional retrieval of item and relational information, and the extent to which aging may affect these neural substrates. The current fMRI study sought to address these questions; participants incidentally encoded word pairs embedded in sentences and incidental item and relational retrieval were assessed through speeded reading of intact, rearranged, and new word-pair sentences, while intentional item and relational retrieval were assessed through old/new associative recognition of a separate set of intact, rearranged, and new word pairs. Results indicated that, in both younger and older adults, anterior hippocampus and perirhinal cortex indexed incidental and intentional item retrieval in the same manner. In contrast, posterior hippocampus supported incidental and intentional relational retrieval in both age groups and an adjacent cluster in posterior hippocampus was recruited during both forms of relational retrieval for older, but not younger, adults. Our findings suggest that while medial temporal lobe regions do not differentiate between incidental and intentional forms of retrieval, there are distinct roles for anterior and posterior medial temporal lobe regions during retrieval of item and relational information, respectively, and further indicate that posterior regions may, under certain conditions, be over-recruited in healthy aging. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Robust non-parametric one-sample tests for the analysis of recurrent events.

Science.gov (United States)

Rebora, Paola; Galimberti, Stefania; Valsecchi, Maria Grazia

2010-12-30

One-sample non-parametric tests are proposed here for inference on recurring events. The focus is on the marginal mean function of events and the basis for inference is the standardized distance between the observed and the expected number of events under a specified reference rate. Different weights are considered in order to account for various types of alternative hypotheses on the mean function of the recurrent events process. A robust version and a stratified version of the test are also proposed. The performance of these tests was investigated through simulation studies under various underlying event generation processes, such as homogeneous and nonhomogeneous Poisson processes, autoregressive and renewal processes, with and without frailty effects. The robust versions of the test have been shown to be suitable in a wide variety of event generating processes. The motivating context is a study on gene therapy in a very rare immunodeficiency in children, where a major end-point is the recurrence of severe infections. Robust non-parametric one-sample tests for recurrent events can be useful to assess efficacy and especially safety in non-randomized studies or in epidemiological studies for comparison with a standard population. Copyright © 2010 John Wiley & Sons, Ltd.

Autonomic Differentiation Map: A Novel Statistical Tool for Interpretation of Heart Rate Variability

Directory of Open Access Journals (Sweden)

Daniela Lucini

2018-04-01

Full Text Available In spite of the large body of evidence suggesting Heart Rate Variability (HRV alone or combined with blood pressure variability (providing an estimate of baroreflex gain as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%, subdivided in oscillatory (40.84%, amplitude (18.04%, pressure (16.48%, and pulse domains (11.58%. Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory statistical and graphical tools to ANS proxies defines

Nonparametric estimation in an "illness-death" model when all transition times are interval censored

DEFF Research Database (Denmark)

Frydman, Halina; Gerds, Thomas; Grøn, Randi

2013-01-01

We develop nonparametric maximum likelihood estimation for the parameters of an irreversible Markov chain on states {0,1,2} from the observations with interval censored times of 0 → 1, 0 → 2 and 1 → 2 transitions. The distinguishing aspect of the data is that, in addition to all transition times ...

Non-Parametric Bayesian Updating within the Assessment of Reliability for Offshore Wind Turbine Support Structures

DEFF Research Database (Denmark)

Ramirez, José Rangel; Sørensen, John Dalsgaard

2011-01-01

This work illustrates the updating and incorporation of information in the assessment of fatigue reliability for offshore wind turbine. The new information, coming from external and condition monitoring can be used to direct updating of the stochastic variables through a non-parametric Bayesian u...

Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison

NARCIS (Netherlands)

Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, J.G.P.W.; Camps-Valls, Gustau; Moreno, José

2015-01-01

Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC),

ITEM LEVEL DIAGNOSTICS AND MODEL - DATA FIT IN ITEM ...

African Journals Online (AJOL)

Global Journal

Item response theory (IRT) is a framework for modeling and analyzing item response ... data. Though, there is an argument that the evaluation of fit in IRT modeling has been ... National Council on Measurement in Education ... model data fit should be based on three types of ... prediction should be assessed through the.

Nonparametric predictive pairwise comparison with competing risks

International Nuclear Information System (INIS)

Coolen-Maturi, Tahani

2014-01-01

In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserved failure modes. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that the lifetime of a future unit from one group, say Y, is greater than the lifetime of a future unit from the second group, say X. The paper also shows how the two groups can be compared based on particular failure mode(s), and the comparison of the two groups when some of the competing risks are combined is discussed

Nonparametric bootstrap analysis with applications to demographic effects in demand functions.

Science.gov (United States)

Gozalo, P L

1997-12-01

"A new bootstrap proposal, labeled smooth conditional moment (SCM) bootstrap, is introduced for independent but not necessarily identically distributed data, where the classical bootstrap procedure fails.... A good example of the benefits of using nonparametric and bootstrap methods is the area of empirical demand analysis. In particular, we will be concerned with their application to the study of two important topics: what are the most relevant effects of household demographic variables on demand behavior, and to what extent present parametric specifications capture these effects." excerpt

Symptoms of anxiety in depression: assessment of item performance of the Hamilton Anxiety Rating Scale in patients with depression.

Science.gov (United States)

Vaccarino, Anthony L; Evans, Kenneth R; Sills, Terrence L; Kalali, Amir H

2008-01-01

Although diagnostically dissociable, anxiety is strongly co-morbid with depression. To examine further the clinical symptoms of anxiety in major depressive disorder (MDD), a non-parametric item response analysis on "blinded" data from four pharmaceutical company clinical trials was performed on the Hamilton Anxiety Rating Scale (HAMA) across levels of depressive severity. The severity of depressive symptoms was assessed using the 17-item Hamilton Depression Rating Scale (HAMD). HAMA and HAMD measures were supplied for each patient on each of two post-screen visits (n=1,668 observations). Option characteristic curves were generated for all 14 HAMA items to determine the probability of scoring a particular option on the HAMA in relation to the total HAMD score. Additional analyses were conducted using Pearson's product-moment correlations. Results showed that anxiety-related symptomatology generally increased as a function of overall depressive severity, though there were clear differences between individual anxiety symptoms in their relationship with depressive severity. In particular, anxious mood, tension, insomnia, difficulties in concentration and memory, and depressed mood were found to discriminate over the full range of HAMD scores, increasing continuously with increases in depressive severity. By contrast, many somatic-related symptoms, including muscular, sensory, cardiovascular, respiratory, gastro-intestinal, and genito-urinary were manifested primarily at higher levels of depression and did not discriminate well at lower HAMD scores. These results demonstrate anxiety as a core feature of depression, and the relationship between anxiety-related symptoms and depression should be considered in the assessment of depression and evaluation of treatment strategies and outcome.

NParCov3: A SAS/IML Macro for Nonparametric Randomization-Based Analysis of Covariance

Directory of Open Access Journals (Sweden)

Richard C. Zink

2012-07-01

Full Text Available Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is a reduction of variance for the treatment effect which provides more powerful statistical tests and more precise confidence intervals. Second, it provides estimates of the treatment effect which are adjusted for random imbalances of covariates between the treatment groups. The nonparametric analysis of covariance method of Koch, Tangen, Jung, and Amara (1998 defines a very general methodology using weighted least-squares to generate covariate-adjusted treatment effects with minimal assumptions. This methodology is general in its applicability to a variety of outcomes, whether continuous, binary, ordinal, incidence density or time-to-event. Further, its use has been illustrated in many clinical trial settings, such as multi-center, dose-response and non-inferiority trials.NParCov3 is a SAS/IML macro written to conduct the nonparametric randomization-based covariance analyses of Koch et al. (1998. The software can analyze a variety of outcomes and can account for stratification. Data from multiple clinical trials will be used for illustration.

Hadron energy reconstruction for the ATLAS calorimetry in the framework of the nonparametrical method

CERN Document Server

Akhmadaliev, S Z; Ambrosini, G; Amorim, A; Anderson, K; Andrieux, M L; Aubert, Bernard; Augé, E; Badaud, F; Baisin, L; Barreiro, F; Battistoni, G; Bazan, A; Bazizi, K; Belymam, A; Benchekroun, D; Berglund, S R; Berset, J C; Blanchot, G; Bogush, A A; Bohm, C; Boldea, V; Bonivento, W; Bosman, M; Bouhemaid, N; Breton, D; Brette, P; Bromberg, C; Budagov, Yu A; Burdin, S V; Calôba, L P; Camarena, F; Camin, D V; Canton, B; Caprini, M; Carvalho, J; Casado, M P; Castillo, M V; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Chadelas, R; Chalifour, M; Chekhtman, A; Chevalley, J L; Chirikov-Zorin, I E; Chlachidze, G; Citterio, M; Cleland, W E; Clément, C; Cobal, M; Cogswell, F; Colas, Jacques; Collot, J; Cologna, S; Constantinescu, S; Costa, G; Costanzo, D; Crouau, M; Daudon, F; David, J; David, M; Davidek, T; Dawson, J; De, K; de La Taille, C; Del Peso, J; Del Prete, T; de Saintignon, P; Di Girolamo, B; Dinkespiler, B; Dita, S; Dodd, J; Dolejsi, J; Dolezal, Z; Downing, R; Dugne, J J; Dzahini, D; Efthymiopoulos, I; Errede, D; Errede, S; Evans, H; Eynard, G; Fassi, F; Fassnacht, P; Ferrari, A; Ferrer, A; Flaminio, Vincenzo; Fournier, D; Fumagalli, G; Gallas, E; Gaspar, M; Giakoumopoulou, V; Gianotti, F; Gildemeister, O; Giokaris, N; Glagolev, V; Glebov, V Yu; Gomes, A; González, V; González de la Hoz, S; Grabskii, V; Graugès-Pous, E; Grenier, P; Hakopian, H H; Haney, M; Hébrard, C; Henriques, A; Hervás, L; Higón, E; Holmgren, Sven Olof; Hostachy, J Y; Hoummada, A; Huston, J; Imbault, D; Ivanyushenkov, Yu M; Jézéquel, S; Johansson, E K; Jon-And, K; Jones, R; Juste, A; Kakurin, S; Karyukhin, A N; Khokhlov, Yu A; Khubua, J I; Klioukhine, V I; Kolachev, G M; Kopikov, S V; Kostrikov, M E; Kozlov, V; Krivkova, P; Kukhtin, V V; Kulagin, M; Kulchitskii, Yu A; Kuzmin, M V; Labarga, L; Laborie, G; Lacour, D; Laforge, B; Lami, S; Lapin, V; Le Dortz, O; Lefebvre, M; Le Flour, T; Leitner, R; Leltchouk, M; Li, J; Liablin, M V; Linossier, O; Lissauer, D; Lobkowicz, F; Lokajícek, M; Lomakin, Yu F; López-Amengual, J M; Lund-Jensen, B; Maio, A; Makowiecki, D S; Malyukov, S N; Mandelli, L; Mansoulié, B; Mapelli, Livio P; Marin, C P; Marrocchesi, P S; Marroquim, F; Martin, P; Maslennikov, A L; Massol, N; Mataix, L; Mazzanti, M; Mazzoni, E; Merritt, F S; Michel, B; Miller, R; Minashvili, I A; Miralles, L; Mnatzakanian, E A; Monnier, E; Montarou, G; Mornacchi, Giuseppe; Moynot, M; Muanza, G S; Nayman, P; Némécek, S; Nessi, Marzio; Nicoleau, S; Niculescu, M; Noppe, J M; Onofre, A; Pallin, D; Pantea, D; Paoletti, R; Park, I C; Parrour, G; Parsons, J; Pereira, A; Perini, L; Perlas, J A; Perrodo, P; Pilcher, J E; Pinhão, J; Plothow-Besch, Hartmute; Poggioli, Luc; Poirot, S; Price, L; Protopopov, Yu; Proudfoot, J; Puzo, P; Radeka, V; Rahm, David Charles; Reinmuth, G; Renzoni, G; Rescia, S; Resconi, S; Richards, R; Richer, J P; Roda, C; Rodier, S; Roldán, J; Romance, J B; Romanov, V; Romero, P; Rossel, F; Rusakovitch, N A; Sala, P; Sanchis, E; Sanders, H; Santoni, C; Santos, J; Sauvage, D; Sauvage, G; Sawyer, L; Says, L P; Schaffer, A C; Schwemling, P; Schwindling, J; Seguin-Moreau, N; Seidl, W; Seixas, J M; Selldén, B; Seman, M; Semenov, A; Serin, L; Shaldaev, E; Shochet, M J; Sidorov, V; Silva, J; Simaitis, V J; Simion, S; Sissakian, A N; Snopkov, R; Söderqvist, J; Solodkov, A A; Soloviev, A; Soloviev, I V; Sonderegger, P; Soustruznik, K; Spanó, F; Spiwoks, R; Stanek, R; Starchenko, E A; Stavina, P; Stephens, R; Suk, M; Surkov, A; Sykora, I; Takai, H; Tang, F; Tardell, S; Tartarelli, F; Tas, P; Teiger, J; Thaler, J; Thion, J; Tikhonov, Yu A; Tisserant, S; Tokar, S; Topilin, N D; Trka, Z; Turcotte, M; Valkár, S; Varanda, M J; Vartapetian, A H; Vazeille, F; Vichou, I; Vinogradov, V; Vorozhtsov, S B; Vuillemin, V; White, A; Wielers, M; Wingerter-Seez, I; Wolters, H; Yamdagni, N; Yosef, C; Zaitsev, A; Zitoun, R; Zolnierowski, Y

2002-01-01

This paper discusses hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter (consisting of a lead-liquid argon electromagnetic part and an iron-scintillator hadronic part) in the framework of the nonparametrical method. The nonparametrical method utilizes only the known e/h ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to an easy use in a first level trigger. The reconstructed mean values of the hadron energies are within +or-1% of the true values and the fractional energy resolution is [(58+or-3)%/ square root E+(2.5+or-0.3)%](+)(1.7+or-0.2)/E. The value of the e/h ratio obtained for the electromagnetic compartment of the combined calorimeter is 1.74+or-0.04 and agrees with the prediction that e/h >1.66 for this electromagnetic calorimeter. Results of a study of the longitudinal hadronic shower development are also presented. The data have been taken in the H8 beam...

Parametric and nonparametric Granger causality testing: Linkages between international stock markets

Science.gov (United States)

De Gooijer, Jan G.; Sivarajasingham, Selliah

2008-04-01

This study investigates long-term linear and nonlinear causal linkages among eleven stock markets, six industrialized markets and five emerging markets of South-East Asia. We cover the period 1987-2006, taking into account the on-set of the Asian financial crisis of 1997. We first apply a test for the presence of general nonlinearity in vector time series. Substantial differences exist between the pre- and post-crisis period in terms of the total number of significant nonlinear relationships. We then examine both periods, using a new nonparametric test for Granger noncausality and the conventional parametric Granger noncausality test. One major finding is that the Asian stock markets have become more internationally integrated after the Asian financial crisis. An exception is the Sri Lankan market with almost no significant long-term linear and nonlinear causal linkages with other markets. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VAR filtered residuals and VAR filtered squared residuals for the post-crisis sample. We find quite a few remaining significant bi- and uni-directional causal nonlinear relationships in these series. Finally, after filtering the VAR-residuals with GARCH-BEKK models, we show that the nonparametric test statistics are substantially smaller in both magnitude and statistical significance than those before filtering. This indicates that nonlinear causality can, to a large extent, be explained by simple volatility effects.

Evolution of a Test Item

Science.gov (United States)

Spaan, Mary

2007-01-01

This article follows the development of test items (see "Language Assessment Quarterly", Volume 3 Issue 1, pp. 71-79 for the article "Test and Item Specifications Development"), beginning with a review of test and item specifications, then proceeding to writing and editing of items, pretesting and analysis, and finally selection of an item for a…

A photographic method to measure food item intake. Validation in geriatric institutions.

Science.gov (United States)

Pouyet, Virginie; Cuvelier, Gérard; Benattar, Linda; Giboreau, Agnès

2015-01-01

From both a clinical and research perspective, measuring food intake is an important issue in geriatric institutions. However, weighing food in this context can be complex, particularly when the items remaining on a plate (side dish, meat or fish and sauce) need to be weighed separately following consumption. A method based on photography that involves taking photographs after a meal to determine food intake consequently seems to be a good alternative. This method enables the storage of raw data so that unhurried analyses can be performed to distinguish the food items present in the images. Therefore, the aim of this paper was to validate a photographic method to measure food intake in terms of differentiating food item intake in the context of a geriatric institution. Sixty-six elderly residents took part in this study, which was performed in four French nursing homes. Four dishes of standardized portions were offered to the residents during 16 different lunchtimes. Three non-trained assessors then independently estimated both the total and specific food item intakes of the participants using images of their plates taken after the meal (photographic method) and a reference image of one plate taken before the meal. Total food intakes were also recorded by weighing the food. To test the reliability of the photographic method, agreements between different assessors and agreements among various estimates made by the same assessor were evaluated. To test the accuracy and specificity of this method, food intake estimates for the four dishes were compared with the food intakes determined using the weighed food method. To illustrate the added value of the photographic method, food consumption differences between the dishes were explained by investigating the intakes of specific food items. Although they were not specifically trained for this purpose, the results demonstrated that the assessor estimates agreed between assessors and among various estimates made by the same

The Longer We Have to Forget the More We Remember: The Ironic Effect of Postcue Duration in Item-Based Directed Forgetting

Science.gov (United States)

Bancroft, Tyler D.; Hockley, William E.; Farquhar, Riley

2013-01-01

The effects of the duration of remember and forget cues were examined to test the differential rehearsal account of item-based directed forgetting. In Experiments 1 and 2, cues were shown for 300, 600, or 900 ms, and a directed forgetting effect (better recognition of remember than forget items) was found at each duration. In addition, recognition…

Efficiency Analysis of German Electricity Distribution Utilities : Non-Parametric and Parametric Tests

OpenAIRE

von Hirschhausen, Christian R.; Cullmann, Astrid

2005-01-01

Abstract This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) ...

Bootstrapping the economy -- a non-parametric method of generating consistent future scenarios

OpenAIRE

Müller, Ulrich A; Bürgi, Roland; Dacorogna, Michel M

2004-01-01

The fortune and the risk of a business venture depends on the future course of the economy. There is a strong demand for economic forecasts and scenarios that can be applied to planning and modeling. While there is an ongoing debate on modeling economic scenarios, the bootstrapping (or resampling) approach presented here has several advantages. As a non-parametric method, it directly relies on past market behaviors rather than debatable assumptions on models and parameters. Simultaneous dep...

Psychometric validation of the Persian nine-item Internet Gaming Disorder Scale - Short Form: Does gender and hours spent online gaming affect the interpretations of item descriptions?

Science.gov (United States)

Wu, Tzu-Yi; Lin, Chung-Ying; Årestedt, Kristofer; Griffiths, Mark D; Broström, Anders; Pakpour, Amir H

2017-06-01

Background and aims The nine-item Internet Gaming Disorder Scale - Short Form (IGDS-SF9) is brief and effective to evaluate Internet Gaming Disorder (IGD) severity. Although its scores show promising psychometric properties, less is known about whether different groups of gamers interpret the items similarly. This study aimed to verify the construct validity of the Persian IGDS-SF9 and examine the scores in relation to gender and hours spent online gaming among 2,363 Iranian adolescents. Methods Confirmatory factor analysis (CFA) and Rasch analysis were used to examine the construct validity of the IGDS-SF9. The effects of gender and time spent online gaming per week were investigated by multigroup CFA and Rasch differential item functioning (DIF). Results The unidimensionality of the IGDS-SF9 was supported in both CFA and Rasch. However, Item 4 (fail to control or cease gaming activities) displayed DIF (DIF contrast = 0.55) slightly over the recommended cutoff in Rasch but was invariant in multigroup CFA across gender. Items 4 (DIF contrast = -0.67) and 9 (jeopardize or lose an important thing because of gaming activity; DIF contrast = 0.61) displayed DIF in Rasch and were non-invariant in multigroup CFA across time spent online gaming. Conclusions Given the Persian IGDS-SF9 was unidimensional, it is concluded that the instrument can be used to assess IGD severity. However, users of the instrument are cautioned concerning the comparisons of the sum scores of the IGDS-SF9 across gender and across adolescents spending different amounts of time online gaming.

The Comparability of English, French and Dutch Scores on the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F): An Assessment of Differential Item Functioning in Patients with Systemic Sclerosis

Science.gov (United States)

Kwakkenbos, Linda; Willems, Linda M.; Baron, Murray; Hudson, Marie; Cella, David; van den Ende, Cornelia H. M.; Thombs, Brett D.

2014-01-01

Objective The Functional Assessment of Chronic Illness Therapy- Fatigue (FACIT-F) is commonly used to assess fatigue in rheumatic diseases, and has shown to discriminate better across levels of the fatigue spectrum than other commonly used measures. The aim of this study was to assess the cross-language measurement equivalence of the English, French, and Dutch versions of the FACIT-F in systemic sclerosis (SSc) patients. Methods The FACIT-F was completed by 871 English-speaking Canadian, 238 French-speaking Canadian and 230 Dutch SSc patients. Confirmatory factor analysis was used to assess the factor structure in the three samples. The Multiple-Indicator Multiple-Cause (MIMIC) model was utilized to assess differential item functioning (DIF), comparing English versus French and versus Dutch patient responses separately. Results A unidimensional factor model showed good fit in all samples. Comparing French versus English patients, statistically significant, but small-magnitude DIF was found for 3 of 13 items. French patients had 0.04 of a standard deviation (SD) lower latent fatigue scores than English patients and there was an increase of only 0.03 SD after accounting for DIF. For the Dutch versus English comparison, 4 items showed small, but statistically significant, DIF. Dutch patients had 0.20 SD lower latent fatigue scores than English patients. After correcting for DIF, there was a reduction of 0.16 SD in this difference. Conclusions There was statistically significant DIF in several items, but the overall effect on fatigue scores was minimal. English, French and Dutch versions of the FACIT-F can be reasonably treated as having equivalent scoring metrics. PMID:24638101

Non-parametric transformation for data correlation and integration: From theory to practice

Energy Technology Data Exchange (ETDEWEB)

Datta-Gupta, A.; Xue, Guoping; Lee, Sang Heon [Texas A& M Univ., College Station, TX (United States)

1997-08-01

The purpose of this paper is two-fold. First, we introduce the use of non-parametric transformations for correlating petrophysical data during reservoir characterization. Such transformations are completely data driven and do not require a priori functional relationship between response and predictor variables which is the case with traditional multiple regression. The transformations are very general, computationally efficient and can easily handle mixed data types for example, continuous variables such as porosity, permeability and categorical variables such as rock type, lithofacies. The power of the non-parametric transformation techniques for data correlation has been illustrated through synthetic and field examples. Second, we utilize these transformations to propose a two-stage approach for data integration during heterogeneity characterization. The principal advantages of our approach over traditional cokriging or cosimulation methods are: (1) it does not require a linear relationship between primary and secondary data, (2) it exploits the secondary information to its fullest potential by maximizing the correlation between the primary and secondary data, (3) it can be easily applied to cases where several types of secondary or soft data are involved, and (4) it significantly reduces variance function calculations and thus, greatly facilitates non-Gaussian cosimulation. We demonstrate the data integration procedure using synthetic and field examples. The field example involves estimation of pore-footage distribution using well data and multiple seismic attributes.

The Piper Fatigue Scale-12 (PFS-12): psychometric findings and item reduction in a cohort of breast cancer survivors.

Science.gov (United States)

Reeve, Bryce B; Stover, Angela M; Alfano, Catherine M; Smith, Ashley Wilder; Ballard-Barbash, Rachel; Bernstein, Leslie; McTiernan, Anne; Baumgartner, Kathy B; Piper, Barbara F

2012-11-01

Brief, valid measures of fatigue, a prevalent and distressing cancer symptom, are needed for use in research. This study's primary aim was to create a shortened version of the revised Piper Fatigue Scale (PFS-R) based on data from a diverse cohort of breast cancer survivors. A secondary aim was to determine whether the PFS captured multiple distinct aspects of fatigue (a multidimensional model) or a single overall fatigue factor (a unidimensional model). Breast cancer survivors (n = 799; stages in situ through IIIa; ages 29-86 years) were recruited through three SEER registries (New Mexico, Western Washington, and Los Angeles, CA) as part of the Health, Eating, Activity, and Lifestyle (HEAL) study. Fatigue was measured approximately 3 years post-diagnosis using the 22-item PFS-R that has four subscales (Behavior, Affect, Sensory, and Cognition). Confirmatory factor analysis was used to compare unidimensional and multidimensional models. Six criteria were used to make item selections to shorten the PFS-R: scale's content validity, items' relationship with fatigue, content redundancy, differential item functioning by race and/or education, scale reliability, and literacy demand. Factor analyses supported the original 4-factor structure. There was also evidence from the bi-factor model for a dominant underlying fatigue factor. Six items tested positive for differential item functioning between African-American and Caucasian survivors. Four additional items either showed poor association, local dependence, or content validity concerns. After removing these 10 items, the reliability of the PFS-12 subscales ranged from 0.87 to 0.89, compared to 0.90-0.94 prior to item removal. The newly developed PFS-12 can be used to assess fatigue in African-American and Caucasian breast cancer survivors and reduces response burden without compromising reliability or validity. This is the first study to determine PFS literacy demand and to compare PFS-R responses in African

Assessing Psychopathy Among Justice Involved Adolescents with the PCL: YV: An Item Response Theory Examination Across Gender

Science.gov (United States)

Tsang, Siny; Schmidt, Karen M.; Vincent, Gina M.; Salekin, Randall T.; Moretti, Marlene M.; Odgers, Candice L.

2014-01-01

This study used an item response theory (IRT) model and a large adolescent sample of justice involved youth (N = 1,007, 38% female) to examine the item functioning of the Psychopathy Checklist – Youth Version (PCL: YV). Items that were most discriminating (or most sensitive to changes) of the latent trait (thought to be psychopathy) among adolescents included “Glibness/superficial charm”, “Lack of remorse”, and “Need for stimulation”, whereas items that were least discriminating included “Pathological lying”, “Failure to accept responsibility”, and “Lacks goals.” The items “Impulsivity” and “Irresponsibility” were the most likely to be rated high among adolescents, whereas “Parasitic lifestyle”, and “Glibness/superficial charm” were the most likely to be rated low. Evidence of differential item functioning (DIF) on four of the 13 items was found between boys and girls. “Failure to accept responsibility” and “Impulsivity” were endorsed more frequently to describe adolescent girls than boys at similar levels of the latent trait, and vice versa for “Grandiose sense of self-worth” and “Lacks goals.” The DIF findings suggest that four PCL: YV items function differently between boys and girls. PMID:25580672

Instructional Topics in Educational Measurement (ITEMS) Module: Using Automated Processes to Generate Test Items

Science.gov (United States)

Gierl, Mark J.; Lai, Hollis

2013-01-01

Changes to the design and development of our educational assessments are resulting in the unprecedented demand for a large and continuous supply of content-specific test items. One way to address this growing demand is with automatic item generation (AIG). AIG is the process of using item models to generate test items with the aid of computer…

Teoria da Resposta ao Item Teoria de la respuesta al item Item response theory