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Showing 1 to 15 of 19 results Save | Export
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Lee, Sunbok – Journal of Educational Measurement, 2020
In the logistic regression (LR) procedure for differential item functioning (DIF), the parameters of LR have often been estimated using maximum likelihood (ML) estimation. However, ML estimation suffers from the finite-sample bias. Furthermore, ML estimation for LR can be substantially biased in the presence of rare event data. The bias of ML…
Descriptors: Regression (Statistics), Test Bias, Maximum Likelihood Statistics, Simulation
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Bogaert, Jasper; Loh, Wen Wei; Rosseel, Yves – Educational and Psychological Measurement, 2023
Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…
Descriptors: Factor Analysis, Regression (Statistics), Structural Equation Models, Error of Measurement
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Jin, Ying; Eason, Hershel – Journal of Educational Issues, 2016
The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…
Descriptors: Test Bias, Simulation, Hierarchical Linear Modeling, Comparative Analysis
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Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane – Journal of Educational and Behavioral Statistics, 2015
Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
Descriptors: Structural Equation Models, Nonparametric Statistics, Regression (Statistics), Maximum Likelihood Statistics
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Kopanidis, Foula Zografina; Shaw, Michael John – Education & Training, 2017
Purpose: Educational institutions are caught between increasing their offer rates and attracting and retaining those prospective students who are most suited to course completion. The purpose of this paper is to demonstrate the influence of demographic and psychological constructs on students' preferences when choosing to study in a particular…
Descriptors: Student Attitudes, Course Selection (Students), Preferences, Models
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Vuolo, Mike – Sociological Methods & Research, 2017
Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…
Descriptors: Sociology, Research Methodology, Social Science Research, Models
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Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H. – Research Synthesis Methods, 2014
Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…
Descriptors: Meta Analysis, Diagnostic Tests, Accuracy, Comparative Analysis
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Petersen, Janne; Bandeen-Roche, Karen; Budtz-Jorgensen, Esben; Larsen, Klaus Groes – Psychometrika, 2012
Latent class regression models relate covariates and latent constructs such as psychiatric disorders. Though full maximum likelihood estimation is available, estimation is often in three steps: (i) a latent class model is fitted without covariates; (ii) latent class scores are predicted; and (iii) the scores are regressed on covariates. We propose…
Descriptors: Computation, Prediction, Regression (Statistics), Maximum Likelihood Statistics
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Gemici, Sinan; Bednarz, Alice; Lim, Patrick – International Journal of Training Research, 2012
Quantitative research in vocational education and training (VET) is routinely affected by missing or incomplete information. However, the handling of missing data in published VET research is often sub-optimal, leading to a real risk of generating results that can range from being slightly biased to being plain wrong. Given that the growing…
Descriptors: Vocational Education, Educational Research, Data, Statistical Analysis
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Schlomer, Gabriel L.; Bauman, Sheri; Card, Noel A. – Journal of Counseling Psychology, 2010
This article urges counseling psychology researchers to recognize and report how missing data are handled, because consumers of research cannot accurately interpret findings without knowing the amount and pattern of missing data or the strategies that were used to handle those data. Patterns of missing data are reviewed, and some of the common…
Descriptors: Maximum Likelihood Statistics, Counseling Psychology, Researchers, Data Collection
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Verkuilen, Jay; Smithson, Michael – Journal of Educational and Behavioral Statistics, 2012
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…
Descriptors: Responses, Regression (Statistics), Statistical Analysis, Models
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Young, Rebekah; Johnson, David – Journal of Marriage and Family, 2013
Secondary respondent data are underutilized because researchers avoid using these data in the presence of substantial missing data. The authors reviewed, evaluated, and tested solutions to this problem. Five strategies of dealing with missing partner data were reviewed: (a) complete case analysis, (b) inverse probability weighting, (c) correction…
Descriptors: Research Methodology, Marital Satisfaction, Marriage, Spouses
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Paek, Insu – ETS Research Report Series, 2009
Three statistical testing procedures well-known in the maximum likelihood approach are the Wald, likelihood ratio (LR), and score tests. Although well-known, the application of these three testing procedures in the logistic regression method to investigate differential item function (DIF) has not been rigorously made yet. Employing a variety of…
Descriptors: Test Bias, Statistical Analysis, Regression (Statistics), Maximum Likelihood Statistics
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Meyer, J. Patrick; Setzer, J. Carl – Journal of Educational Measurement, 2009
Recent changes to federal guidelines for the collection of data on race and ethnicity allow respondents to select multiple race categories. Redefining race subgroups in this manner poses problems for research spanning both sets of definitions. NAEP long-term trends have used the single-race subgroup definitions for over thirty years. Little is…
Descriptors: Elementary Secondary Education, Federal Legislation, Simulation, Maximum Likelihood Statistics
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Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M. – Structural Equation Modeling, 2002
Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…
Descriptors: Maximum Likelihood Statistics, Regression (Statistics), Simulation, Structural Equation Models
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