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Showing 1 to 15 of 18 results Save | Export
McNeish, Daniel; Bauer, Daniel J. – Grantee Submission, 2020
Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Factor Analysis, Matrices
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Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
Pustejovsky, James E. – Grantee Submission, 2018
Methods for meta-analyzing single-case designs (SCDs) are needed to inform evidence-based practice in clinical and school settings and to draw broader and more defensible generalizations in areas where SCDs comprise a large part of the research base. The most widely used outcomes in single-case research are measures of behavior collected using…
Descriptors: Meta Analysis, Case Studies, Evidence Based Practice, Behavioral Science Research
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Shieh, Gwowen – Journal of Experimental Education, 2015
Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…
Descriptors: Statistical Analysis, Sample Size, Computation, Effect Size
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Lai, Mark H. C.; Kwok, Oi-Man – Journal of Educational and Behavioral Statistics, 2014
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…
Descriptors: Hierarchical Linear Modeling, Differences, Effect Size, Computation
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Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K. – Multivariate Behavioral Research, 2012
Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…
Descriptors: Questionnaires, Data Analysis, Computation, Monte Carlo Methods
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Hung, Lai-Fa – Multivariate Behavioral Research, 2011
The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…
Descriptors: Markov Processes, Computer Software, Psychology, Computation
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Zhong, Xiaoling; Yuan, Ke-Hai – Multivariate Behavioral Research, 2011
In the structural equation modeling literature, the normal-distribution-based maximum likelihood (ML) method is most widely used, partly because the resulting estimator is claimed to be asymptotically unbiased and most efficient. However, this may not hold when data deviate from normal distribution. Outlying cases or nonnormally distributed data,…
Descriptors: Structural Equation Models, Simulation, Racial Identification, Computation
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Holden, Jocelyn E.; Kelley, Ken – Educational and Psychological Measurement, 2010
Classification procedures are common and useful in behavioral, educational, social, and managerial research. Supervised classification techniques such as discriminant function analysis assume training data are perfectly classified when estimating parameters or classifying. In contrast, unsupervised classification techniques such as finite mixture…
Descriptors: Discriminant Analysis, Classification, Computation, Behavioral Science Research
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Solanas, Antonio; Manolov, Rumen; Onghena, Patrick – Behavior Modification, 2010
The current study proposes a new procedure for separately estimating slope change and level change between two adjacent phases in single-case designs. The procedure eliminates baseline trend from the whole data series before assessing treatment effectiveness. The steps necessary to obtain the estimates are presented in detail, explained, and…
Descriptors: Simulation, Computation, Models, Behavioral Science Research
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Chong, Terence Tai-Leung; Cheung, Ka-Shing; Hui, Pik-Hung – Journal of Higher Education Policy and Management, 2009
This paper investigates the determinants of student attendance of economics classes. Course-specific and individual-specific factors are shown to have significant impacts on class attendance. It was found that female students and overseas students skip classes less often. Surprisingly, students involved in extra-curricular activities attend…
Descriptors: Economics Education, Attendance, Foreign Countries, Case Studies
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Williams, Jason; MacKinnon, David P. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Recent advances in testing mediation have found that certain resampling methods and tests based on the mathematical distribution of 2 normal random variables substantially outperform the traditional "z" test. However, these studies have primarily focused only on models with a single mediator and 2 component paths. To address this limitation, a…
Descriptors: Intervals, Testing, Predictor Variables, Effect Size
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Halpern, Casey; Clark, Robin; Moore, Peachie; Cross, Katy; Grossman, Murray – Brain and Cognition, 2007
Patients with corticobasal degeneration (CBD) have calculation impairments. This study examined whether impaired number knowledge depends on verbal mediation. We focused particularly on knowledge of very small numbers, where there is a precise relationship between a cardinality and its number concept, but little hypothesized role for verbal…
Descriptors: Dementia, Computation, Patients, Reaction Time
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Penev, Spiridon; Raykov, Tenko – Multivariate Behavioral Research, 2006
A linear combination of a set of measures is often sought as an overall score summarizing subject performance. The weights in this composite can be selected to maximize its reliability or to maximize its validity, and the optimal choice of weights is in general not the same for these two optimality criteria. We explore several relationships…
Descriptors: Behavioral Science Research, Reliability, Validity, Evaluation Methods
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Caplan, Jeremy B.; Glaholt, Mackenzie G.; McIntosh, Anthony R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Paired associates and serial list memory are typically investigated separately. An "isolation principle" (J. B. Caplan, 2005) was proposed to explain behavior in both paradigms by using a single model, in which serial list and paired associates memory differ only in how isolated pairs of items are from interference from other studied items. In…
Descriptors: Memory, Computation, Cognitive Processes, Experiments
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