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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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Cheung, Mike W. -L. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Confidence intervals (CIs) for parameters are usually constructed based on the estimated standard errors. These are known as Wald CIs. This article argues that likelihood-based CIs (CIs based on likelihood ratio statistics) are often preferred to Wald CIs. It shows how the likelihood-based CIs and the Wald CIs for many statistics and psychometric…
Descriptors: Intervals, Structural Equation Models, Simulation, Correlation
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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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Cai, Li; Hayes, Andrew F. – Journal of Educational and Behavioral Statistics, 2008
When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…
Descriptors: Least Squares Statistics, Error Patterns, Error Correction, Computation
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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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Hoshino, Takahiro – Psychometrika, 2007
Due to the difficulty in achieving a random assignment, a quasi-experimental or observational study design is frequently used in the behavioral and social sciences. If a nonrandom assignment depends on the covariates, multiple group structural equation modeling, that includes the regression function of the dependent variables on the covariates…
Descriptors: Structural Equation Models, Simulation, Observation, Behavioral Science Research
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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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Zhang, Zhiyong; Nesselroade, John R. – Multivariate Behavioral Research, 2007
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
Descriptors: Bayesian Statistics, Computation, Simulation, Behavioral Science Research
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Song, Xin-Yuan; Lee, Sik-Yum – Multivariate Behavioral Research, 2005
In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…
Descriptors: Structural Equation Models, Simulation, Computation, Error of Measurement