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Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Wulff, Dirk U.; Pachur, Thorsten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated…
Descriptors: Experimental Psychology, Cognitive Psychology, Modeling (Psychology), Models
Kubinger, Klaus D.; Rasch, Dieter; Yanagida, Takuya – Educational Research and Evaluation, 2011
Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and…
Descriptors: Sample Size, Simulation, Testing, Achievement Tests
Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
Hutchinson, Susan R. – 1994
The work of R. MacCallum et al. (1992) was extended by examining chance modifications through a Monte Carlo simulation. The stability of post hoc model modifications was examined under varying sample size, model complexity, and severity of misspecification using 2- and 4-factor oblique confirmatory factor analysis (CFA) models with four and eight…
Descriptors: Computer Simulation, Models, Monte Carlo Methods, Reliability
Fiedler, Klaus; Kareev, Yaakov – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Adaptive decision making requires that contingencies between decision options and their relative assets be assessed accurately and quickly. The present research addresses the challenging notion that contingencies may be more visible from small than from large samples of observations. An algorithmic account for such a seemingly paradoxical effect…
Descriptors: Sampling, Decision Making, Computer Simulation, Models
Schmitt, J. Eric; Mehta, Paras D.; Aggen, Steven H.; Kubarych, Thomas S.; Neale, Michael C. – Multivariate Behavioral Research, 2006
Ordered latent class analysis (OLCA) can be used to approximate unidimensional latent distributions. The main objective of this study is to evaluate the method of OLCA in detecting non-normality of an unobserved continuous variable (i.e., a common factor) used to explain the covariation between dichotomous item-level responses. Using simulation,…
Descriptors: Probability, Sample Size, Effect Size, Depression (Psychology)
Johnson, Colleen Cook – 1993
This study integrates into one comprehensive Monte Carlo simulation a vast array of previously defined and substantively interrelated research studies of the robustness of analysis of variance (ANOVA) and analysis of covariance (ANCOVA) statistical procedures. Three sets of balanced ANOVA and ANCOVA designs (group sizes of 15, 30, and 45) and one…
Descriptors: Analysis of Covariance, Analysis of Variance, Computer Simulation, Models
Hsiung, Tung-Hsing; Olejnik, Stephen – 1994
This study investigated the robustness of the James second-order test (James 1951; Wilcox, 1989) and the univariate F test under a two-factor fixed-effect analysis of variance (ANOVA) model in which cell variances were heterogeneous and/or distributions were nonnormal. With computer-simulated data, Type I error rates and statistical power for the…
Descriptors: Analysis of Variance, Computer Simulation, Estimation (Mathematics), Interaction
Carlson, James E. – 1993
In this article some results are presented relating to the dimensionality of instruments containing polytomously scored as well as dichotomously scored items, concentrating on the 1992 National Assessment of Educational Progress' (NAEP) mathematics and reading assessment data and several simulated datasets. The maximum likelihood factor analytic…
Descriptors: Computer Simulation, Correlation, Elementary Secondary Education, Factor Analysis
Peer reviewedClauser, Brian E.; And Others – Journal of Educational Measurement, 1995
A scoring algorithm for performance assessments is described that is based on expert judgments but requires the rating of only a sample of performances. A regression-based policy capturing procedure was implemented for clinicians evaluating skills of 280 medical students. Results demonstrate the usefulness of the algorithm. (SLD)
Descriptors: Algorithms, Clinical Diagnosis, Computer Simulation, Educational Assessment

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