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Direct linkMoeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim – Journal of Experimental Education, 2014
One approach for combining single-case data involves use of multilevel modeling. In this article, the authors use a Monte Carlo simulation study to inform applied researchers under which realistic conditions the three-level model is appropriate. The authors vary the value of the immediate treatment effect and the treatment's effect on the time…
Descriptors: Hierarchical Linear Modeling, Monte Carlo Methods, Case Studies, Research Design
Peer reviewedBandalos, Deborah L. – Multivariate Behavioral Research, 1993
A Monte Carlo study investigated the use of four cross-validation indices with confirmatory factor analysis models. Influences of sample size, loading size, and degree of model misspecification were studied. Larger sample sizes and better specified models result in better cross-validation results. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Influences, Mathematical Models
Peer reviewedDwyer, James H. – Evaluation Review, 1984
A solution to the problem of specification error due to excluded variables in statistical models of treatment effects in nonrandomized (nonequivalent) control group designs is presented. It involves longitudinal observation with at least two pretests. A maximum likelihood estimation program such as LISREL may provide reasonable estimates of…
Descriptors: Control Groups, Mathematical Models, Maximum Likelihood Statistics, Monte Carlo Methods
