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Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A. – Multivariate Behavioral Research, 2011
In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…
Descriptors: Research Design, Statistical Analysis, Research Methodology, Longitudinal Studies
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Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)
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McArdle, John J. – Multivariate Behavioral Research, 1994
Benefits and limitations of structural equation models for multivariate experiments with incomplete data are presented. Examples from studies of latent variable path models of cognitive performance illustrate analyses with latent variables, omitted variables, randomly missing data, and nonrandomly missing data. (SLD)
Descriptors: Cost Effectiveness, Experiments, Factor Analysis, Longitudinal Studies
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Cronbach, Lee J. – Multivariate Behavioral Research, 1984
This article describes the evolution of Raymond B. Cattell's data box (covariation chart), a synoptic conception of psychological data, from its introduction in 1946. Analytical techniques and related methodologies developed from this model by Cattell and other psychological researchers are discussed. (BS)
Descriptors: Experimental Psychology, Factor Analysis, Longitudinal Studies, Models