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Biesanz, Jeremy C.; Falk, Carl F.; Savalei, Victoria – Multivariate Behavioral Research, 2010
Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses (Baron & Kenny, 1986; Sobel, 1982) have in recent years…
Descriptors: Computation, Intervals, Models, Monte Carlo Methods
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Hung, Lai-Fa – Multivariate Behavioral Research, 2010
Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…
Descriptors: Longitudinal Studies, Data, Models, Markov Processes
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Hsieh, Chueh-An; von Eye, Alexander A.; Maier, Kimberly S. – Multivariate Behavioral Research, 2010
The application of multidimensional item response theory models to repeated observations has demonstrated great promise in developmental research. It allows researchers to take into consideration both the characteristics of item response and measurement error in longitudinal trajectory analysis, which improves the reliability and validity of the…
Descriptors: Item Response Theory, Change, Adolescents, Social Isolation
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Song, Xin-Yuan; Lee, Sik-Yum – Multivariate Behavioral Research, 2006
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…
Descriptors: Structural Equation Models, Bayesian Statistics, Markov Processes, Monte Carlo Methods