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Shrout, Patrick E. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) extended the work of Maxwell and Cole (2007), which raised important questions about whether mediation analyses based on cross-sectional data can shed light on longitudinal mediation process. The latest article considers longitudinal processes that can only be partially explained by an intervening variable, and…
Descriptors: Causal Models, Psychopathology, Peer Mediation, Longitudinal Studies
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Choi, Jaehwa; Harring, Jeffrey R.; Hancock, Gregory R. – Multivariate Behavioral Research, 2009
Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…
Descriptors: Causal Models, Structural Equation Models, Longitudinal Studies, Change
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Markus, Keith A. – Multivariate Behavioral Research, 2008
One can distinguish statistical models used in causal modeling from the causal interpretations that align them with substantive hypotheses. Causal modeling typically assumes an efficient causal interpretation of the statistical model. Causal modeling can also make use of mereological causal interpretations in which the state of the parts…
Descriptors: Research Design, Structural Equation Models, Data Analysis, Causal Models
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Schluchter, Mark D. – Multivariate Behavioral Research, 2008
In behavioral research, interest is often in examining the degree to which the effect of an independent variable X on an outcome Y is mediated by an intermediary or mediator variable M. This article illustrates how generalized estimating equations (GEE) modeling can be used to estimate the indirect or mediated effect, defined as the amount by…
Descriptors: Intervals, Predictor Variables, Equations (Mathematics), Computation