Literature DB >> 24364798

The separation of between-person and within-person components of individual change over time: a latent curve model with structured residuals.

Patrick J Curran1, Andrea L Howard2, Sierra A Bainter1, Stephanie T Lane1, James S McGinley1.   

Abstract

OBJECTIVE: Although recent statistical and computational developments allow for the empirical testing of psychological theories in ways not previously possible, one particularly vexing challenge remains: how to optimally model the prospective, reciprocal relations between 2 constructs as they developmentally unfold over time. Several analytic methods currently exist that attempt to model these types of relations, and each approach is successful to varying degrees. However, none provide the unambiguous separation over time of between-person and within-person components of stability and change, components that are often hypothesized to exist in the psychological sciences. Our goal in this article is to propose and demonstrate a novel extension of the multivariate latent curve model to allow for the disaggregation of these effects.
METHOD: We begin with a review of the standard latent curve models and describe how these primarily capture between-person differences in change. We then extend this model to allow for regression structures among the time-specific residuals to capture within-person differences in change.
RESULTS: We demonstrate this model using an artificial data set generated to mimic the developmental relation between alcohol use and depressive symptomatology spanning 5 repeated measures.
CONCLUSIONS: We obtain a specificity of results from the proposed analytic strategy that is not available from other existing methodologies. We conclude with potential limitations of our approach and directions for future research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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Year:  2013        PMID: 24364798      PMCID: PMC4067471          DOI: 10.1037/a0035297

Source DB:  PubMed          Journal:  J Consult Clin Psychol        ISSN: 0022-006X


  26 in total

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