Graciela Muniz-Terrera1, Annie Robitaille2, Amanda Kelly2, Boo Johansson3, Scott Hofer2, Andrea Piccinin2. 1. Centre for Dementia Prevention, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Scotland. Electronic address: G.Muniz@ed.ac.uk. 2. Department of Psychology, Cornett Building, University of Victoria, Victoria, British Columbia, Canada. 3. Department of Psychology, University of Gothenburg, Haraldsgatan 1, Gothenburg 40530, Sweden.
Abstract
OBJECTIVES: Given theoretical and methodological advances that propose hypothesis about change in one or multiple processes, analytical methods for longitudinal data have been developed that provide researchers with various options for analyzing change over time. In this paper, we revisited several latent growth curve models that may be considered to answer questions about repeated measures of continuous variables, which may be operationalized as time-varying covariates or outcomes. STUDY DESIGN AND SETTING: To illustrate each of the models discussed and how to interpret parameter estimates, we present examples of each method discussed using cognitive and blood pressure measures from a longitudinal study of aging, the Origins of Variance in the Old-Old study. RESULTS AND CONCLUSION: Although statistical models are helpful tools to test theoretical hypotheses about the dynamics between multiple processes, the choice of model and its specification will influence results and conclusions made.
OBJECTIVES: Given theoretical and methodological advances that propose hypothesis about change in one or multiple processes, analytical methods for longitudinal data have been developed that provide researchers with various options for analyzing change over time. In this paper, we revisited several latent growth curve models that may be considered to answer questions about repeated measures of continuous variables, which may be operationalized as time-varying covariates or outcomes. STUDY DESIGN AND SETTING: To illustrate each of the models discussed and how to interpret parameter estimates, we present examples of each method discussed using cognitive and blood pressure measures from a longitudinal study of aging, the Origins of Variance in the Old-Old study. RESULTS AND CONCLUSION: Although statistical models are helpful tools to test theoretical hypotheses about the dynamics between multiple processes, the choice of model and its specification will influence results and conclusions made.
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