title: Latent growth models matched to research questions to answer questions about dynamics of change in multiple processes.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Centre for Dementia Prevention, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Scotland. Electronic address: G.Muniz@ed.ac.uk.
authors.forename: Graciela
authors.initials: G
authors.lastname: Muniz-Terrera
authors.affiliation: Department of Psychology, Cornett Building, University of Victoria, Victoria, British Columbia, Canada.
authors.forename: Annie
authors.initials: A
authors.lastname: Robitaille
authors.affiliation: Department of Psychology, Cornett Building, University of Victoria, Victoria, British Columbia, Canada.
authors.forename: Amanda
authors.initials: A
authors.lastname: Kelly
authors.affiliation: Department of Psychology, University of Gothenburg, Haraldsgatan 1, Gothenburg 40530, Sweden.
authors.forename: Boo
authors.initials: B
authors.lastname: Johansson
authors.affiliation: Department of Psychology, Cornett Building, University of Victoria, Victoria, British Columbia, Canada.
authors.forename: Scott
authors.initials: S
authors.lastname: Hofer
authors.affiliation: Department of Psychology, Cornett Building, University of Victoria, Victoria, British Columbia, Canada.
authors.forename: Andrea
authors.initials: A
authors.lastname: Piccinin
mesh_terms: D000369:Aged, 80 and over; D015340:Epidemiologic Research Design; D005260:Female; D015577:Geriatric Assessment / Q000706:statistics & numerical data*; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D012042:Registries; D013548:Sweden; D014427:Twins
keywords: Bivariate latent growth model; Latent growth model; Longitudinal models; Repeated measures, Multilevel models; Time-varying covariates