Description

Time metric is an important consideration for all longitudinal models because it can influence the interpretation of estimates, parameter estimate accuracy, and model convergence in longitudinal models with latent variables.

Time metric is an important consideration for all longitudinal models because it can influence the interpretation of estimates, parameter estimate accuracy, and model convergence in longitudinal models with latent variables. Currently, the literature on latent difference score (LDS) models does not discuss the importance of time metric. Furthermore, there is little research using simulations to investigate LDS models. This study examined the influence of time metric on model estimation, interpretation, parameter estimate accuracy, and convergence in LDS models using empirical simulations.

Reuse Permissions
  • 1.13 MB application/pdf

    Download count: 0

    Details

    Contributors
    Date Created
    • 2016
    Resource Type
  • Text
  • Collections this item is in
    Note
    • Partial requirement for: Ph. D., Arizona State University, 2016
      Note type
      thesis
    • Includes bibliographical references (pages 37-40)
      Note type
      bibliography
    • Field of study: Psychology

    Citation and reuse

    Statement of Responsibility

    by Holly P. O'Rourke

    Machine-readable links