Includes bibliographical references (pages 263-273) and indexes.
Introduction -- Unconditional latent curve model -- Missing data and alternative metrics of time -- Nonlinear trajectories and the coding of time -- Conditional latent curve models -- The analysis of groups -- Multivariate latent curve models -- Extensions of latent curve models.
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"The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories."--Jacket.