Title

Data Analysis and Modeling Longitudinal Processes

Publication Type

Journal Article

Publication Date

1-2003

Abstract

This article presents a nontechnical overview of the major data analysis techniques for modeling longitudinal processes, with an explicit focus on their advantages and disadvantages as tools for drawing inferences about different specific aspects of change over time. It is argued that traditional longitudinal analysis techniques offer limited ways of addressing many specific questions about change. Recent advances in latent variable techniques, when adequately driven by theory, design, and measurement, offer a unified and flexible framework for addressing such questions.

Keywords

longitudinal analysis, assessment of change, latent variable, growth modeling

Discipline

Quantitative Psychology

Research Areas

Psychology

Publication

Group and Organization Management

Volume

28

Issue

3

First Page

341

Last Page

365

ISSN

1059-6011

Identifier

10.1177/1059601102250814

Publisher

SAGE

Additional URL

http://dx.doi.org/10.1177/1059601102250814

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