Longitudinal measurement models in evaluation research

Examining stability and change

Steven C. Pitts, Stephen West, Jenn-Yun Tein

Research output: Contribution to journalArticle

138 Citations (Scopus)

Abstract

This article provides an introduction to the use of Confirmatory Factor Analysis to test measurement invariance and stability in longitudinal research. The approach is illustrated through examples representing: (a) one construct, two measurement waves; (b) one construct, three waves; (c) two constructs, two waves; and (d) comparison of treatment and control groups in pre-post designs. Basic issues in establishing measurement invariance over time, across treatment groups, and within measurement waves are discussed. Estimates of the stability coefficients that are corrected for measurement error and method variance associated with each specific measured variable are provided. Establishing measurement invariance is a critical requirement for making inferences about treatment effects and changes in constructs over time.

Original languageEnglish (US)
Pages (from-to)333-350
Number of pages18
JournalEvaluation and Program Planning
Volume19
Issue number4
DOIs
StatePublished - Nov 1996

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evaluation research
Statistical Factor Analysis
Control Groups
Research
factor analysis
Measurement invariance
Evaluation research
Measurement model
evaluation
Group

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Public Health, Environmental and Occupational Health
  • Social Psychology
  • Education
  • Sociology and Political Science

Cite this

Longitudinal measurement models in evaluation research : Examining stability and change. / Pitts, Steven C.; West, Stephen; Tein, Jenn-Yun.

In: Evaluation and Program Planning, Vol. 19, No. 4, 11.1996, p. 333-350.

Research output: Contribution to journalArticle

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