title: Measurement invariance in longitudinal clinical research assuming change from development and intervention.
abstract: Valid and reliable measures of psychological and behavioral constructs are critical to clinical research, particularly longitudinal treatment research, in which multiple groups are compared over time for possible changes within and between constructs as a result of intervention or development. Structural equation modeling (SEM) analysis is a class of statistical procedures that can be used to test multiple hypotheses about these relationships simultaneously while controlling for measurement error. The procedures have been applied primarily to testing between-construct relationships in nonexperimental studies, with relatively little emphasis on establishing whether measures are sufficiently invariant across groups and across time to permit these tests. This article uses an empirical example of a longitudinal experimental prevention study with two groups to illustrate the use of SEM, first, to systematically test measurement invariance across groups at each wave of measurement, and second, after establishing measurement invariance, to test structural invariance longitudinally.
authors.affiliation: Department of Preventive Medicine, University of Southern California, Alhambra 91803.
authors.forename: M A
authors.initials: MA
authors.lastname: Pentz
authors.forename: C P
authors.initials: CP
authors.lastname: Chou
mesh_terms: D000293:Adolescent; D002648:Child; D005163:Factor Analysis, Statistical; D005260:Female; D005500:Follow-Up Studies; D006266:Health Education / Q000706:statistics & numerical data*; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D010043:Outcome and Process Assessment, Health Care; D019966:Substance-Related Disorders / Q000453:epidemiology / Q000517:prevention & control*