Cited by 31

Structural equation models and the regression bias for measuring correlates of change

Cribbie, Robert A., Jamieson, John·2000·Educational and Psychological Measurement

Abstract

ANCOVA and regression both exhibit a directional bias when measuring correlates of change. This bias confounds the comparison of changes between naturally occurring groups with large pretest differences (ANCOVA), or for identifying predictors of change when the predictor is correlated with pretest (regression). This bias is described in some detail. A computer simulation study is presented, which shows that properly identified structural equation models are not susceptible to this bias. Neither gain scores (posttest minus pretest) nor structural equation models exhibit the “regression bias.” Other factors, such as skewness, that may confound measurement of change are also discussed.

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Crossref · 10.1177/00131640021970970

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  • The use of gain scores is justified by the quasi-experimental setup, the moderation analysis, and the research question.

    “The use of gain scores is justified by both the quasi-experimental setup and the use of a moderation analysis (Cribbie and Jamieson, 2000), as well as the main research question at hand: how do the experimental and the control groups differ with regard to changes in emotional exhaustion and work engagement (Fitzmaurice et al., 2012).”

    From For whom and under what circumstances does email message batching work? (2022) · cites this paper as Cribbie and Jamieson, 2000

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Authors
Cribbie, R. A., & Jamieson, J.
Affiliations
  • University of Manitoba
  • Lakehead University
Venue
Educational and Psychological Measurement
Published
2000-12
Volume
60
Issue
6
Pages
893-907
ISSN
  • 0013-1644
  • 1552-3888
Cited by
31
References
1
Language
en

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