Center for Epidemiologic Studies-Depression scale (CES-D) item response bias found with Mantel-Haenszel method was successfully replicated using latent variable modeling

Frances M. Yang, Richard N. Jones

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Objective: This study reexamines findings reported by Cole et al. of item response bias in the Center for Epidemiologic Studies-Depression (CES-D) scale by age, gender, and race. We use an item response theory-based latent variable conditioning approach. Study Design and Setting: We used the multiple indicators, multiple causes (MIMIC) model framework to estimate measurement bias in the CES-D responses of participants in the New Haven Established Populations for the Epidemiologic Studies of the Elderly study (N = 2,340). Results: Measurement bias attributable to race was significant for the following two CES-D items: people "are unfriendly" and "dislike me". The proportional odds of a higher-category response by blacks relative to whites on these items were 2.35 (95% confidence interval [CI]: 1.65, 3.36) and 3.11 (95% CI: 2.04, 4.76), respectively. The proportional odds were higher among women (2.03 [95% CI: 1.35, 3.06]) relative to men for the CES-D item "crying.". Conclusion: Our findings confirm that three items on the CES-D show strong evidence of item response bias. The MIMIC model is preferable to the Mantel-Haenszel approach because it conditions on a latent variable, although the effect estimates can also be interpreted using a proportional odds framework.

Original languageEnglish (US)
Pages (from-to)1195-1200
Number of pages6
JournalJournal of Clinical Epidemiology
Volume60
Issue number11
DOIs
StatePublished - Nov 1 2007

Keywords

  • Center for Epidemiological Studies-Depression (CES-D)
  • Differential item functioning (DIF)
  • Established Populations for the Epidemiologic Studies of the Elderly (EPESE)
  • Item response theory (IRT)
  • Late-life depression
  • Multiple indicators, multiple causes (MIMIC) model

ASJC Scopus subject areas

  • Epidemiology

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