Reducing the length of mental health instruments through structurally incomplete designs

Niels Smits, Pim Cuijpers, Aartjan T.F. Beekman, Johannes H. Smit

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)


This paper presents structurally incomplete designs as an approach to reduce the length of mental health tests. In structurally incomplete test designs, respondents only fill out a subset of the total item set. The scores on the unadministered items are estimated using methods for missing data. As an illustration, structurally incomplete test designs recording, respectively, two thirds, one half, one third and one quarter of the complete item set were applied to item scores on the Centre of Epidemiological Studies-Depression (CES-D) scale of the respondents in the Longitudinal Aging Study Amsterdam (LASA). The resulting unobserved item scores were estimated with the missing data method Data Augmentation. The complete and reconstructed data yielded very similar total scores and depression classifications. In contrast, the diagnostic accuracy of the incomplete designs decreased as the designs had more unobserved item scores. The discussion addresses the strengths and limitations of the application of incomplete designs in mental health research.

Original languageEnglish
Pages (from-to)150-160
Number of pages11
JournalInternational journal of methods in psychiatric research
Issue number3
Publication statusPublished - Sept 2007


  • Aged
  • Aged, 80 and over
  • Aging
  • Data augmentation
  • Diagnostics accuracy
  • Female
  • Humans
  • Journal Article
  • Male
  • Mental Disorders
  • Middle Aged
  • Missing data
  • Multiple imputation
  • Psychological Tests
  • Structurally incomplete designs
  • Time Factors

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