TY - JOUR
T1 - Reducing the length of mental health instruments through structurally incomplete designs
AU - Smits, Niels
AU - Cuijpers, Pim
AU - Beekman, Aartjan T.F.
AU - Smit, Johannes H.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
KW - Data augmentation
KW - Diagnostics accuracy
KW - Missing data
KW - Multiple imputation
KW - Structurally incomplete designs
UR - http://www.scopus.com/inward/record.url?scp=34648843060&partnerID=8YFLogxK
U2 - 10.1002/mpr.223
DO - 10.1002/mpr.223
M3 - Article
C2 - 17849433
AN - SCOPUS:34648843060
VL - 16
SP - 150
EP - 160
JO - International Journal of Methods in Psychiatric Research
JF - International Journal of Methods in Psychiatric Research
SN - 1049-8931
IS - 3
ER -