Abstract:
:We consider the design of both cohort and case-control studies in which an initial ('stage 1') sample of complete data on an error-free disease indicator (D), a correct ('gold standard') dichotomous exposure measurement (X) and an error-prone exposure measurement (Z) are available. We calculate the amount of additional information on the odds ratio relating D to X that one can obtain from a second ('stage 2') sample of measurements only on D and Z. If one allows for differential measurement error in Z, there is often little advantage in having more than four times as much data in stage 2 data as in stage 1. With the assumption that a non-differential measurement error model is reasonable, larger amounts of stage 2 data can be useful. Simulations indicate that stage 1 samples of modest size (50 cases in case-control studies and 50 failures in cohort studies) yield sufficiently reliable estimates of needed parameters to assist in determining an appropriate size for the stage 2 sample. These ideas apply in settings either where the amount of stage 1 data is limited and fixed by external constraints or where one has gathered stage 1 data in advance to avoid collecting superfluous stage 2 data.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Dahm PF,Gail MH,Rosenberg PS,Pee Ddoi
10.1002/sim.4780142307subject
Has Abstractpub_date
1995-12-15 00:00:00pages
2581-98issue
23eissn
0277-6715issn
1097-0258journal_volume
14pub_type
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