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Influence of model‐building strategies on the results of a case‐control study
Author(s) -
Blettner Maria,
Sauerbrei Willi
Publication year - 1993
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780121405
Subject(s) - computer science , control (management) , variation (astronomy) , selection (genetic algorithm) , missing data , sensitivity (control systems) , variable (mathematics) , risk analysis (engineering) , econometrics , operations research , data mining , machine learning , artificial intelligence , medicine , mathematics , engineering , mathematical analysis , physics , electronic engineering , astrophysics
We evaluate the analysis of a case‐control study in which many variables were investigated simultaneously. The purpose of the study was to explore some rather unspecific hypotheses about potential risk factors for adult brain tumour. Our aim is to show that in the analysis of case‐control studies many decisions are necessary which are usually not published in detail. As in most studies these decisions are made during analysis and are data dependent. We demonstrate that the data allow sensible alternative decisions which influence the final results. A sensitivity analysis of several aspects of the analysis such as different measurement scales, variable selection, handling of missing values and interactions was performed, and demonstrated variation in the results based on the strategy for analysis. We conclude that details of the final analysis should be decided in the planning phase of a case‐control study, and that more details of model‐building strategies must be published. Results from a study where the analysis is highly data dependent must be interpreted with caution and validation of the results with new studies is essential.