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J Clin Epidemiol. 2014 Jul;67(7):821-9. doi: 10.1016/j.jclinepi.2014.02.008. Epub 2014 Apr 24.

Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study.

Author information

1
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 107, 3584 CL Utrecht, The Netherlands. Electronic address: a.f.schmidt@umcutrecht.nl.
2
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands.
3
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; RIVM, National Institute for Public Health and the Environment Centre for Infectious Disease Control Netherlands (CIb) Epidemiology and Surveillance Unit (EPI), P.O. Box 1, 3720 BA Bilthoven, The Netherlands.
4
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands.
5
Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 107, 3584 CL Utrecht, The Netherlands.
6
Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands.

Abstract

OBJECTIVE:

To give a comprehensive comparison of the performance of commonly applied interaction tests.

METHODS:

A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow-Day (BD), Tarone, unconditional score, likelihood ratio (LR), Wald, and relative excess risk due to interaction (RERI)-based tests.

RESULTS:

Review results agreed with results from our simulation study, which showed that on the OR scale, in small sample sizes (eg, number of subjects ≤ 250) the type 1 error rates of the LR test was 0.10; the BD and Tarone tests showed results around 0.05. On the RD scale, the LR and RERI tests had error rates around 0.05. On both scales, tests did not differ regarding power. When exposure prevented the outcome RERI-based tests were relatively underpowered (eg, N = 100; RERI power = 5% vs. Wald power = 18%). With increasing sample size, difference decreased.

CONCLUSION:

In small samples, interaction tests differed. On the OR scale, the Tarone and BD tests are recommended. On the RD scale, the LR and RERI-based tests performed best. However, RERI-based tests are underpowered compared with other tests, when exposure prevents the outcome, and sample size is limited.

KEYWORDS:

Effect modification; Epidemiologic methods; Interaction; Odds ratio; Relative excess risk due to interaction; Review; Risk ratio; Simulation; Statistics; Subgroups

PMID:
24768005
DOI:
10.1016/j.jclinepi.2014.02.008
[Indexed for MEDLINE]

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