A method to compute multiplicity corrected confidence intervals for odds ratios and other relative effect estimates.
Epidemiological studies commonly test multiple null hypotheses. In some situations it may be appropriate to account for multiplicity using statistical methodology rather than simply interpreting results with greater caution as the number of comparisons increases. Given the one-to-one relationship that exists between confidence intervals and hypothesis tests, we derive a method based upon the Hochberg step-up procedure to obtain multiplicity corrected confidence intervals (CI) for odds ratios (OR) and by analogy for other relative effect estimates. In contrast to previously published methods that explicitly assume knowledge of P values, this method only requires that relative effect estimates and corresponding CI be known for each comparison to obtain multiplicity corrected CI.
Efird
Jimmy Thomas
JT
Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, S.9.548 (MLC 7000), Cincinnati, Ohio 45229-3039, USA. jimmy.efird@stanfordalumni.org
Nielsen
Susan Searles
SS
D004782:Environmental Health / Q000706:statistics & numerical data*; D016021:Epidemiologic Studies; D013223:Statistics as Topic / Q000379:methods*