Literature DB >> 16704513

When to combine hypotheses and adjust for multiple tests.

Peter J Veazie1.   

Abstract

OBJECTIVE: To provide guidelines for identifying composite hypotheses and addressing the probability of false rejection for multiple hypotheses. DATA SOURCES AND STUDY
SETTING: Examples from the literature in health services research are used to motivate the discussion of composite hypothesis tests and multiple hypotheses.
METHODS: This article is a didactic presentation. PRINCIPAL
FINDINGS: It is not rare to find mistaken inferences in health services research because of inattention to appropriate hypothesis generation and multiple hypotheses testing. Guidelines are presented to help researchers identify composite hypotheses and set significance levels to account for multiple tests.
CONCLUSIONS: It is important for the quality of scholarship that inferences are valid: properly identifying composite hypotheses and accounting for multiple tests provides some assurance in this regard.

Mesh:

Year:  2006        PMID: 16704513      PMCID: PMC1713204          DOI: 10.1111/j.1475-6773.2006.00512.x

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  5 in total

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Authors:  K J Rothman
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Review 3.  Multiple comparisons, explained.

Authors:  S N Goodman
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Review 4.  Describing data requires no adjustment for multiple comparisons: a reply from Savitz and Olshan.

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5.  Multiple comparisons and related issues in the interpretation of epidemiologic data.

Authors:  D A Savitz; A F Olshan
Journal:  Am J Epidemiol       Date:  1995-11-01       Impact factor: 4.897

  5 in total
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