Procedures that assess inconsistency in meta-analyses can assess the likelihood of response bias in multiwave surveys

Victor M. Montori, Teresa W. Leung, Stephen D. Walter, Gordon H. Guyatt

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Background and Objective: Response bias may affect the result of surveys with <100% response rate. We applied methods commonly used in meta-analysis to ascertain the extent to which response bias affects multiwave survey results. Methods: To test hypotheses of between-wave similarity, we used the Cochran-Armitage test for trends and the Q-test of heterogeneity across waves in a survey of 2,127 North American clinicians using six e-mail waves and one fax wave and achieving a response rate of 22%. We used the I2 statistic To quantify the extent of inconsistency in survey outcomes across waves not due to within-wave random error (i.e., inconsistency due to response bias). Results: With this survey, tests of heterogeneity and trend were not significant and I2 equaled 0%. These results suggest that the underlying responses did not differ across waves and thus strengthened the inference that response bias was not affecting the interpretation of the survey. Conclusion: Researchers can use procedures that assess inconsistency in meta-analyses to evaluate the validity of a multiwave survey with a less than optimal response rate.

Original languageEnglish (US)
Pages (from-to)856-858
Number of pages3
JournalJournal of Clinical Epidemiology
Volume58
Issue number8
DOIs
StatePublished - Aug 2005

Keywords

  • Heterogeneity
  • I statistic
  • Inconsistency
  • Q-test
  • Response bias
  • Surveys, multiwave

ASJC Scopus subject areas

  • Epidemiology

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