N Kreiger1, E D Nishri. 1. Division of Preventive Oncology, Ontario Cancer Treatment and Research Foundation, Toronto, Canada.
Abstract
PURPOSE: Although it is understood that low response rates can bias a study's results and that follow-up can increase response rates, the effect of follow-up on the odds ratio estimates in a case-control study is not obvious. METHODS: We used the data from a case-control study of renal cell carcinoma conducted in Ontario. Information on risk factors was collected with a mailed questionnaire; the number of telephone or mail follow-ups attempted was recorded. Sex, age group, residence, and follow-up method were known for all cases and controls. RESULTS: Cases, women, subjects under age 60, subjects living outside of Toronto, and subjects with telephone follow-up were all more likely to be respondents. This pattern of response did not bias the odds ratio estimates. Over all categories of follow-up intensity, the odds ratio estimates for the risk factors varied little. For example, the odds ratio estimate for ever smoking cigarettes ranged from 1.94 to 2.01 for males and from 2.27 to 1.80 for females. CONCLUSIONS: The data indicate that the substantive conclusions of the study would not have changed if response rates had been lower. There is a suggestion, however, that the odds ratios for smoking by men may be overestimated.
PURPOSE: Although it is understood that low response rates can bias a study's results and that follow-up can increase response rates, the effect of follow-up on the odds ratio estimates in a case-control study is not obvious. METHODS: We used the data from a case-control study of renal cell carcinoma conducted in Ontario. Information on risk factors was collected with a mailed questionnaire; the number of telephone or mail follow-ups attempted was recorded. Sex, age group, residence, and follow-up method were known for all cases and controls. RESULTS: Cases, women, subjects under age 60, subjects living outside of Toronto, and subjects with telephone follow-up were all more likely to be respondents. This pattern of response did not bias the odds ratio estimates. Over all categories of follow-up intensity, the odds ratio estimates for the risk factors varied little. For example, the odds ratio estimate for ever smoking cigarettes ranged from 1.94 to 2.01 for males and from 2.27 to 1.80 for females. CONCLUSIONS: The data indicate that the substantive conclusions of the study would not have changed if response rates had been lower. There is a suggestion, however, that the odds ratios for smoking by men may be overestimated.
Authors: Mohammad Siahpush; Raees A Shaikh; Melissa Tibbits; Terry T-K Huang; Gopal K Singh Journal: Int J Environ Res Public Health Date: 2013-07-12 Impact factor: 3.390
Authors: Jean-Paul Chretien; Laura K Chu; Tyler C Smith; Besa Smith; Margaret A K Ryan Journal: BMC Med Res Methodol Date: 2007-01-25 Impact factor: 4.615
Authors: A Rosemary Tate; Margaret Jones; Lisa Hull; Nicola T Fear; Roberto Rona; Simon Wessely; Matthew Hotopf Journal: BMC Med Res Methodol Date: 2007-11-28 Impact factor: 4.615