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A method to visualize and adjust for selection bias in prevalent cohort studies
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- Törner, Anna (author)
- Department of Epidemiology, Swedish Institute for Infectious Disease Control, Solna, Sweden
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- Dickman, Paul (author)
- Karolinska Institutet
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- Duberg, Ann-Sofi, 1957- (author)
- Department of Infectious Diseases, Örebro University Hospital, Örebro, Sweden
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- (creator_code:org_t)
- 2011-09-13
- 2011
- English.
- In: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 174:8, s. 969-76
- Journal article (peer-reviewed)
Abstract
Subject headings
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- Selection bias and confounding are concerns in cohort studies where the reason for inclusion of subjects in the cohort may be related to the outcome of interest. Selection bias in prevalent cohorts is often corrected by excluding observation time and events during the first time period after inclusion in the cohort. This time period must be chosen carefully-long enough to minimize selection bias but not too long so as to unnecessarily discard observation time and events. A novel method visualizing and estimating selection bias is described and exemplified by using 2 real cohort study examples: a study of hepatitis C virus infection and a study of monoclonal gammopathy of undetermined significance. The method is based on modeling the hazard for the outcome of interest as a function of time since inclusion in the cohort. The events studied were "hospitalizations for kidney-related disease" in the hepatitis C virus cohort and "death" in the monoclonal gammopathy of undetermined significance cohort. Both cohorts show signs of considerable selection bias as evidenced by increased hazard in the time period after inclusion in the cohort. The method was very useful in visualizing selection bias and in determining the initial time period to be excluded from the analyses.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- cohort studies; cubic spline; epidemiologic methods; hepatitis C; monoclonal gammopathy of undetermined significance; selection bias
- Public health
- Folkhälsovetenskap
- Mathematical Statistics
Publication and Content Type
- ref (subject category)
- art (subject category)
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