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Case-Control Study Design What, when, and why?

Case-Control Study Design What, when, and why? EDITORIAL Case-Control Study Design What, when, and why? Jayawant N. Mandrekar, PhD, and Sumithra J. Mandrekar, PhD n this issue of the Journal of Thoracic Oncology, Berthiller et al. present the results of Ia pooled analysis of three hospital based case-control studies performed to estimate the risk of lung cancer from cannabis smoking in men. Data regarding smoking, demograph- ics, and occupational exposures were gathered through a questionnaire. In two of the three studies, each case (men with primary incident lung cancer) was matched to one or two controls based on age and place of residence and matched on age, gender, and place of residence in the third study. The authors use an unconditional logistic regression model to obtain the study specific and pooled odds ratio estimates. All analyses were performed on the complete set of cases and controls as well as on data with the recoded missing variables. The analyses techniques used in this article include unconditional logistic regression models, pooling of data without stratifying by study, and testing for between study heterogeneity, and the (biased) approaches for recoding the missing data. These approaches are somewhat inappropriate, however, in this editorial we will focus only on the case-control http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Thoracic Oncology Wolters Kluwer Health

Case-Control Study Design What, when, and why?

Mandrekar, Sumithra J.
Journal of Thoracic Oncology , Volume 3 (12) – Dec 1, 2008
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References (5)

ISSN
1556-0864
DOI
10.1097/JTO.0b013e31818dd97b
pmid
19057257
Publisher site
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Abstract

EDITORIAL Case-Control Study Design What, when, and why? Jayawant N. Mandrekar, PhD, and Sumithra J. Mandrekar, PhD n this issue of the Journal of Thoracic Oncology, Berthiller et al. present the results of Ia pooled analysis of three hospital based case-control studies performed to estimate the risk of lung cancer from cannabis smoking in men. Data regarding smoking, demograph- ics, and occupational exposures were gathered through a questionnaire. In two of the three studies, each case (men with primary incident lung cancer) was matched to one or two controls based on age and place of residence and matched on age, gender, and place of residence in the third study. The authors use an unconditional logistic regression model to obtain the study specific and pooled odds ratio estimates. All analyses were performed on the complete set of cases and controls as well as on data with the recoded missing variables. The analyses techniques used in this article include unconditional logistic regression models, pooling of data without stratifying by study, and testing for between study heterogeneity, and the (biased) approaches for recoding the missing data. These approaches are somewhat inappropriate, however, in this editorial we will focus only on the case-control

Journal

Journal of Thoracic Oncology – Wolters Kluwer Health

Published: Dec 1, 2008

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