著者
Hisashi Noma Munechika Misumi Shiro Tanaka
出版者
Japan Epidemiological Association
雑誌
Journal of Epidemiology (ISSN:09175040)
巻号頁・発行日
pp.JE20210509, (Released:2022-06-25)
参考文献数
40
被引用文献数
1 2

Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have been widely used because of their computational simplicity. However, the resultant odds ratio estimates cannot be interpreted as relative risk measures unless the event rate is low. The risk ratio and risk difference are more favorable outcome measures that are directly interpreted as effect measures without the rare disease assumption.Methods: We provide pseudo-Poisson and pseudo-normal linear regression methods for estimating risk ratios and risk differences in analyses of case-cohort studies. These multivariate regression models are fitted by weighting the inverses of sampling probabilities. Also, the precisions of the risk ratio and risk difference estimators can be improved using auxiliary variable information, specifically by adapting the calibrated or estimated weights, which are readily measured on all samples from the whole cohort. Finally, we provide computational code in R (R Foundation for Statistical Computing, Vienna, Austria) that can easily perform these methods.Results: Through numerical analyses of artificially simulated data and the National Wilms Tumor Study data, accurate risk ratio and risk difference estimates were obtained using the pseudo-Poisson and pseudo-normal linear regression methods. Also, using the auxiliary variable information from the whole cohort, precisions of these estimators were markedly improved.Conclusion: The ordinary logistic regression analyses may provide uninterpretable effect measure estimates, and the risk ratio and risk difference estimation methods are effective alternative approaches for case-cohort studies. These methods are especially recommended under situations in which the event rate is not low.

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#J_Epidemi Thank You Authors! 2023: Risk Ratio and Risk Difference Estimation in Case-cohort Studies Hisashi Noma, et al. https://t.co/0TsSER4qaG
Risk Ratio and Risk Difference Estimation in Case-cohort Studies https://t.co/yFiuMSI0m3
#J_Epidemi 2023 October issue: Risk Ratio and Risk Difference Estimation in Case-cohort Studies Hisashi Noma et al. https://t.co/0TsSER4qaG @J_Epidemi https://t.co/7HjbSWfKCy
J-STAGE Articles - Risk Ratio and Risk Difference Estimation in Case-cohort Studies https://t.co/yzzIWq1zVj
Risk Ratio and Risk Difference Estimation in Case-cohort Studies(Journal of Epidemiology, 早期公開, 2版: 2022/10/19) https://t.co/8csMZR0q2H

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