{"title":"Hazard Ratio Estimators after Terminating Observation within Matched Pairs in Sibling and Propensity Score Matched Designs.","authors":"Tomohiro Shinozaki, Mohammad Ali Mansournia","doi":"10.1515/ijb-2017-0103","DOIUrl":null,"url":null,"abstract":"<p><p>Similar to unmatched cohort studies, matched cohort studies may suffer from the censoring of events prior to the end of follow-up. Moreover, in some matched-pair cohort studies, observation time is prematurely terminated immediately after the follow-up of his/her matched member is completed by an event or censoring. Although the follow-up termination within matched pairs may or may not change the hazard ratio estimators, when and how the change occurs has not been clarified. We study the change in the estimates of the hazard ratio conditional on matched pairs and/or covariates by considering two types of matched-pair designs in cohort studies-sibling pair matching and propensity score matching-in which termination can be naturally considered. If all possible confounders are shared within the matched pairs, after termination, a wide range of hazard ratio estimators coincides with that obtained from a stratified Cox model. If unshared confounders should be adjusted for in the analysis, however, such coincidence is not observed. Simulation studies on sibling designs with unshared confounders suggested that the pair-stratified covariate-adjusted Cox model for the hazard ratio conditional on matched pairs and covariates is generally preferred, for which termination does not deteriorate the estimation. Conversely, the comparison between stratifying or not stratifying on pair is a more subtle issue in propensity score matching which targets a marginal or covariate-conditional hazard ratio. Based on simulation studies considering Cox models after matching based on estimated propensity scores, we discourage pair-stratified analysis and termination, particularly after data collection.</p>","PeriodicalId":49058,"journal":{"name":"International Journal of Biostatistics","volume":"15 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2019-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/ijb-2017-0103","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biostatistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1515/ijb-2017-0103","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
Similar to unmatched cohort studies, matched cohort studies may suffer from the censoring of events prior to the end of follow-up. Moreover, in some matched-pair cohort studies, observation time is prematurely terminated immediately after the follow-up of his/her matched member is completed by an event or censoring. Although the follow-up termination within matched pairs may or may not change the hazard ratio estimators, when and how the change occurs has not been clarified. We study the change in the estimates of the hazard ratio conditional on matched pairs and/or covariates by considering two types of matched-pair designs in cohort studies-sibling pair matching and propensity score matching-in which termination can be naturally considered. If all possible confounders are shared within the matched pairs, after termination, a wide range of hazard ratio estimators coincides with that obtained from a stratified Cox model. If unshared confounders should be adjusted for in the analysis, however, such coincidence is not observed. Simulation studies on sibling designs with unshared confounders suggested that the pair-stratified covariate-adjusted Cox model for the hazard ratio conditional on matched pairs and covariates is generally preferred, for which termination does not deteriorate the estimation. Conversely, the comparison between stratifying or not stratifying on pair is a more subtle issue in propensity score matching which targets a marginal or covariate-conditional hazard ratio. Based on simulation studies considering Cox models after matching based on estimated propensity scores, we discourage pair-stratified analysis and termination, particularly after data collection.
期刊介绍:
The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.