{"title":"Stata提示146:使用泊松回归模型后的余量来估计干预措施阻止的事件数量","authors":"M. Falcaro, R. Newson, P. Sasieni","doi":"10.1177/1536867X221106437","DOIUrl":null,"url":null,"abstract":"After fitting a Poisson regression model to evaluate the effect of an intervention in a cohort study, one might be interested in estimating the number of events prevented by the intervention (assuming the observed associations are causal). This can be derived as the difference in the intervention group between the predicted number of events under the counterfactual (no intervention) and the factual (intervention) scenarios. One could use the predict command to obtain the predicted number of events under the two scenarios and then sum up the differences, but this approach would not be conve-nient for several reasons. One would need to change the intervention variable to get the counterfactual predicted values, and the confidence intervals would not be readily available ( bootstrap or jackknife could be used, but this could be particularly time consuming if the dataset is large). We here suggest the margins command. Its use, however, is not straight-forward for our specific problem margins computes observation then the these","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Stata tip 146: Using margins after a Poisson regression model to estimate the number of events prevented by an intervention\",\"authors\":\"M. Falcaro, R. Newson, P. Sasieni\",\"doi\":\"10.1177/1536867X221106437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"After fitting a Poisson regression model to evaluate the effect of an intervention in a cohort study, one might be interested in estimating the number of events prevented by the intervention (assuming the observed associations are causal). This can be derived as the difference in the intervention group between the predicted number of events under the counterfactual (no intervention) and the factual (intervention) scenarios. One could use the predict command to obtain the predicted number of events under the two scenarios and then sum up the differences, but this approach would not be conve-nient for several reasons. One would need to change the intervention variable to get the counterfactual predicted values, and the confidence intervals would not be readily available ( bootstrap or jackknife could be used, but this could be particularly time consuming if the dataset is large). We here suggest the margins command. Its use, however, is not straight-forward for our specific problem margins computes observation then the these\",\"PeriodicalId\":51171,\"journal\":{\"name\":\"Stata Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stata Journal\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1177/1536867X221106437\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X221106437","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
Stata tip 146: Using margins after a Poisson regression model to estimate the number of events prevented by an intervention
After fitting a Poisson regression model to evaluate the effect of an intervention in a cohort study, one might be interested in estimating the number of events prevented by the intervention (assuming the observed associations are causal). This can be derived as the difference in the intervention group between the predicted number of events under the counterfactual (no intervention) and the factual (intervention) scenarios. One could use the predict command to obtain the predicted number of events under the two scenarios and then sum up the differences, but this approach would not be conve-nient for several reasons. One would need to change the intervention variable to get the counterfactual predicted values, and the confidence intervals would not be readily available ( bootstrap or jackknife could be used, but this could be particularly time consuming if the dataset is large). We here suggest the margins command. Its use, however, is not straight-forward for our specific problem margins computes observation then the these
期刊介绍:
The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.