期刊
STATISTICS IN BIOPHARMACEUTICAL RESEARCH
卷 15, 期 1, 页码 125-132出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/19466315.2021.1942975
关键词
Causal inference; Generalizability; Post-stratification; Propensity score; Randomized clinical trial
This article reviews the process of estimating the external validity of treatment effects from clinical trials, i.e., how to generalize trial results to the target population. The traditional method of adjusting trial results is post-stratification and reweighting, while contemporary methods use stratification and weighting techniques based on individual-level population data. These methods are more flexible but require additional data.
The external validity of the estimated treatment effect from a clinical trial is in doubt when there are effect modifiers whose distribution in the target population differs from that in the trial. Adjusting an estimated treatment effect from a trial to predict its likely value for the target population is a process known as generalization. We review classical and contemporary approaches to this problem. The traditional method is post-stratification, or the reweighting of stratum-specific treatment effect estimates by population distribution proportions. Contemporary methods employ stratification or weighting techniques based on estimates of the probability that an individual is included in the trial, akin to the propensity score. These methods are more flexible in that they readily accommodate continuous effect modifiers. Estimating the probabilities, however, requires in principle that one have individual-level population data, which are seldom available for pharmaceutical trials. When the effect modifiers are all discrete, the post-stratification and probability-weighting approaches give essentially the same estimates. Naively computed standard errors with the contemporary methods may be inflated. We illustrate and compare generalization methods in a simulation and using data from the Lipids Research Clinics Coronary Primary Prevention Trial and the New York School Choice Experiment.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据