Alternatives to Randomized Trials for Estimating Treatment Effects
作者
Thomas B. Newman,Michael A. Kohn
出处
期刊:Cambridge University Press eBooks [Cambridge University Press] 日期:2020-05-04卷期号:: 231-249
标识
DOI:10.1017/9781108500111.010
摘要
We said in Chapter 8 that randomized blinded trials are the best way to estimate treatment effects because they minimize the potential for confounding, co-interventions, and bias, thus maximizing the strength of causal inference. However, sometimes observational studies can be attractive alternatives to randomized trials because they may be more feasible, ethical, or elegant. Of course, the issue of inferring causality from observational studies is a major topic in classical risk factor epidemiology. In this chapter, we focus on observational studies of treatments rather than risk factors, describing methods of reducing or assessing confounding that are particularly applicable to such studies.