Meta‐Regression Models and Observational Research
指出，在观察性研究中，由于作者可能追求统计显著性，元回归模型容易产生假阳性结果，误判为真实效应。这提醒研究者在使用元回归时需谨慎，并呼吁更多研究来改进模型设定。
Abstract Meta‐regression models were originally developed for the synthesis of experimental research where randomization ensures unbiased and consistent estimation of the effect of interest. Most economics research is, however, observational and specification searches may often result in estimates that are biased and inconsistent, for example, due to omitted‐variable biases. We show that if the authors of primary studies search for statistically significant estimates in observational research, meta‐regression models tend to make false‐positive findings of genuine empirical effects. More research is needed to better understand how meta‐regression models need to be specified to help identifying genuine empirical effects in observational research.