From the Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
Center for Health and Community, School of Medicine, University of California, San Francisco.
Epidemiology. 2022 Sep 1;33(5):689-698. doi: 10.1097/EDE.0000000000001502. Epub 2022 Jun 24.
Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.
违反阳性假设(也称为共同支持条件)会对健康政策研究产生挑战,并可能导致重大偏差、方差增大和无效推断。我们在单时间点和多时间点(即纵向)健康政策评估设置中定义阳性,并讨论对阳性的实际威胁。我们展示了当试图估计健康政策(在这种情况下,纳洛酮获取法)的效果时,可能会出现实际阳性违反的经验证据。在这种情况下,一种替代方法是估计法律颁布的转变的效果(例如,如果颁布推迟了若干年的效果)。这种效果对应于所谓的修改后的治疗政策,并且极大地削弱了所需的阳性假设,从而提供了一种即使在存在严重阳性问题的情况下也可以估计政策效果的手段。我们应用该方法来定义和估计纳洛酮获取法对阿片类药物过量率的纵向影响。