Variation in Performance of Commonly Used Statistical Methods for Estimating Effectiveness of State-Level Opioid Policies on Opioid-Related Mortality

Beth Ann Griffin, Megan S. Schuler, Elizabeth A. Stuart, Stephen Patrick, Elizabeth McNeer, Rosanna Smart, David Powell, Bradley Stein, Terry Schell and Rosalie Pacula

No 27029, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Over the last two decades, there has been a surge of opioid-related overdose deaths resulting in a myriad of state policy responses. Researchers have evaluated the effectiveness of such policies using a wide-range of statistical models, each of which requires multiple design choices that can influence the accuracy and precision of the estimated policy effects. This simulation study used real-world data to compare model performance across a range of important statistical constructs to better understand which methods are appropriate for measuring the impacts of state-level opioid policies on opioid-related mortality. Our findings show that many commonly-used methods have very low statistical power to detect a significant policy effect (

JEL-codes: C1 C12 C15 C18 C22 C23 C4 C52 C54 H0 H51 H7 I18 I28 K32 (search for similar items in EconPapers)
Date: 2020-04
New Economics Papers: this item is included in nep-gen, nep-hea and nep-ore
Note: EH PE
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Citations: View citations in EconPapers (3)

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