Columbia University, Department of Biostatistics

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Presentation transcript:

Columbia University, Department of Biostatistics Using Published Prevalence estimates to perform difference-in-Difference Tests Christine Mauro, PhD Columbia University, Department of Biostatistics JSM, July 30, 2018 cmm2212@cumc.columbia.edu

Introduction Colorado and Washington first two states with Recreational Marijuana Laws (RML) enacted 2012, fully implemented 2014 Goal: Assess impact of RML on marijuana use in Washington and Colorado Examine changes in the prevalence of past-month marijuana use from 2010-2011 to 2015-2016 using a difference-in-difference (DID) analysis. Statistical Challenge: Data limited to published two-year state-level prevalence estimates and confidence intervals (CIs).

Statistical Methods Derive standard errors from confidence intervals For each state (and US) and year, simulate 10K observations from a normal distribution mean=published prevalence, sd=derived standard error. From simulated data, Obtain 10K estimates of change (Δ) in use for CO, WA, and the US (2015-16 vs. 2010-11) Obtain 10K diff-in-diff estimates (ΔCO - ΔUS; Δ WA - ΔUS) 95% CI: Extract 2.5th and 97.5th percentiles of 10K diff-in-diff estimates CIs not crossing zero  statistically significant change post RML

Results Overall Trends in past-month marijuana use: ↓ among those aged 12-17 ↑ among those 18-25 and 26+. After RML in Colorado: No differential change for 12-17 year olds or those 18-25. Significantly larger ↑ for those 26+, DID=+3.7% = 5.8 - 2.1. After RML in Washington: No differential change for any age group. Extracting standard errors from published CIs allows for testing of simple research hypotheses using simulation methods.