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Table 3 Policy effects derived from the seven methods based on education-stratified analysis and the inclusion of interaction terms

From: Assessing the impact of natural policy experiments on socioeconomic inequalities in health: how to apply commonly used quantitative analytical methods?

Method Specification Low-educated [95% CI] High-educated [95% CI] Interaction term [95% CI]
Regression adjustment Logistic regression, adjusted for gender 0.647 [0.570, 0.734] (odds ratio) 0.679 [0.550, 0.839] (odds ratio) 0.953 [0.745, 1.218] (odds ratio)
Propensity score matching Matched on gender −0.048 [-0.065, -0.031] (probability difference) −0.020 [-0.031, -0.009] (probability difference) Not applicable
Difference-in-differences Logistic regression 0.666 [0.574, 0.773] (odds ratio) 0.687 [0.530, 0.890] (odds ratio) 0.970 [0.719, 1.307] (odds ratio)
Fixed effects Linear regression, adjusted for time −0.044 [-0.051, -0.037] (probability difference) −0.016 [-0.023, -0.009] (probability difference) −0.029 [-0.039, -0.019] (probability difference)
Instrumental variable Probit regression −0.050 [-0.063, -0.037] (probability difference) −0.020 [-0.029, -0.011] (probability difference) −0.036 [-0.057, -0.015] (probability difference)
Regression discontinuity Logistic regression around the income threshold 0.678 [0.495, 0.929] (odds ratio) 0.687 [0.483, 0.977] (odds ratio) 0.987 [0.615, 1.583] (odds ratio)
Interrupted time-series Linear regression −0.023 [-0.027,-0.020] (probability difference) −0.005 [-0.008, -0.002] (probability difference) −0.019 [-0.023, -0.014] (probability difference)