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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)