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Step 2.2: estimating the treatment effect via random-effects logistic regression model
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Once the matched dataset was formed, a random-effects logit model was estimated:
where Zij denotes the treatment status of ith subject within jth study, exp(θ) is the pooled odds ratio to be estimated, is the study-specific random intercept, is the study-specific random slope, is the estimated propensity score from PSM model and ω is the corresponding parameter of the estimated propensity score.
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