The difference between two proportions, referred to as a risk difference, is a useful measure of effect size in studies where the response variable is dichotomous. Confidence interval methods based on a varying coefficient model are proposed for combining and comparing risk differences from multi-study between-subjects or within-subjects designs. The proposed methods are new alternatives to the popular constant coefficient and random coefficient methods. The proposed varying coefficient methods do not require the constant coefficient assumption of effect size homogeneity, nor do they require the random coefficient assumption that the risk differences from the selected studies represent a random sample from a normally distributed superpopulation of risk differences. The proposed varying coefficient methods are shown to have excellent finite-sample performance characteristics under realistic conditions.