Statistical analysis
LCA
REGRESSIONS
To examine the differential impacts of EMAP by baseline experience of IPV reported by women, subgroups of couples are constructed using two different methods. First, subgroups of couples are defined using the binary indicators of IPV experience in the last 12 months, for physical and sexual violence. Throughout the paper, we use the terms “physical and sexual IPV” and “physical and sexual violence” interchangeably. A couple is in the “physically violent” subgroup if the female partner of the male participant reported an instance of physical violence perpetrated by her intimate partner in the 12 months prior to baseline. Similarly, a couple is in the “physically non-violent” subgroup if the female partner reported at baseline that none of the instances of physical violence had occurred in the last 12 months. The same methodology is followed to form the subgroups of couples for sexual violence. The sexually and physically violent subgroups at baseline are not mutually exclusive.Second, to explore distinct patterns of IPV experience, a Latent Class Analysis (LCA) was conducted to identify latent subgroups (i.e., latent classes) of couples exposed to physical and sexual violence at baseline. LCA is a method for identifying and understanding unobserved groups in a population [Physical and sexual IPV experience as reported by female partners are measured with 7 physical violence items and 3 sexual violence items (Having defined these subgroups of couples based on the female partner’s experience of IPV at baseline, we conduct an intention-to-treat analysis of the impacts of EMAP separately for each subgroup of couples identified through both methods using ordinary least squares (OLS) and linear probability (for binary outcomes) models. Our findings are robust to using logistic models. Results are available upon request. We estimate adjusted models in which we control for the following baseline characteristics: men and women’s age and education, household size, and the language of the interview. For all analyses, standard errors are clustered at the site level in the regressions.