Then data will be exported to SPSS window version (23.0) for further analysis. Data cleaning will be performed computing frequency using box plot to explore outliers and other data anomalies. Multiple imputation will be done to handle missing data. Different statistical assumptions will be checked for data distribution and suitability for statistical analysis. Descriptive statistics will be computed to determine prevalence (proportion), mean, median, and standard deviation of some independent variables as necessary. Cross tabulation (chi-square) will be employed. Binary logistic regression will be carried out to confirm the association of explanatory variable with DVAW. Explanatory variable which will have score of p-value less than 0.25 in binary logistic regression will be included into the multiple logistic regression analysis to determine the independent determinants of domestic violence by controlling the confounding variable. In addition, Intention to Treat Analysis (ITTA) will be carried out to compute the overall changes on the level of DVAW. Moreover, Difference in Difference (DID) will be calculated to determine the net intervention effect. The DID will be computed as subtracting intervention arm outcomes from baseline data to endline minus difference of control arm outcomes from baseline to endline. Finally, statistical significance of intervention effect will be measured using adjusted prevalence ratio, adjusted odd ratio/adjusted risk ratio at 95% CI and p value less than 0.05.