Statistical analysis
REGRESSION
Follow-up analyses were based on the final household visit for each participant. If a participant had both a 6-month and long-term follow-up visit, the long-term follow-up visit was used. To compare changes in behavioral determinants from baseline to follow-up, descriptive statistics were calculated. Logistic regression with generalized estimating equations (GEE) with exchangeable working correlation was performed to account for clustering within households. Study timepoint was the outcome, with each behavioral determinant as the predictor. Logistic regression models with GEE with exchangeable working correlation were also used to examine the baseline behavioral determinants associated with the use of arsenic-safe water for drinking and cooking with household as the cluster, baseline behavioral determinant or demographic factor as the predictor, and follow-up water use as the outcome. To assess the influence of baseline behavioral determinants on arsenic filter cartridge change during the study period, GEE logistic regression models with independent working correlation (due to the smaller sample size) were run with behavioral determinants at baseline as the predictors and arsenic filter cartridge change as the outcome. Finally, logistic regression models with GEE with exchangeable working correlation were also used to assess the influence of the change in baseline determinants (follow-up – baseline) over the study period on use of arsenic-safe water with household as the cluster variable. All analyses were completed using SAS software (version 9.4, Cary, NC).