Statistical methods
infection
REGRESSION, INFECTION, SECONDARY, WORMS
Descriptive statistics were calculated as frequencies and proportions for categorical variables; arithmetic means ± standard deviation (SD) and geometric means with 95% CIs were calculated for continuous variables. Comparisons between treatment groups for demographic, infection, and adverse-event variables were performed using chi-square and Fisher’s exact tests (as appropriate) for categorical variables; analysis of variance (ANOVA) was used for continuous variables, and data were log transformed as needed to meet model assumptions. Analysis of the primary (% fertile female worms) and secondary (% living female worms) efficacy outcomes was conducted using a mixed-effects logistic regression model where study participant was included as a random effect to adjust for multiple worms per person. The covariates age, sex, and Mf density at baseline were also evaluated for inclusion in these models, and they were retained if they were significant (P < 0.05). All analyses were conducted in SAS for Windows version 9.4 (SAS Institute), and P < 0.05 was used to determine statistical significance.