Epi info version 3.5

Following the data collection, data were checked, coded and entered using EPI-INFO version 3.5 and exported to SPSS version 20 for analysis. Both descriptive and analytical statistical procedures were utilized. Descriptive statistics like percentage, mean and standard deviation were used for presentation of data and prevalence of smear positive PTB and MDR-TB. All variables of the study were initially tested for association with smear positive PTB by using binary logistic regression model. Those variables which have a p-value less than 0.2 by univariate analysis were put in the multivariable analysis model to control the possible effect of confounders. Finally the variable which has independent association with smear positive PTB was identified on the basis of odd ratio (OR) with 95 % confidence interval (CI) and P value less than 0.05. The variable was entered into multivariate model using the forward stepwise (likelihood ratio) regression method. Model fitness was checked using Hosmer and Lemeshow goodness of a fit test (0.70).

The data was cleaned manually, coded and entered into Epi info version 3.5 and exported to SPSS version 20 software for further analysis. After coding, and entering the data to the software descriptive statistics were used to calculate the result in proportion, frequencies, cross tabulation, and measure of central tendency. Tables and graphs were used to present the result. A bivariate binary logistic regression was used to identify candidate variables for the final model (multivariate binary logistic regressions) at p - value < 0.20. Finally the independent predictors or variables which had significant association were identified by using multivariate binary logistic regressions. The cut point to declare the presence of an association between the dependent and independent variable was p – value < 0.05 or AOR, 95% CI.