USING MULTIPLE IMPUTATION AND INVERSE PROBABILITY WEIGHTING TO ADJUST FOR MISSING DATA IN HIV PREVALENCE ESTIMATES
USING MULTIPLE IMPUTATION AND INVERSE PROBABILITY WEIGHTING TO ADJUST FOR MISSING DATA IN HIV PREVALENCE ESTIMATES
Introduction 
 Population surveys and demographic studies are the gold standard for estimating HIV prevalence. However, non-response in these surveys is of major concern, especially if it is not random and complete case analysis becomes an inappropriate data analysis method. Therefore, a comprehensive analysis that will account for the missing …