Comparative Study of Confidence Intervals for Proportions in Complex Sample Surveys.

ABSTRACT: The most widespread method of computing confidence intervals (CIs) in complex surveys is to add and subtract the margin of error (MOE) from the point estimate, where the MOE is the estimated standard error multiplied by the suitable Gaussian quantile. This Wald-type interval is used by the American Community Survey (ACS), the largest US household sample survey. For inferences on small proportions with moderate sample sizes, this method often results in marked under-coverage and lower CI endpoint less than 0. We assess via simulation the coverage and width, in complex sample surveys, of seven alternatives to the Wald interval for a binomial proportion with sample size replaced by the 'effective sample size,' that is, the sample size divided by the design effect. Building on previous work by

SUBMITTER: Franco C 

PROVIDER: S-EPMC6690503 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature