Inference with Survey Data Having Nonignorable Nonresponse

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

Item nonresponse exists in most surveys and nonresponse rates are often appreciable. Nonresponse is ignorable if it is related to the observed data only; otherwise, it is nonignorable. Research for nonignorable nonresponse is far from complete. This investigator focuses on statistical estimation and inference in cross-sectional or longitudinal surveys with nonignorable nonresponse. Methods for deriving approximately unbiased and consistent survey estimators for parameters such as population totals and quantiles will be developed. In addition, the efficiency and robustness of estimators will also be studied. Effort will be made to study multivariate or longitudinal survey data, and problems with nonresponse in not only the main survey variables but also the covariates. This investigator will also study variance estimation for valid estimators, using methods such as linearization, substitution, replication or resampling such as the jackknife, the balanced half samples, the random groups, and the bootstrap. Many statistical and government agencies collect data through surveys. In most of these surveys, there are typically people who do not respond to the survey, or give partial answers; such cases are called nonresponses. Often a nonresponse is related to the nonrespondent; for example, males under the age of twenty-five years may be more likely not to respond than older males. In this case, the statistical methodology is not well developed. The investigator plans to study methods for estimation and inference in the presence of nonresponse for various types of surveys. To increase the precision of estimators, effort will be made to use all observed data, to utilize auxilliary information, and to statistically model the nonresponse rate and/or distribution of the survey data. Methods of assessing the varibility of the derived estimators will also be studied. Since most of the proposed research topics are motivated by problems in survey agencies such as the Census Bureau, the Bureau of Labor Statistics, Westat, and Statistics Canada, results obtained from the proposed research will have significant impacts on the methodology for handling noresponse in these survey agencies.