Cross-sectional and Panel Data Analyses of an Incompletely Observed Variable Derived From the Nonrandomized Method for Surveying Sensitive Questions

Abstract

This article describes (1) the survey methodological and statistical characteristics of the nonrandomized method for surveying sensitive questions for both cross-sectional and panel survey data and (2) the way to use the incompletely observed variable obtained from this survey method in logistic regression and in loglinear and log-multiplicative association models. The nonrandomized method, which was introduced by Yu, Tian, and Tang and Tian et al. for surveying sensitive questions, is much more efficient than randomized response methods, and unlike the latter, the former can be included in a mail survey. The method also has unique advantages compared with the randomized response method for the analysis of panel survey data. A simulation analysis presents how the relative efficiency of statistics in the analysis of data collected with this method changes as a function of mixing probability compared with a hypothetical situation of collecting responses of a sensitive question from every sample subject. The use of statistical software for the application of the logistic regression model, with an incompletely observed variable from cross-sectional and panel surveys, is also described.