Analysis of Ordinal Populations from Judgment Post-Stratification

Abstract: In surveys requiring cost efficiency, such as medical research, measuring the variable of interest (e.g., disease status) is expensive and/or time-consuming; However, we often have access to easily attainable characteristics about sampling units. These characteristics are not typically employed in the data collection process. Judgment post-stratification (JPS) sampling enables us to supplement the random samples from the population of interest with these characteristics as ranking information. In this paper, we develop methods based on JPS samples for the estimation of categorical ordinal populations. We develop various estimators from JPS data even for a situation where JPS suffers from empty strata. We also propose JPS estimators using multiple ranking resources. Through extensive numerical studies, we evaluate the performance of the methods in the estimation of the population. Finally, the developed estimation methods are applied to bone mineral data to estimate the bone disorder status of women aged 50 and older.