Ranked set sampling (RSS) is a technique for incorporating auxiliary (concomitant) information into estimation and testing procedures right at the design stage. In this paper, we propose group sequential testing procedures for comparing two treatments with binary outcomes under an RSS scheme...

The presence of variation in all manufacturing and measurement processes is a natural phenomenon and is the key factor which affects the performance of all types of processes. A better understanding of the causes of variability in any processes is necessary to improve the process. For an...

Balanced sampling is a very efficient sampling design when the variable of interest is correlated to the auxiliary variables on which the sample is balanced. A procedure to select balanced samples in a stratified population has previously been proposed. Unfortunately, this procedure becomes very...

New design-based ratio and difference estimators of the distribution function are defined by minimizing the mean square error of a class of estimators. Proposed estimators do not assume a superpopulation model between the variable of interest and the auxiliary variable. Results derived from...

Regression type estimators of a population proportion under a general sampling design and using auxiliary information are obtained. Confidence intervals based on various methods, involving auxiliary information, are also derived. An application of the proposed methods is illustrated by...

We consider how to incorporate auxiliary information to improve quantile regression via empirical likelihood. We propose a novel framework and show that our approach yields more efficient estimates compared to those from the conventional quantile regression. The efficiency gain is quantified...