On inference of multivariate means under ranked set sampling

Haresh Rochani, Daniel F. Linder, Hani Samawi, Viral Panchal

Research output: Contribution to journalArticle

Abstract

In many studies, a researcher attempts to describe a population where units are measured for multiple outcomes, or responses. In this paper, we present an efficient procedure based on ranked set sampling to estimate and perform hypothesis testing on a multivariate mean. The method is based on ranking on an auxiliary covariate, which is assumed to be correlated with the multivariate response, in order to improve the efficiency of the estimation. We showed that the proposed estimators developed under this sampling scheme are unbiased, have smaller variance in the multivariate sense, and are asymptotically Gaussian. We also demonstrated that the efficiency of multivariate regression estimator can be improved by using Ranked set sampling. A bootstrap routine is developed in the statistical software R to perform inference when the sample size is small. We use a simulation study to investigate the performance of the method under known conditions and apply the method to the biomarker data collected in China Health and Nutrition Survey (CHNS 2009) data.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalCommunications for Statistical Applications and Methods
Volume25
Issue number1
DOIs
StatePublished - Jan 1 2018

Fingerprint

Ranked Set Sampling
Sampling
Multiple Outcomes
Multivariate Response
Multiple Responses
Statistical Software
Multivariate Regression
Nutrition
Regression Estimator
Biomarkers
Hypothesis Testing
Bootstrap
Covariates
Ranking
China
Sample Size
Health
Simulation Study
Estimator
Unit

Keywords

  • Hypothesis testing
  • Multivariate mean
  • Ranked set sampling
  • Regression estimator

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Finance
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Cite this

On inference of multivariate means under ranked set sampling. / Rochani, Haresh; Linder, Daniel F.; Samawi, Hani; Panchal, Viral.

In: Communications for Statistical Applications and Methods, Vol. 25, No. 1, 01.01.2018, p. 1-13.

Research output: Contribution to journalArticle

Rochani, Haresh ; Linder, Daniel F. ; Samawi, Hani ; Panchal, Viral. / On inference of multivariate means under ranked set sampling. In: Communications for Statistical Applications and Methods. 2018 ; Vol. 25, No. 1. pp. 1-13.
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