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Article
Using Ranked Auxiliary Covariate as a More Efficient Sampling Design for ANCOVA Model: Analysis of a Psychological Intervention to Buttress Resilience
Communications for Statistical Applications and Methods
  • Rajai Jabrah, Georgia Southern University
  • Hani Samawi, Georgia Southern University
  • Robert Vogel, Georgia Southern University
  • Haresh Rochani, Georgia Southern University
  • Daniel Linder, Georgia Southern University
Document Type
Article
Publication Date
3-1-2017
DOI
10.5351/CSAM.2017.24.3.241
Abstract

Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis of covariance (ANCOVA) models. A comparison to simple random sampling (SRS) is made to demonstrate efficiency. The results indicate that the required sample sizes for a given precision are smaller under RSS than under SRS. The modified RSS protocol was applied to an experimental study. The experimental study was designed to obtain a better understanding of the pathways by which positive experiences (i.e., goal completion) contribute to higher levels of happiness, well-being, and life satisfaction. The use of the RSS method resulted in a cost reduction associated with smaller sample size without losing the precision of the analysis.

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Copyright Statement: Copyright © The Korean Statistical Society and Korean International Statistical Society. All Rights Reserved. Article retrieved from Communications for Statistical Applications and Methods, an official journal of the Korean Statistical Society (KSS) and Korean International Statistical Society (KISS). It is an international and Open Access journal dedicated to publishing peer-reviewed, high quality and innovative statistical research.

Citation Information
Rajai Jabrah, Hani Samawi, Robert Vogel, Haresh Rochani, et al.. "Using Ranked Auxiliary Covariate as a More Efficient Sampling Design for ANCOVA Model: Analysis of a Psychological Intervention to Buttress Resilience" Communications for Statistical Applications and Methods Vol. 24 (2017) p. 241 - 254 ISSN: 2383-4757
Available at: http://works.bepress.com/hareshrochani/40/