Concomitant-based rank set sampling proportion estimates

2004 ◽  
Vol 23 (13) ◽  
pp. 2061-2070 ◽  
Author(s):  
Jeff T. Terpstra ◽  
Lindsey A. Liudahl
Keyword(s):  
Rank Set Sampling

Estimation of Ratio Using Rank Set Sampling

1996 ◽  
Vol 38 (6) ◽  
pp. 753-764 ◽  
Author(s):  
Hani M. Samawi ◽  
Hassen A. Muttlak
Keyword(s):  
Rank Set Sampling

scholarly journals Rank Set Sampling in Improving the Estimates of Simple Regression Model

2015 ◽  
Vol 11 (1) ◽  
pp. 41
Author(s):  
M Iqbal Jeelani ◽  
S.A. Mir ◽  
I. Khan ◽  
S. Maqbool ◽  
Nageena Nazir ◽  
...  
Keyword(s):  
Regression Model ◽  
Simple Regression Model ◽  
Rank Set Sampling ◽  
Simple Regression

scholarly journals Sensitive proportion in ranked set sampling

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256699
Author(s):  
Azhar Mehmood Abbasi ◽  
Muhammad Yousaf Shad
Keyword(s):  
Numerical Integration ◽  
Random Sampling ◽  
Unbiased Estimator ◽  
Real Data ◽  
Simple Random Sampling ◽  
Ranked Set Sampling ◽  
Ratio Method ◽  
Integration Technique ◽  
Sampling Cost ◽  
Rank Set Sampling

This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner SL (1965)) that based on simple random sampling (SRS) without increasing sampling cost. Additionally, a new estimator based on ratio method is introduced using CRSS protocol, preserving the respondent’s confidentiality through a randomizing device. The numerical results of these estimators are obtained by using numerical integration technique. An application to real data is also given to support the methods.

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