Ranked set sampling with missing observations: The estimation of the population mean and the difference of means

The authors develop the estimation of the difference of means of a pair of variables X and Y when we deal with missing observations. A seminal paper in this line is due to Bouza and Prabhu-Ajgaonkar when the sample and the subsamples are selected using simple random sampling. In this this chapter, the authors consider the use of ranked set-sampling for estimating the difference when we deal with a stratified population. The sample error is deduced. Numerical comparisons with the classic stratified model are developed using simulated and real data.

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Stratified Ranked Set Sampling (SRSS) for Estimating the Population Mean With Ratio-Type Imputation of the Missing Values

10.4018/978-1-7998-7556-7.ch007 ◽

2022 ◽

pp. 141-170

Author(s):

Carmen Elena Viada- Gonzalez ◽

Sira María Allende-Alonso

Keyword(s):

Real World ◽

Missing Values ◽

Sample Selection ◽

Ranked Set Sampling ◽

Missing Observations ◽

Selection Procedures ◽

Population Mean ◽

Numerical Studies ◽

The Mean ◽

Stratified Ranked Set Sampling

In this chapter, the authors develop stratified ranked set sampling (RSS) under missing observations. Imputation based of ratio rules is used for completing the information for estimating the mean. They introduce the needed elements on imputation and on the sample selection procedures. They extend RSS models to imputation in stratified populations. A theory on ratio-based imputation rules for estimating the mean is presented. Some numerical studies, based on real-world problems, are developed for illustrating the behaviour of the accuracy of the estimators due to their proposals.

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Estimation of Population Mean by Using a Generalized Family of Estimators Under Classical Ranked Set Sampling

RMS: Research in Mathematics & Statistics ◽

10.1080/27658449.2021.1948184 ◽

2021 ◽

Vol 8 (1) ◽

pp. 1948184

Author(s):

Asad Ali ◽

Muhammad Moeen Butt ◽

Kanwal Iqbal ◽

Muhammad Hanif ◽

Muhammad Zubair

Keyword(s):

Ranked Set Sampling ◽

Population Mean

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On Two Novel Applications of Ranked Set Sampling

Calcutta Statistical Association Bulletin ◽

10.1177/0008068320030109 ◽

2003 ◽

Vol 54 (1-2) ◽

pp. 105-114

Author(s):

Sukuman Sarikavanij ◽

Montip Tiensuw

Keyword(s):

Case Studies ◽

Random Sample ◽

Ranked Set Sampling ◽

Simple Random Sample ◽

Single Family ◽

Ranked Set Sample ◽

Population Mean ◽

Sales Data ◽

Tree Data ◽

Novel Applications

In this paper we discuss two case studies which clearly indicate the advantages of using a ranked set sample (RSS) over those of a simple random sample (SRS). The applications of RSS considered here cover single family homes sales data, and tree data. It is demonstrated that in each case RSS is much more efficient than SRS for estimation of population mean.

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