Novel imputation methods under stratified simple random sampling

被引：3

作者：

Kumar, Anoop ^{[1
]}

Bhushan, Shashi ^{[2
]}

Mustafa, Manahil SidAhmed ^{[3
]}

Aldallal, Ramy ^{[4
]}

Aljohani, Hassan M. ^{[5
]}

Almulhim, Fatimah A. ^{[6
]}

机构：

[1] Cent Univ Haryana, Dept Stat, Mahendergarh 123031, India

[2] Univ Lucknow, Dept Stat, Lucknow 226007, UP, India

[3] Univ Tabuk, Fac Sci, Dept Stat, Tabuk, Saudi Arabia

[4] Prince Sattam Bin Abdulaziz Univ, Coll Business Adm Hawtat Bani Tamim, Dept Management, Al Hulwah, Saudi Arabia

[5] Taif Univ, Coll Sci, Dept Math & Stat, POB 11099, Taif 21944, Saudi Arabia

[6] Princess Nourah Bint Abdulrahman Univ, Coll Sci, Dept Math Sci, POB 84428, Riyadh 11671, Saudi Arabia

来源：

ALEXANDRIA ENGINEERING JOURNAL | 2024年 / 95卷

关键词：

Missing values; Imputation; Stratified simple random sampling; ESTIMATORS; RATIO;

D O I：

10.1016/j.aej.2024.03.088

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called 'novel'. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

引用

页码：236 / 246

页数：11

共 50 条

[1] Optimal Imputation Methods under Stratified Ranked Set Sampling
Bhushan, Shashi
Kumar, Anoop
REVSTAT-STATISTICAL JOURNAL, 2025, 23 (01) : 53 - 77
[2] Empirical likelihood confidence intervals under imputation for missing survey data from stratified simple random sampling
Cai, Song
Qin, Yongsong
Rao, J. N. K.
Winiszewska, Malgorzata
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2019, 47 (02): : 281 - 301
[3] Improved ratio estimator under simple and stratified random sampling
Saini M.
Jitendrakumar B.R.
Kumar A.
Life Cycle Reliability and Safety Engineering, 2024, 13 (2) : 181 - 187
[4] Some Compromised Exponential Ratio Type Imputation Methods in Simple Random Sampling
Shakti Prasad
Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 2021, 91 : 337 - 349
[5] Some Compromised Exponential Ratio Type Imputation Methods in Simple Random Sampling
Prasad, Shakti
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES, 2021, 91 (02) : 337 - 349
[6] Novel Logarithmic Imputation Methods Under Ranked Set Sampling
Bhushan, Shashi
Kumar, Anoop
MEASUREMENT-INTERDISCIPLINARY RESEARCH AND PERSPECTIVES, 2024, 22 (03) : 235 - 257
[7] STRATIFIED SIMPLE RANDOM SAMPLING AND PRIOR DISTRIBUTIONS
REDDY, VN
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1976, 28 (03) : 445 - 459
[8] New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods
Sinsomboonthong, Juthaphorn
Sinsomboonthong, Saichon
PLOS ONE, 2025, 20 (03):
[9] Resolving the Raven Paradox: Simple Random Sampling, Stratified Random Sampling, and Inference to Best Explanation
Ward, Barry
PHILOSOPHY OF SCIENCE, 2022, 89 (02) : 360 - 377
[10] RANDOM VS STRATIFIED SAMPLING METHODS FOR TOMATO INSPECTION
FILIPELLO, F
WHIPPLE, SR
FOOD TECHNOLOGY, 1957, 11 (08) : 434 - 436

← 1 2 3 4 5 →