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Simulation analysis of non-respondent information in context of small domain.
Ashutosh, Ashutosh; Stefan, Marius; Rai, Piyush Kant; Emam, Walid; Iftikhar, Soofia; Anas, Malik Muhammad.
Afiliação
  • Ashutosh A; Department of Statistics, Allahabad Degree College, University of Allahabad, Prayagraj, 211003, India.
  • Stefan M; Department of Applied Mathematics, Faculty of Applied Sciences, Polytechnic University of Bucharest, Splaiul Independentei, nr. 313, RO-060042, USA.
  • Rai PK; Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.
  • Emam W; Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia.
  • Iftikhar S; Department of Statistics, Shaheed Benazir Bhutto Women University Peshawar, KP, Pakistan.
  • Anas MM; Department of Economics and Statistics, University of Salerno, Fisciano, Salerno, 84084, Italy.
Heliyon ; 10(6): e26897, 2024 Mar 30.
Article em En | MEDLINE | ID: mdl-38533019
ABSTRACT
In the real-world, there are various situations when all units are not accessible of the respondent called unit non-response. The effect of unit non-response is a tricky matter for estimating the total number of unit. The present work highlights the interest about subpopulations (domains) in two affairs i. if domains total of the supportive information is accessible ii. if domains total of the supportive variable does not access. The government needs to be introducing the actual facilities in these small domains. The supportive information is used to find out the estimate of the non respondent information and to apply this information for desired domains. Sometimes, it has been found that the accessible auxiliary variable for the domains might be positive shape. Therefore, it develops an appropriate model that has positive skewness. The present context highlighted the indirect method using a power-based estimation with calibration approach. By combining power based estimation and calibration technique, it is possible to obtain more accurate estimates for intended small domains. Even the supportive information is positively biased. This approach helps us in mitigating the effect of non-respondent and improving the overall reliability of the estimators. The simulation was conducted for different sizes 70 and 90 when nonresponse variable in the study variable. The results show that investigated power-based estimate provides better option over relevant exponential, ratio, and generalized regression estimators for intended domains.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article