Hypothetical versus real life predictions for clusters based finite population total using count and binary survey data
Brajendra C. Sutradhar
Statistics & Probability Letters, 2025, vol. 226, issue C
Abstract:
This paper, as opposed to the existing generalized least square estimation based prediction, provides an optimal estimating function approach with valid prediction for clusters based finite population totals, where within cluster data are supposed to be correlated.
Keywords: Constant mean model; Correlated discrete responses within a cluster; Design cum model unbiased parameters estimation; Design cum model unbiased prediction; Sampling design weights; Two-stage cluster sample (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715225001397
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:226:y:2025:i:c:s0167715225001397
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spl.2025.110494
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().