TITLE:
Web-Based Software for Small Area Estimation under Unit Level Model
AUTHORS:
James Karangwa, Anshu Bharadwaj
KEYWORDS:
Small Area Estimation, R Studio, Unit Level Model
JOURNAL NAME:
Open Access Library Journal,
Vol.8 No.4,
April
15,
2021
ABSTRACT: The purpose of this paper is to produce reasonably accurate direct estimators, not only for the characteristics of whole Population but also for a variety of Subpopulations or domains. Many policymakers and researchers also want to obtain statistics for small domains. These small domains are also called small areas, because the sample size in the area or domain from the Survey is small. Due to small sample size, domain-specific direct estimators provide an acceptably large coefficient of variation. Therefore, it becomes necessary to employ indirect small area estimators that make use of the sample data from related areas or domains through linking models, and this increases the effective sample size in the small areas. Such estimators can provide significantly smaller coefficient of variation than direct estimators, provided the linking models are valid. In this paper, a web-based software for small area estimation Under unit level model has been developed But this doesn’t include the Unit level effects in the model. This software will help the researchers, academicians, data analysts, Students and other domain groups who have been working in area of the SAE.