Estimation from incomplete sampling frames in case of simple random sampling

Issue title: Statistical Inference with Missing Data

Guest editors: Ma del Mar Rueda

Article type: Research Article

Authors: Agarwal, Bhawna^{a; *} | Gupta, P.C.^b

Affiliations: [a] Institute for integrated learning in management, 3 Lodhi Institutional Area, New Delhi 110003, India | [b] Veer Narmad South Gujarat University, U.M. Road, Surat 395007, Gujarat, India

Correspondence: [*] Corresponding author: Institute for integrated learning in management, 3, Lodhi Institutional Area, New Delhi – 110003, India. Tel.: 09990053051/91 11 65105541; E-mail: bhawna.agrawal@iilm.edu.

Abstract: In large scale surveys, sampling frames are mostly incomplete. Hence, in the present paper, methods of estimation of total population, mean, variance have been developed and the formulae for estimators from incomplete frames in case of SRSWOR and SRSWR are derived. The theory has been substantiated through a numerical problem. This example clearly reveals that estimates are much improved.

Keywords: Simple random sampling, estimation, incomplete frame

DOI: 10.3233/MAS-2008-3204

Journal: Model Assisted Statistics and Applications, vol. 3, no. 2, pp. 113-117, 2008