Estimation of a Finite Population Proportion in Light of Randomized Reporting

DOI

10.2991/jsta.2018.17.4.2How to use a DOI?

Keywords

Sampling design; SRSWOR; Investigator intervention; Supervisor intervention; Study design; Probability model; Randomization distribution

Abstract

In large scale surveys, it is customary to accept unaltered the responses provided by the respondents, leaving no provision for investigators to pass on any circumstantial judgment on the responses. This restrictive practice sometimes vitiates the estimation of a parameter. Here we consider a real life scenario in which the data gathering process is compounded by possible interventions by investigators/supervisors who may provide thoughtful judgments on the quality/category of the response given by a respondent. In this modified scenario, we address the problem of estimating the unknown population proportion P. In the context of an illustrative example, we develop a possible randomization theory and computational formulas to estimate P under intervention effects.

Copyright

© 2018 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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TY  - JOUR
AU  - Pulakesh Maiti
AU  - Jyotirmoy Sarkar
AU  - Bikas K. Sinha
PY  - 2018
DA  - 2018/12/31
TI  - Estimation of a Finite Population Proportion in Light of Randomized Reporting
JO  - Journal of Statistical Theory and Applications
SP  - 597
EP  - 605
VL  - 17
IS  - 4
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2018.17.4.2
DO  - 10.2991/jsta.2018.17.4.2
ID  - Maiti2018
ER  -