Open AccessA Modified Forced Randomized Response Model
Author(s) -
Adefemi Adeniran,
A. A. Sodipo,
Christopher Godwin Udomboso
Publication year - 2020
Publication title -
journal of the nigerian society of physical sciences
Language(s) - English
Resource type - Journals
ISSN - 2714-4704
DOI - 10.46481/jnsps.2020.30
Subject(s) - randomized response , simple random sample , estimator , statistics , sampling (signal processing) , population mean , bayesian probability , variance (accounting) , random effects model , simple (philosophy) , computer science , sampling design , importance sampling , population , mathematics , medicine , monte carlo method , philosophy , meta analysis , environmental health , accounting , filter (signal processing) , epistemology , business , computer vision
In this paper, we proposed a new Randomized Response Model (RRM) that estimate proportion of people in a population (P) belonging to a sensitive group (S) under study. Simple random sampling with replacement and stratied simple random sampling scheme were adopted. Maximum likelihood and Bayesian estimation procedures of the proposed model were developed and compared. The sampling distribution (expectation and variance) of the proposed estimator under the two sampling techniques, eciency comparison of the proposed model with some existing models, and numerical illustration of all the compared models were also explored. We found that the proposed model outperformed other existing RRMs in terms of eciency and it proved to be more protective in designing survey for sensitive related issues.