Estimation of parameters of logistic regression for two-stage randomized response technique

Pei-Chieh Chang, Kim-Hung Pho, Shen-Ming Lee and Chin-Shang Li ()
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Pei-Chieh Chang: Feng Chia University
Kim-Hung Pho: Feng Chia University
Shen-Ming Lee: Feng Chia University
Chin-Shang Li: University at Buffalo

Computational Statistics, 2021, vol. 36, issue 3, No 26, 2133 pages

Abstract: Abstract When a survey study is related to sensitive issues such as political orientation, sexual orientation, and income, respondents may not be willing to reply truthfully, which leads to bias results. To protect the respondents’ privacy and improve their willingness to provide true answers, Warner (J Am Stat Assoc 60:63–69, 1965) proposed the randomized response (RR) technique in which respondents select a question by means of a random device in order to ensure that they maintain privacy. Huang (Stat Neerl 58:75–82, 2004) extended the RR design of Warner (1965) to propose a two-stage RR design. Not only can this method be used to estimate the population proportion of persons with a sensitive characteristic, but also estimate the honest answer rate in the first stage. This work develops a covariate extension of the two-stage RR design of Huang (2004) by applying logistic regression to investigate the effects of covariates on a sensitive characteristic and an honest response. Simulation experiments are conducted to study the finite-sample performance of the maximum likelihood estimators of the logistic regression parameters. The proposed methodology is applied to analyze the survey data of sexuality of freshmen at Feng Chia University in Taiwan in 2016.

Keywords: Honest response; Logistic regression; Maximum likelihood estimation; Sensitive characteristic (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s00180-021-01068-5

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