Generalized Scrambling in Quantitative Optional Randomized Response Models

Autor:	Javid Shabbir, Samridhi Mehta, Sat Gupta, Bal Kishan Dass
Rok vydání:	2013
Předmět:	Statistics and Probability Discrete mathematics Estimation theory Generalization Multiplicative function Randomized response Linear combination Algorithm Scrambling Mathematics
Zdroj:	Communications in Statistics - Theory and Methods. 42:4034-4042
ISSN:	1532-415X 0361-0926
DOI:	10.1080/03610926.2011.638427
Popis:	Huang (2010) proposed an optional randomized response model using a linear combination scrambling which is a generalization of the multiplicative scrambling of Eichhorn and Hayre (1983) and the additive scrambling of Gupta et al. (2006, 2010). In this article, we discuss two main issues. (1) Can the Huang (2010) model be improved further by using a two-stage approach?; (2) Does the linear combination scrambling provide any benefit over the additive scrambling of Gupta et al. (2010)? We will note that the answer to the first question is “yes” but the answer to the second question is “no.”
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7ecf91a892d2e44944318f8506d95b74 https://doi.org/10.1080/03610926.2011.638427 Zobrazit plný text záznamu