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The randomized response log linear model as a composite link model

Record type: Article

In randomized response (RR) designs, misclassification is used to protect the privacy of respondents when sensitive questions are asked. A generalized linear model with a composite link function is presented to formulate log linear models that take the RR design into account. The approach is extended to model the situation where some respondents do not follow the instructions of the RR design. For example, if there are three binary RR variables with regard to practicing fraud, the 2 × 2 × 2 cross-classification of the true answers is latent due to the misclassification. Using composite link functions, log linear models can be specified for the latent table to investigate possible association between the variables. Fast iteratively re-weighted least squares algorithms are presented.

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Citation

van den Hout, Ardo, Gilchrist, Robert and van der Heijden, Peter G.M. (2010) The randomized response log linear model as a composite link model Statistical Modelling, 10, (1), pp. 57-67. (doi:10.1177/1471082X0801000104).

More information

Published date: April 2010
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 344664
URI: http://eprints.soton.ac.uk/id/eprint/344664
ISSN: 1471-082X
PURE UUID: 8d3e6553-9cd9-4c10-b7cb-30d5e3ca62d9

Catalogue record

Date deposited: 26 Oct 2012 11:24
Last modified: 18 Jul 2017 05:15

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Contributors

Author: Ardo van den Hout
Author: Robert Gilchrist

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