The item count method for sensitive survey questions: modelling criminal behaviour

Jouni Kuha and Jonathan Jackson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: The item count method is a way of asking sensitive survey questions which protects the anonymity of the respondents by randomization before the interview. It can be used to estimate the probability of sensitive behaviour and to model how it depends on explanatory variables. We analyse item count survey data on the illegal behaviour of buying stolen goods. The analysis of an item count question is best formulated as an instance of modelling incomplete categorical data. We propose an efficient implementation of the estimation which also provides explicit variance estimates for the parameters. We then suggest pecifications for the model for the control items, which is an auxiliary but unavoidable part of the analysis of item count data. These considerations and the results of our analysis of criminal behaviour highlight the fact that careful design of the questions is crucial for the success of the item count method.

Keywords: categorical data analysis; EM algorithm; list experiment; missing information; Newton-Raphson algorithm; randomized response (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 2014-02-11
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Published in Journal of the Royal Statistical Society. Series C: Applied Statistics, 11, February, 2014, 63(2), pp. 321-341. ISSN: 0035-9254

Downloads: (external link)
http://eprints.lse.ac.uk/48069/ Open access version. (application/pdf)

Related works:
Journal Article: The item count method for sensitive survey questions: modelling criminal behaviour (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:48069

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().