Evidence map›Paper›PMID 37165153›Full record

ArticleBehavior research methods2024

The analysis of randomized response "ever" and "last year" questions: A non-saturated Multinomial model.

Khadiga H A Sayed, Maarten J L F Cruyff, Peter G M van der Heijden

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Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Khadiga H A SayedDepartment of Methodology and Statistics, Utrecht University, Utrecht, Netherlands. k.h.a.sayed@uu.nl.ORCID 0000-0002-4286-6350
Maarten J L F CruyffDepartment of Methodology and Statistics, Utrecht University, Utrecht, Netherlands.
Peter G M van der HeijdenDepartment of Methodology and Statistics, Utrecht University, Utrecht, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Randomized response (RR) is a well-known interview technique designed to eliminate evasive response bias that arises from asking sensitive questions. The most frequently asked questions in RR are either whether respondents were "ever" carriers of the sensitive characteristic, or whether they were carriers in a recent period, for instance, "last year". The present paper proposes a design in which both questions are asked, and derives a multinomial model for the joint analysis of these two questions. Compared to the separate analyses with the binomial model, the model makes a useful distinction between last year and former carriers of the sensitive characteristic, it is more efficient in estimating the prevalence of last year carriers, and it has a degree of freedom that allows for a goodness-of-fit test. Furthermore, it is easily extended to a multinomial logistic regression model to investigate the effects of covariates on the prevalence estimates. These benefits are illustrated in two studies on the use of anabolic androgenic steroids in the Netherlands, one using Kuk and one using both the Kuk and forced response. A salient result of our analyses is that the multinomial model provided ample evidence of response biases in the forced response condition.

Indexed as

Models, StatisticalBiasHumansLogistic ModelsNetherlandsPrevalenceAnabolic steroidsEfficiencyForced responseGoodness-of-fitKuk modelMultinomial logisticRandomized responseResponse bias

Identifiers

PMID37165153
PMCPMC10991035

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.