Estimating the prevalence of socially sensitive behaviors: Attributing guilty and innocent noncompliance with the single sample count method

T. Nepusz, Andrea Petróczi, Declan P. Naughton, Tracy Epton, Paul Norman

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Prevalence estimation models, using randomized or fuzzy responses, provide protection against exposure to respondents beyond anonymity and represent a useful research tool in socially sensitive situations. However, both guilty and innocent noncompliance can have a profound impact on prevalence estimations derived from these models. In this article, we introduce the maximumlikelihood extension of the single sample count (SSC-MLE) estimation model to detect and attribute noncompliance through testing 5 competing hypotheses on possible ways of noncompliance. We demonstrate the ability of the SSC-MLE to estimate and attribute noncompliance with a single sample using the observed distribution of affirmative answers on recent recreational drug use from a sample of university students (N = 1,441). Based on the survey answers, the drug use prevalence was estimated at 17.62% (± 6.75%), which is in line with relevant drug use statistics. Only 2.51% (± 1.54%) were noncompliant, of which 0.55% (± 0.44%) was attributed to guilty noncompliance (i.e., have used drugs but did not admit) and 2.17% (± 1.44%) to innocent noncompliers with no drug use in the past 3 months to hide. The SSC-MLE indirect estimation method represents an important tool for estimating the prevalence of a broad range of socially sensitive behaviors. Subsequent applications of the SSC-MLE to a range of transgressive behaviors with varying sensitivity will contribute to establishing the SSC-MLE's performance properties, along with obtaining empirical evidence to test the underlying assumption of independence of noncompliance from involvement. Freely downloadable, user-friendly software to facilitate applications of the SSC-MLE model is provided.

Original languageEnglish
Pages (from-to)334-355
Number of pages22
JournalPsychological Methods
Volume19
Issue number3
DOIs
Publication statusPublished - 2014

Fingerprint

Pharmaceutical Preparations
Street Drugs
Software
Students
Drugs
Research
Surveys and Questionnaires
Fuzzy
Statistics
Anonymity
Empirical Evidence
Testing
Maximum Likelihood

Keywords

  • Birthday distribution
  • Cheating detection
  • Illicit drug
  • Prevalence estimation
  • Randomized response

ASJC Scopus subject areas

  • Psychology (miscellaneous)
  • History and Philosophy of Science
  • Medicine(all)

Cite this

Estimating the prevalence of socially sensitive behaviors : Attributing guilty and innocent noncompliance with the single sample count method. / Nepusz, T.; Petróczi, Andrea; Naughton, Declan P.; Epton, Tracy; Norman, Paul.

In: Psychological Methods, Vol. 19, No. 3, 2014, p. 334-355.

Research output: Contribution to journalArticle

Nepusz, T. ; Petróczi, Andrea ; Naughton, Declan P. ; Epton, Tracy ; Norman, Paul. / Estimating the prevalence of socially sensitive behaviors : Attributing guilty and innocent noncompliance with the single sample count method. In: Psychological Methods. 2014 ; Vol. 19, No. 3. pp. 334-355.
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