Literature DB >> 22924599

Asking sensitive questions: a statistical power analysis of randomized response models.

Rolf Ulrich1, Hannes Schröter, Heiko Striegel, Perikles Simon.   

Abstract

This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warner's model, crosswise model, unrelated question model, forced-choice models, item count model, cheater detection model). This power analysis can help in choosing the optimal model and sample size and in setting model parameters in survey studies. The general framework can be applied to all existing randomized response model versions. The Appendix of this article contains worked-out numerical examples to demonstrate the power analysis for each specific model. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Mesh:

Year:  2012        PMID: 22924599     DOI: 10.1037/a0029314

Source DB:  PubMed          Journal:  Psychol Methods        ISSN: 1082-989X


  16 in total

1.  Detecting nonadherence without loss in efficiency: A simple extension of the crosswise model.

Authors:  Daniel W Heck; Adrian Hoffmann; Morten Moshagen
Journal:  Behav Res Methods       Date:  2018-10

2.  Doping in Two Elite Athletics Competitions Assessed by Randomized-Response Surveys.

Authors:  Rolf Ulrich; Harrison G Pope; Léa Cléret; Andrea Petróczi; Tamás Nepusz; Jay Schaffer; Gen Kanayama; R Dawn Comstock; Perikles Simon
Journal:  Sports Med       Date:  2018-01       Impact factor: 11.136

3.  Doping Prevalence in Competitive Sport: Evidence Synthesis with "Best Practice" Recommendations and Reporting Guidelines from the WADA Working Group on Doping Prevalence.

Authors:  John Gleaves; Andrea Petróczi; Dirk Folkerts; Olivier de Hon; Emmanuel Macedo; Martial Saugy; Maarten Cruyff
Journal:  Sports Med       Date:  2021-04-26       Impact factor: 11.136

4.  Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models.

Authors:  Shi-Fang Qiu; Man-Lai Tang; Ji-Ran Tao; Ricky S Wong
Journal:  Psychometrika       Date:  2022-03-20       Impact factor: 2.500

5.  A Comparison of the Cheater Detection and the Unrelated Question Models: A Randomized Response Survey on Physical and Cognitive Doping in Recreational Triathletes.

Authors:  Hannes Schröter; Beatrix Studzinski; Pavel Dietz; Rolf Ulrich; Heiko Striegel; Perikles Simon
Journal:  PLoS One       Date:  2016-05-24       Impact factor: 3.240

6.  The multidimensional randomized response design: Estimating different aspects of the same sensitive behavior.

Authors:  Maarten J L F Cruyff; Ulf Böckenholt; Peter G M van der Heijden
Journal:  Behav Res Methods       Date:  2016-03

7.  General Belief in a Just World Is Positively Associated with Dishonest Behavior.

Authors:  Kristin Wenzel; Simon Schindler; Marc-André Reinhard
Journal:  Front Psychol       Date:  2017-10-10

8.  Functionality of the Crosswise Model for Assessing Sensitive or Transgressive Behavior: A Systematic Review and Meta-Analysis.

Authors:  Dominic Sagoe; Maarten Cruyff; Owen Spendiff; Razieh Chegeni; Olivier de Hon; Martial Saugy; Peter G M van der Heijden; Andrea Petróczi
Journal:  Front Psychol       Date:  2021-06-23

9.  Use of illicit and prescription drugs for cognitive or mood enhancement among surgeons.

Authors:  Andreas G Franke; Christiana Bagusat; Pavel Dietz; Isabell Hoffmann; Perikles Simon; Rolf Ulrich; Klaus Lieb
Journal:  BMC Med       Date:  2013-04-09       Impact factor: 8.775

10.  Associations between physical and cognitive doping--a cross-sectional study in 2.997 triathletes.

Authors:  Pavel Dietz; Rolf Ulrich; Robert Dalaker; Heiko Striegel; Andreas G Franke; Klaus Lieb; Perikles Simon
Journal:  PLoS One       Date:  2013-11-13       Impact factor: 3.240

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