Mathematics (Mar 2024)

Accounting for Measurement Error and Untruthfulness in Binary RRT Models

  • Bailey Meche,
  • Venu Poruri,
  • Sat Gupta,
  • Sadia Khalil

DOI
https://doi.org/10.3390/math12060875
Journal volume & issue
Vol. 12, no. 6
p. 875

Abstract

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This study examines the effect of measurement error on binary Randomized Response Technique models. We discuss a method for estimating and accounting for measurement error and untruthfulness in two basic models and one comprehensive model. Both theoretical and empirical results show that not accounting for measurement error leads to inaccurate estimates. We introduce estimators that account for the effect of measurement error. Furthermore, we introduce a new measure of model privacy using an odds ratio statistic, which offers better interpretability than traditional methods.

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