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Variation from Classical Data Generating Procedures by Repeated Drawing

In: Randomized Response Techniques

Author

Listed:
  • Arijit Chaudhuri

    (Indian Statistical Institute)

  • Sanghamitra Pal

    (West Bengal State University)

  • Dipika Patra

    (Seth Anandram Jaipuria College)

Abstract

Consider $${y}_{i}$$ takes value 1 if the $${i}^\text{th}(i=\text{1,2},\dots ,N)$$ individual in the population $$U$$ bears a sensitive characteristic $$A$$ and value 0 if individual $$i$$ bears $${A}^{C}$$ . The proportion of individuals $$\theta =\frac{1}{N}\sum_{i=1}^{N}{y}_{i}$$ in the population bearing $$A$$ is estimated by employing randomized response (RR) devices pioneered by (Warner, Journal of American Statistical Association 60:63–69, 1965) followed by several other devices existing in literature. These devices usually mandate a sampled respondent to select card(s) randomly from a box answer a ‘match’ or ‘mismatch’ according to the characteristic ( $$A$$ or $${A}^{C}$$ ) marked in the selected card(s).

Suggested Citation

  • Arijit Chaudhuri & Sanghamitra Pal & Dipika Patra, 2024. "Variation from Classical Data Generating Procedures by Repeated Drawing," Springer Books, in: Randomized Response Techniques, chapter 0, pages 139-148, Springer.
    • Handle: RePEc:spr:sprchp:978-981-99-9669-8_8
    DOI: 10.1007/978-981-99-9669-8_8
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