Some alternative strategies to Moors’ model in randomized response sampling
By Sarjinder Singh, R. Singh, N. Mangat. 2000
54 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/ce7a7cd14331bd2e3d82d3e85847d127cbcb56fb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Jong‐Min Kim
- William D. Warde
- K. Huang
- Housila P. Singh
- Sarjinder Singh
- Christopher R. Gjestvang
- Tanveer A. Tarray
- Matthew E. Elam
Citations in the corpus
- Unbiased estimators of mean, variance and sensitivity level for quantitative characteristics in finite population sampling (2010, background): “In recent years, many improvements and enhancements have significantly increased the value and acceptance of the RR approaches, see Bhargava and Singh (2000); Chua and Tsui (2000); Padmawar and Vijayan (2000); Singh et al. (2000, 2001) ; Chaudhuri (2001); Bar-Lev et al. (2004); Chaudhuri (2004) and”
- A mixed randomized response model (2005, methodology): “Singh et al. (2000)also proposed two different models as alternatives for the Moors model, but the proposed models used simple random sampling without replacement which led to a high-cost survey compared with the Moors model using simple random sampling with replacement.”