Randomized Response Techniques for Complex Surveys
BarLev model
Chaudhuri-Christofides model
Christofides model
Devore model
Diana-Perri-1 model
Diana-Perri-2 model
Eichhorn-Hayre model
Eriksson model
Forced-Response model
Horvitz model
Horvitz-UB model
Kuk model
Mangat model
Mangat-Singh model
Mangat-Singh-Singh model
Mangat-Singh-Singh-UB model
Mangat-UB model
Resampling variance of randomized response models
Internal RRTCS Functions
Randomized Response Techniques for Complex Surveys
Saha model
Singh-Joarder model
SoberanisCruz model
Warner model
Point and interval estimation of linear parameters with data obtained from complex surveys (including stratified and clustered samples) when randomization techniques are used. The randomized response technique was developed to obtain estimates that are more valid when studying sensitive topics. Estimators and variances for 14 randomized response methods for qualitative variables and 7 randomized response methods for quantitative variables are also implemented. In addition, some data sets from surveys with these randomization methods are included in the package.