Univariate and multivariate methods to analyze randomized response (RR) survey designs (e.g., Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69). Besides univariate estimates of true proportions, RR variables can be used for correlations, as dependent variable in a logistic regression (with or without random effects), as predictors in a linear regression, or as dependent variable in a beta-binomial ANOVA. For simulation and bootstrap purposes, RR data can be generated according to several models.
|Author||Daniel W. Heck [aut, cre], Morten Moshagen [aut]|
|Date of publication||2016-01-12 14:18:56|
|Maintainer||Daniel W. Heck <email@example.com>|
getPW: Get Misclassification Matrices for RR Models
minarets: Minaret Data
plot.powerplot: Plot power of multivariate RR methods
plot.RRlog: Plot Logistic RR Regression
powerplot: Power plots for multivariate RR methods
predict.RRlog: Predict Individual Prevalences of the RR Attribute
RRcor: Bivariate correlations including randomized response...
RRgen: Generate randomized response data
RRlin: Linear randomized response regression
RRlog: Logistic randomized response regression
RRmixed: Mixed Effects Logistic Regression for RR Data
RRreg-package: Correlation and Regression Analyses for Randomized Response...
RRsimu: Monte Carlo simulation for one or two RR variables
RRuni: Univariate analysis of randomized response data