Imputes missing data in a categorical variable using polytomous regression
Usage
impute.polyreg(y, ry, x)
Arguments
y
Incomplete data vector of length n
ry
Vector of missing data pattern (FALSE=missing, TRUE=observed)
x
Matrix (n x p) of complete covariates.
Value
A vector of length nmis with imputations.
Details
Imputation for categorical response variables by the Bayesian
polytomous regression model. See J.P.L. Brand (1999), Chapter 4,
Appendix B.
The method consists of the following steps:
enumerate
\itemFit categorical response as a multinomial model
\itemCompute predicted categories
\itemAdd appropriate noise to predictions.
enumerate
This algorithm uses the function multinom from the libraries nnet and MASS
(Venables and Ripley).
References
Van Buuren, S. & Oudshoorn, C.G.M. (2000). Multivariate Imputation by Chained Equations:
MICE V1.0 User's manual. Report PG/VGZ/00.038, TNO Prevention and Health, Leiden.
Brand, J.P.L. (1999). Development, Implementation and Evaluation of Multiple Imputation Strategies for the Statistical Analysis of Incomplete Data Sets. Ph.D. Thesis, TNO Prevention and Health/Erasmus University Rotterdam. ISBN 90-74479-08-1.