mice.impute.polyreg {mice} | R Documentation |
Imputes missing data in a categorical variable using polytomous regression
mice.impute.polyreg(y, ry, x)
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. |
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:
This algorithm uses the function multinom()
from the libraries nnet
(Venables and Ripley).
A vector of length nmis with imputations.
Stef van Buuren, Karin Groohuis-Oudshoorn, 2000
Van Buuren, S., Groothuis-Oudshoorn, C.G.M. (2000) Multivariate Imputation by Chained Equations: MICE V1.0 User's manual. Leiden: TNO Quality of Life. http://www.stefvanbuuren.nl/publications/MICE V1.0 Manual TNO00038 2000.pdf
Brand, J.P.L. (1999) Development, implementation and evaluation of multiple imputation strategies for the statistical analysis of incomplete data sets. Dissertation. Rotterdam: Erasmus University.
Venables, W.N. & Ripley, B.D. (1997). Modern applied statistics with S-Plus (2nd ed). Springer, Berlin.