mice.impute.logreg2 {mice} | R Documentation |
Imputes univariate missing data using logistic regression.
imp <- mice.impute.logreg2(y, ry, x)
y |
Incomplete data vector of length n |
ry |
Vector of missing data pattern of length n (FALSE=missing, TRUE=observed) |
x |
Matrix (n x p) of complete covariates. |
Imputation for binary response variables by the Bayesian logistic regression model. See Rubin (1987, p. 169-170) for a description of the method. The method consists of the following steps:
This method uses direct minimization of the likelihood function by means of V&R function logitreg (V&R, 2nd ed, p. 293).
imp |
A vector of length nmis with imputations (0 or 1). |
An alternative is mice.impute.logreg.
Stef van Buuren, Karin Oudshoorn, 2000
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.
Venables, W.N. & Ripley, B.D. (1997). Modern applied statistics with S-Plus (2nd ed). Springer, Berlin.
mice
, logitreg
, mice.impute.logreg