mice.impute.logreg {mice} | R Documentation |
Imputes univariate missing data using logistic regression.
mice.impute.logreg(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:
The method relies on the standard glm.fit function.
imp |
A vector of length nmis with imputations (0 or 1). |
An alternative is mice.impute.logreg2.
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.
mice
, glm
, glm.fit
,
mice.impute.logreg2