EM by the Method of Weights for Incomplete Data in GLMs
An R package published on CRAN that provides an estimator for generalized linear models with incomplete data for discrete covariates. The estimation is based on the EM algorithm by the method of weights by Ibrahim (1990). The package includes two example data sets which are provided in this paper. First, a data set from Stukel and Dain (1989) involves a study of 82 patients who experienced translaryngeal intubation (TLI) and were evaluated for laryngeal complications. A seoncd data set from Feigl and Zelen (1965) involves survival times of 33 leukemia patients which were classified according to the presence or absence of a morphologic characteristic of white cells.
See here for further information.
You can install the released version of icdGLM from CRAN with:
install.packages("icdGLM")data(TLI.data)
complete.data <- expand_data(data = TLI.data[, 1:3],
y = TLI.data[, 4],
missing.x = 1:3,
value.set = 0:1)
example <- icdglm(y ~ x1 + x2 + x3, family = binomial(link = "logit"),
data = complete.data$data, weights = complete.data$weights,
indicator = complete.data$indicator)
summary(example)Ibrahim, Joseph G. (1990). Incomplete Data in Generalized Linear Models. Journal of the American Statistical Association, Vol.85, No. 411, pp. 765 - 769.
This R package is licensed under the GNU General Public License (>= v2.0).