I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many NAs.
When I fit an ordinal regression model with the function lrm from the Design library:
model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE)
it will by default delete missing values in the variables y, x1, x2.
Based on model.lrm, I want to apply the robust covariance estimator using a cluster variable:
model.robcov.lrm <- robcov(model.lrm, cluster=clust)
How can I remove observations in the cluster variable clust that contain NAs in y, x1, and x2?
Thanks, Christof
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