locate missingness in fitted model in R

Question

Consider fitting a coxph model with, say, 100 data points. Only 95 are included in the analysis, while 5 are excluded due to being NA (i.e. missingness). I extract the residuals on the fitted data so I have a residual vector with 95 observations. I would like to include the residuals back into the original data frame, but I can't do this since the lengths are different.

How do I identify which observations from the original data frame were not included in the model, so I can exclude/delete them to make the two lengths the same?

(The original data is much larger so it's hard to locate where data are missing...)

Answer 1

Re-fit your model, setting the na.action argument to na.exclude. This pads the residuals and fitted values that are part of the fitted object with NAs. If your original model is zn50:

zn50_na <- update(zn50, na.action=na.exclude)

This should give you residuals(zn50_na) and fitted(zn50_na) of the appropriate length. See ?na.omit for more info.