Meaning of weights in output of glm (logistic regression) - vector of weights I asked the question previously as a guest, and stackexchange won't let me edit or respond now that I confirmed my account:
Understanding output of R glm (logistic regression) prediction - vector of weights
I got a response there referring to the "working" weights, but those are not what I am talking about (unless I am even more confused than I previously thought).  Rather, I am referring to this line in the documentation:
"'weights' extracts a vector of weights, one for each case in the fit (after subsetting and na.action)."
I am curious, how are these weights calculated?  How are they related to the probability assigned to each sample?  To be very clear, for every sample in the data set used in the fit, I get "weight" and "fitted.value" and I am trying to understand what the former means and how to calculate it.

You may be even more confused than you previously thought.
The weights function, extracts one of two types of weights, specified by the type argument.  With type="prior" (the default) it extracts the numbers that you supplied as the weights= argument to glm.  With type="working" it extracts the working weights.
