glm code tweak #8
Description
Hello - Not one to rush into - I'll test over next couple of weeks, but as an update I've rewritten a few of the glm functions to be able to handle weights and potentially new families in models (so these are compatible with propensity score matching.
It produces the same glmlist model (albeit with a more accurate call per dependent variable).
I'll work on it a bit and see if it errors at all. Posted for the record!
Example:
glmmulti <- function(df.in, dependent, explanatory, weights = NULL, family = "binomial"){ result = list() if (is.null(weights)){ for (i in 1:length(dependent)) { f <- as.formula(paste(dependent, '~', paste(explanatory, collapse="+"))) fit <- do.call("glm", list(formula=f, data=df.in, family= family)) fit['call'] = deparse(f) result[[i]] <- fit} } else { for (i in 1:length(dependent)) { f <- as.formula(paste(dependent, '~', paste(explanatory, collapse="+"))) fit <- do.call("glm", list(formula=f, data=df.in, family= family, weights = weights)) fit['call'] = deparse(f) result[[i]] <- fit} } result = setNames(result, dependent) class(result) = "glmlist" return(result) }