Run glm.mids on a subset of imputed data from mice (R) -



Run glm.mids on a subset of imputed data from mice (R) -

i error when seek run glm.mids on subset of mids imputation object:

library(mice) imp2 = mice(nhanes) glm.mids( (hyp==2)~bmi+chl, data=imp2, subset=(age==1) )

gives cryptic error message

"error in eval(expr, envir, enclos) : ..1 used in wrong context, no ... in"

even though syntax works regular glm on original dataset:

glm( (hyp==2)~bmi+chl, data=nhanes, subset=(age==1) )

the documentation ?glm.mids doesn't address subset says can pass additional parameters onto glm. if can't utilize subset glm.mids, there way subset mids list object directly?

i have taken liberty of rewriting glm.mids. bit kludgy. issue seems stem implicit nature attributes passed glm.

also see these post:

https://stat.ethz.ch/pipermail/r-help/2003-november/041537.html

http://r.789695.n4.nabble.com/question-on-passing-the-subset-argument-to-an-lm-wrapper-td3009725.html

library(mice) glm.mids=function (formula, family = gaussian, data, ...) { phone call <- match.call() if (!is.mids(data)) stop("the info must have class mids") analyses <- as.list(1:data$m) (i in 1:data$m) { data.i <- complete(data, i) analyses[[i]] <- do.call("glm",list(formula=quote(formula),family=quote(family),data=quote(data.i),...)) } object <- list(call = call, call1 = data$call, nmis = data$nmis, analyses = analyses) oldclass(object) <- c("mira", "glm", "lm") return(object) } imp2 = mice(nhanes) glm.mids( (hyp==2)~bmi+chl, data=imp2 ,subset=quote(age==1))

the part rewrote glm function phone call within glm.mids analyses[[i]] <- do.call("glm",list(formula=quote(formula),family=quote(family),data=quote(data.i),...))

in old version read analyses[[i]] <- glm(formula, family = family, info = data.i,...)

r subset r-mice

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