r - run multiple model after grouping and save as columns in dataframe -


i'm trying run multiple mix effect models on grouped data. here codes:

library(dplyr) library(lme4)  dat.tx.a <- mvrnorm(n=250, mu=c(30, 20, 28),                      sigma=matrix(c(25.0, 17.5, 12.3,                                     17.5, 25.0, 17.5,                                     12.3, 17.5, 25.0), nrow=3, byrow=true)) dat.tx.b <- mvrnorm(n=250, mu=c(30, 20, 22),                      sigma=matrix(c(25.0, 17.5, 12.3,                                     17.5, 25.0, 17.5,                                     12.3, 17.5, 25.0), nrow=3, byrow=true)) dat <- data.frame(rbind(dat.tx.a, dat.tx.b)) names(dat) = c("measure.1", "measure.2", "measure.3") dat <- data.frame(subject.id=factor(1:500), tx=rep(c("a", "b"), each=250), dat) rm(dat.tx.a, dat.tx.b) dat <- reshape(dat, varying=c("measure.1", "measure.2", "measure.3"),                 idvar="subject.id", direction="long")  df.model<-dat %>%            group_by(tx) %>%            (model1=lmer(measure~(1|subject.id), data=.)) %>%             (model2=lmer(measure~time+(1|subject.id), data=.))

here error message:

error in as.data.frame.default(x[[i]], optional = true) :    cannot coerce class "structure("lmermod", package = "lme4")" data.frame

the code works if remove line runs model2. seems dataframe accept 1 column list of models? lot.

just pass multiple models do() :

df.model<-dat %>%   group_by(tx) %>%   (model1=lmer(measure~(1|subject.id), data=.),       model2=lmer(measure~time+(1|subject.id), data=.))

also note in example using mass package.


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