如何动态地将'object'参数传递给anova()函数

Question

我正在努力编写一个脚本,允许更灵活的方法来比较使用lme4或nlme包的不同线性混合效果模型.因为我不想为我添加或删除的每个模型调整脚本,所以我正在寻找一种动态方法.这样做我只需要调整一个包含模型公式的字符串的变量.

这个工作正常,除非anova()进来.anova()不接受包含适当类的元素列表:

###### Here is my problem
# comparing models by means of ANOVA
anova(lme.lst)                                  #### --> does not work
anova(lme.lst[[1]], lme.lst[[2]], lme.lst[[3]]) #### would work but kills the dynamic approach
######

我没有想出一个简洁的方法来分解列表并将多个参数传递给anova()函数.我试过unlist()没有任何成功.

这是一个最小的例子(改编自lme4手册,第8页):

require(lme4)
require(AICcmodavg)

# Variable containing of strings in order to describe the fixed effect terms 
# (wihout response/dependen variable)                                            ### should be orderd from
callModel <- c("angle ~ recipe + temp        + (1|recipe:replicate)",  # model1  ### small
               "angle ~ recipe + temperature + (1|recipe:replicate)",  # model2  ### too                
               "angle ~ recipe * temperature + (1|recipe:replicate)")  # model3  ### BIG

# convert string array 'callFeVar' into a list of formulas
callModel <- sapply(callModel, as.formula)

# create an empty list for safing the results of fitted model 
lme.lst <- list()
# do model fitting in a loop and change list names
for (i in 1 : length(callModel)) {
  lmeTmp <- lmer(callModel[[i]], cake, REML= FALSE)
  lme.lst[i] <- list(lmeTmp)
  names(lme.lst)[i] <- deparse(callModel[[i]])
}
# remove temporary variable
rm(lmeTmp)

# summary of models
lapply(lme.lst, summary)

###### Here is my problem
# comparing models by means of ANOVA
anova(lme.lst)                                  #### --> does not work
anova(lme.lst[[1]], lme.lst[[2]], lme.lst[[3]]) #### would work but kills the dynamic approach
######

# comparing models by means of AICc
aictab(lme.lst)                                 #### accepts list

Answer 1

do.call 使用列表中提供的参数调用函数.

do.call(anova, lme.lst)