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我正在努力编写一个脚本,该脚本允许更灵活的方法来比较使用lme4ornlme包的不同线性混合效果模型。由于我不想为添加或删除的每个模型调整脚本,因此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字符串的变量。

这工作正常,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
######

我没有想出一种巧妙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。

这是一个最小的示例(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
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1 回答 1

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do.call使用列表中提供的参数调用函数。

do.call(anova, lme.lst)
于 2015-04-25T01:21:38.810 回答