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lme4
ornlme
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