函数内的update()只搜索全局环境？

Question

我试着编写一个包装函数来批量进行似然比检验.我尝试包含update()来更新初始模型.但是,它似乎不是在函数内部查找对象,而是在全局环境中搜索对象.

fake <- data.frame(subj= rep(1:5, 4), 
                   factor1 = rep(LETTERS[c(1,2,1,2)], each=5), 
                   factor2 = rep(letters[1:2], each=10), 
                   data=sort(rlnorm(20)))

foo <- function(){
                  temp <- fake
                  model1 <- lmer(data~factor1*factor2 + (1 |subj), temp)
                  model1a <- update(model1, ~.-factor1:factor2)
                  model1a}

它在下面给出了一条错误消息:

Error in eval(expr, envir, enclos) : object 'factor1' not found

无论如何在函数内进行update()搜索？谢谢!

编辑:

我犯了一个错误.我想把"temp"传给lmer而不是"假".

EDIT2:建议的一个方便的解决方案是简单地指定数据对象.虽然update()现在没有问题,但anova()似乎认为我试图比较的模型是基于不同的数据对象

 foo <- function(){
                  temp <- fake
                  model1 <- lmer(data~factor1*factor2 + (1 |subj), data=temp)
                  model1a <- update(model1, ~.-factor1:factor2, data=temp)
                  anova(model1, model1a)
            }
 foo()

我收到一条错误消息:

 Error in anova(model1, model1b) : 
   all models must be fit to the same data object

我想这个错误超出了update().但我想知道是否有人知道如何解决这个问题.请注意,如果我在不使用update()的情况下编写函数,而是拼出模型(见下文),则上面的错误就会消失:

 foo <- function(){
                  temp <- fake
                  model1 <- lmer(data~factor1*factor2 + (1 |subj), data=temp)
                  model1a <- lmer(data~factor1 + factor2 + (1 |subj), data=temp)
                  anova(model1, model1a)
            }
 foo()

 Data: temp
 Models:
 model1a: data ~ factor1 + factor2 + (1 | subj)
 model1: data ~ factor1 * factor2 + (1 | subj)
         Df     AIC    BIC  logLik  Chisq Chi Df Pr(>Chisq)  
 model1a  5 -4.6909 3.7535  7.3454                           
 model1   6 -8.8005 1.3327 10.4003 6.1097      1    0.01344 *
 ---
 Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

编辑3:似乎问题出在anova()上.我也试过@hadley的建议

foo2 <- function(){
  my_update <- function(mod, formula = NULL, data = NULL) {
  call <- getCall(mod)
  if (is.null(call)) {
    stop("Model object does not support updating (no call)", call. = FALSE)
  }
  term <- terms(mod)
  if (is.null(term)) {
    stop("Model object does not support updating (no terms)", call. = FALSE)
  }
  if (!is.null(data)) call$data <- data
  if (!is.null(formula)) call$formula <- update.formula(call$formula, formula)
  env <- attr(term, ".Environment")
  eval(call, env, parent.frame())}

      model1 <- lmer(data~factor1*factor2 + (1 |subj), temp)
      model1a <- my_update(model1, ~.-factor1:factor2)
      anova(model1, model1a)
 }
 foo2()

我收到一条错误消息,如下所示:

 Error in as.data.frame.default(data) : 
   cannot coerce class 'structure("mer", package = "lme4")' into a data.frame

Answer 1

我之前也被这种行为所困扰,所以我写了自己的版本update.它评估公式环境中的所有内容,因此它应该相当健壮.

my_update <- function(mod, formula = NULL, data = NULL) {
  call <- getCall(mod)
  if (is.null(call)) {
    stop("Model object does not support updating (no call)", call. = FALSE)
  }
  term <- terms(mod)
  if (is.null(term)) {
    stop("Model object does not support updating (no terms)", call. = FALSE)
  }

  if (!is.null(data)) call$data <- data
  if (!is.null(formula)) call$formula <- update.formula(call$formula, formula)
  env <- attr(term, ".Environment")

  eval(call, env, parent.frame())
}

library(nlme4)

fake <- data.frame(
  subj = rep(1:5, 4), 
  factor1 = rep(LETTERS[c(1,2,1,2)], each = 5), 
  factor2 = rep(letters[1:2], each = 10), 
  data = sort(rlnorm(20)))

foo <- function() {
  temp <- fake
  model1 <- lmer(data ~ factor1 * factor2 + (1 | subj), fake)
  model1a <- my_update(model1, ~ . - factor1:factor2)
  model1a
}
foo()