R Step 函數在全局環境中查找數據，而不是在定義的函數內部

Question

我有逐步回歸問題，我的理解是我沒有正確傳遞參數Data 。

我有這個功能：

ForwardStep <- function(df,yName, Xs, XsMin) {
    Data <- df[, c(yName,Xs)]
    fit <- glm(formula = paste(yName, " ~ ", paste0(XsMin, collapse = " + ")),
               data = Data, family = binomial(link = "logit") )
    ScopeFormula <- list(lower = paste(yName, " ~ ", paste0(XsMin, collapse = " + ")), 
                         upper = paste(yName, " ~ ", paste0(Xs, collapse = " + ")))
    result <- step(fit, direction = "forward", scope = ScopeFormula, trace = 1 )

    return(result)
}

當我嘗試使用以下參數運行它時

df <- data.frame(Y= rep(c(0,1),25),time = rpois(50,2), x1 = rnorm(50, 0,1),
                 x2 = rnorm(50,.5,2), x3 = rnorm(50,0,1))
yName = "Y"
Xs <- c("x1","x2","x3")
XsMin <- 1

res <- ForwardStep(df,Yname,Xs,XsMin)

我收到一個錯誤： is.data.frame(data) 中的錯誤：找不到對象“數據”

但是如果我首先在 Global Env 中定義Data ，它就可以正常工作。

Data <- df[, c(yName,Xs)]

res <- ForwardStep(df,Yname,Xs,XsMin)

我想我對函數 step 的實現有誤，但是我不知道如何以正確的方式執行。

Answer 1

您需要意識到公式始終具有關聯的環境，請參閱help("formula") 。 永遠不要將文本傳遞給模型函數的formula參數，永遠不要。 如果這樣做，遲早會遇到范圍界定問題。 通常，我建議改為使用語言進行計算，但您也可以從正確范圍內的文本創建公式：

ForwardStep <- function(df,Yname, Xs, XsMin) {
  Data <- df[, c(Yname,Xs)]
  f1 <- as.formula(paste(Yname, " ~ ", paste0(XsMin, collapse = " + ")))

  fit <- glm(formula = f1,
             data = Data, family = binomial(link = "logit") )
  f2 <- as.formula(paste(Yname, " ~ ", paste0(XsMin, collapse = " + ")))
  f3 <- as.formula(paste(Yname, " ~ ", paste0(Xs, collapse = " + ")))

  ScopeFormula <- list(lower = f2, 
                       upper = f3)
   step(fit, direction = "forward", scope = ScopeFormula, trace = 1)
}

df <- data.frame(Y= rep(c(0,1),25),time = rpois(50,2), x1 = rnorm(50, 0,1),
                 x2 = rnorm(50,.5,2), x3 = rnorm(50,0,1))
YName = "Y"
Xs <- c("x1","x2","x3")
XsMin <- 1

res <- ForwardStep(df,YName,Xs,XsMin)
#Start:  AIC=71.31
#Y ~ 1
#
#       Df Deviance    AIC
#<none>      69.315 71.315
#+ x1    1   68.661 72.661
#+ x3    1   68.797 72.797
#+ x2    1   69.277 73.277

（公共服務公告：逐步回歸是垃圾生成器。有更好的統計技術可用。）