R Step函数在全局环境中查找数据，而不是在定义的函数内部

Question

我对逐步回归有疑问，我的理解是我没有正确传递参数Data。

我有这个功能：

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)
}

当我尝试使用以下参数运行它时

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)

我收到一个错误： is.data.frame(data) 中的错误：找不到对象“数据”

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

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

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

我猜我的功能步骤实现有误，但是我不完全知道如何以正确的方式进行操作。

Answer 1

您需要意识到公式始终具有关联的环境，请参阅help("formula")。永远不要将文本传递给模型函数的 formula 参数，永远不要。如果这样做，您迟早会遇到范围界定问题。通常，我会建议使用语言进行计算，但您也可以从正确范围内的文本创建公式：

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

（公共服务公告：step-wise regression is a garbage generator。有更好的统计技术可用。）