逐步删除每个 Regressor

Question

是否有机会指定完整模型一次，然后一个接一个地删除回归器，并用它生成一个漂亮的观星表，而不必一次又一次地编写每条回归线？

data <- datasets::airquality
# Treating Month and Day as crosssectional and time fixed effects

re1 <- plm(data = data, Ozone~Solar.R+Wind+Temp,
       index=c("Month", "Day"), model="within", effect="twoways") # full model 
# this is the only regression line I actually want to write.  
# The other regressors should be automatically dropped one by one in subsequent regressions.

re2 <- plm(data = data, Ozone~Wind+Temp,
       index=c("Month", "Day"), model="within", effect="twoways") # first regressor dropped

re3 <- plm(data = data, Ozone~Solar.R+Temp,
       index=c("Month", "Day"), model="within", effect="twoways") # second regressor dropped

re4 <- plm(data = data, Ozone~Solar.R+Wind,
       index=c("Month", "Day"), model="within", effect="twoways") # third regressor dropped

stargazer(re1, re2, re3, re4, 
          type = "html", 
          title = "Dropped after one another",
          out="HopeThisWorks.html")

我已经研究了 step() 函数，但这并没有太大帮助，因为我的目标不是根据重要性或其他任何东西下降。

Answer 1

 re1 <- plm(data = data, Ozone~Solar.R+Wind+Temp,
   index=c("Month", "Day"), model="within", effect="twoways") # full model 


 A=lapply(paste0(".~.-",c("Solar.R","Wind","Temp")),function(x)update(re1,as.formula(x)))
[[1]]

Model Formula: Ozone ~ Wind + Temp

Coefficients:
   Wind    Temp 
-2.6933  2.3735 


[[2]]

Model Formula: Ozone ~ Solar.R + Temp

Coefficients:
 Solar.R     Temp 
0.040986 2.782978 


[[3]]

Model Formula: Ozone ~ Solar.R + Wind

Coefficients:
  Solar.R      Wind 
 0.096607 -4.841992

现在可以在全局环境中访问它：使用

 list2env(setNames(A,paste0("re",seq_along(A)+1)),.GlobalEnv)

 stargazer(re1, re2, re3, re4, 
      type = "html", 
      title = "Dropped after one another",
      out="HopeThisWorks.html")

Answer 2

这是一个更灵活的选择：

bene <- function(data = datasets::airquality,
                 depvar = "Ozone",
                 covariates = c("Wind","Temp","Solar.R")){

  funny <- function(id){
    covs <- ifelse(is.na(id),paste0(covariates,collapse = " + "),paste0(covariates[-id],collapse = " + "))

    model <- eval(parse(text=paste0("plm(data = data,",depvar," ~ ",covs,",index=c('Month', 'Day'), model='within', effect='twoways')")))

    return(model)
  }

  xx <- capture.output(stargazer::stargazer(purrr::map(c(NA,1:length(covariates)),funny),
                                            type = "html",
                                            out = paste0("results/model.html"),
                                            star.cutoffs = c(0.05,0.01,0.001),
                                            title = paste0(depvar)))

  models <- purrr::map(c(NA,1:length(covariates)),funny)
  map(models,function(x)print(summary(x)))
}

bene(data = datasets::airquality,
     depvar = "Ozone",
     covariates = c("Wind","Temp","Solar.R"))

Answer 3

您可以使用（改编）这个（到目前为止只有逐步工作的）函数，该函数向您显示观星器的输出并将回归表保存为 html 文件。

stepwise_model <- function(data = "datasets::airquality",
                       depvar = "Ozone",
                       covariates = c("Wind","Temp","Solar.R")){


data_df <- eval(parse(text = data)) 


models <- c()
for(q in 1:length(covariates)){

  label <- paste0("mod_",depvar,"_",q)
  models[q] <- label
  cov <- paste0(covariates[1:q],collapse = " + ")

  eval(parse(text = paste0(label," <<- plm::plm(",depvar," ~ ",cov,",data = data_df,index=c('Month', 'Day'), model='within', effect='twoways')")))

  eval(parse(text  = paste0("print(summary(",label,"))")))
}

modellist <- eval(parse(text = paste0("list(",paste0(models,collapse = ","),")")))

xx <- capture.output(stargazer::stargazer(modellist ,
                                          type = "html",
                                          out = paste0("results/paper/models/mod_",depvar,".html"),
                                          star.cutoffs = c(0.05,0.01,0.001),
                                          title = paste0(depvar)))

}

stepwise_model()