R 具有子集和基线规范的回归+；不同变量

我想在基线规范上回归一个变量，然后再回归七个附加变量（即8个回归）。我想对data.frame的两个子集和附加变量的两个子集这样做

然后，我想将这些8x2x2=32回归的输出按子集组合（SO4个文件）保存在

stargazer

中。可以想象，这是一项巨大的打字工作。因此，一些答案与此相关（例如，使用

ddply

），但我很难将两者结合起来，尤其是在每次回归中基线变量保持不变这一事实

以下是我将基线变量（控制）和附加变量的数量减少到两个的数据：

Two.Year <- 1:4
Length <- 4:8
NumAck <- 8:12
degree_max <- 15:19
degree_median <- 16:20
katz_max <- 19:23
katz_median <- 23:27
Year <- rep(c("early","late"), each=2)

Master <-as.data.frame(cbind(
 Two.Year, Length, NumAck, degree_max, degree_median, katz_max, katz_median, Year
 ))

第二个和第三个变量都以

\u max

结尾，因此

lm（2.Year~Length+NumAck+degree\u max，Data=Master）

和

lm（2.Year~Length+NumAck+katz_max，Data=Master）

。这给出了第二个子集，定义为所有以

\u max

结尾的变量和那些以

\u median

结尾的变量。到目前为止，我用

grepl（“\u median”，names（Master））

和

grepl（“\u max”，names（Master））

提取这些变量

如前所述，我想保存分组子集的输出，即（I）早期和最大值，（II）早期和中位数，（III）晚期和最大值，以及（IV）晚期和中位数的所有回归

到目前为止我试过了

Master.subset <- split(Master, Master$time)
ols <- ddply( Master[ Master$time %in% c('early','late'), ], "time",
  function(Master) coefficients(lm(Two.Year~., data=Master)))

---

Master.subset这是我最后做的

首先，我定义了用于三个循环的变量：

# Write baseline model
baseline <- "Two.Year ~ Length + numAck"
# Write the model specific variables
measure <- c("degree", "katz")
# Write variable which determines the subset
timepoints <- c("early", "late")

# Write baseline model
baseline <- "Two.Year ~ Length + numAck"
# Write the model specific variables
measure <- c("degree", "katz")
# Write variable which determines the subset
timepoints <- c("early", "late")

# Output matrix
ols <- matrix()
# First loop for the time
for (tmpnt in considered_time) {
  # Estimate baseline model which is constant in tmpnt
  ols$baseline <- lm(as.formula(baseline),
    data=subset(Master, timepoint==tmpnt)
    )
  ols <- ols[-1] # for some reason the first column in ols is empty
  # Second loop for the variable subset
  for (type in c("median", "max", "mean")) {
    # Third loop for the estimation of all the other models
    for (msr in measures) {
      ols[[msr]] = lm(as.formula(paste(baseline, paste(msr, type, sep="_"), sep="+")),
        data=subset(Master, timepoint==tmpnt)
        )
      }
    # Write output to file
    stargazer(ols,
     title=paste("Regression output for ",tmpnt," subsample using ",type),    
     )
   }
 }