Question

我想计算回归残差的聚类误差。我知道如何在R中运行随机效应模型。

set.seed(50)
data <- data.frame(id=rep(1:10,10),income=rnorm(100),education=rnorm(100))
data$id <- factor(data$id)

library(nlme)
reg <- lme(income ~ education -1,data = data, random = ~ 1 | id)

我不确定如何将标准错误聚集在id级别。

Answer 1

您可以使用plm包。详见here。但这里是如何指定随机效应模型：

set.seed(50)
data <- data.frame(id=rep(1:10,10),income=rnorm(100),education=rnorm(100))
data$id <- factor(data$id)

library(plm)
reg <- plm(income ~ education,
           data= data, 
           index = c('id'), 
           effect = "individual", 
           model ='random')

summary(reg)

Oneway (individual) effect Random Effect Model 
   (Swamy-Arora's transformation)

Call:
plm(formula = income ~ education, data = data, effect = "individual", 
    model = "random", index = c("id"))

Balanced Panel: n = 10, T = 10, N = 100

Effects:
                  var std.dev share
idiosyncratic 0.98161 0.99076 0.973
individual    0.02766 0.16630 0.027
theta: 0.1167

Residuals:
     Min.   1st Qu.    Median   3rd Qu.      Max. 
-2.777437 -0.626498  0.082894  0.602743  2.732686 

Coefficients:
             Estimate Std. Error t-value Pr(>|t|)
(Intercept) -0.116959   0.112068 -1.0436   0.2992
education   -0.033914   0.101471 -0.3342   0.7389

Total Sum of Squares:    95.329
Residual Sum of Squares: 95.221
R-Squared:      0.0011386
Adj. R-Squared: -0.0090539
F-statistic: 0.111707 on 1 and 98 DF, p-value: 0.73892

并获得聚类标准错误：

coeftest(reg, vcov=vcovHC(reg,type="HC0",cluster="group"))

如何在R中使用聚类错误进行随机效应回归？

1 个答案: