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我正在尝试使用该stargazer包来输出我的回归结果。我使用felmfrom the lfepackage 执行了我的回归。输出表正确显示所有内容,stargazer但 F 统计值保持空白。结果不会出现问题lm

是什么原因以及如何让我的felm回归出现在stargazer输出中的 F 统计值?

我知道我可以手动添加一行来显示 F 值,但如果可能的话,我更喜欢更自动的方法。

以下是使用此处提供的数据的示例代码

library(foreign)
temp_dat <- read.dta("http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/test_data.dta")

temp_lm <- lm(y ~ x, temp_dat)
temp_felm <- felm(y ~ x, temp_dat)

library(stargazer)
stargazer(temp_lm, temp_felm, type = "text")

输出:

====================================================================
                                        Dependent variable:         
                                ------------------------------------
                                                 y                  
                                            OLS               felm  
                                            (1)               (2)   
--------------------------------------------------------------------
x                                        1.035***           1.035***
                                          (0.029)           (0.029) 

Constant                                   0.030             0.030  
                                          (0.028)           (0.028) 

--------------------------------------------------------------------
Observations                               5,000             5,000  
R2                                         0.208             0.208  
Adjusted R2                                0.208             0.208  
Residual Std. Error (df = 4998)            2.005             2.005  
F Statistic                     1,310.740*** (df = 1; 4998)         
====================================================================
Note:                                    *p<0.1; **p<0.05; ***p<0.01

4

2 回答 2

3

似乎没有办法在内部自动化stargazer,这是一个很棒的包,但不可扩展。该选项keep.stat = "f"不会为felm对象生成 f-stat。但是,texreg有一个选项包括felm对象的 f-stat。

library(foreign);library(texreg);library(lfe)
temp_dat <- read.dta("http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/test_data.dta")

temp_lm <- lm(y ~ x, temp_dat)
temp_felm <- felm(y ~ x, temp_dat)

screenreg(list(temp_lm, temp_felm), include.fstatistic = T)

产生:

==================================================
                          Model 1      Model 2    
--------------------------------------------------
(Intercept)                  0.03         0.03    
                            (0.03)       (0.03)   
x                            1.03 ***     1.03 ***
                            (0.03)       (0.03)   
--------------------------------------------------
R^2                          0.21                 
Adj. R^2                     0.21                 
Num. obs.                 5000         5000       
F statistic               1310.74                 
RMSE                         2.01                 
R^2 (full model)                          0.21    
R^2 (proj model)                          0.21    
Adj. R^2 (full model)                     0.21    
Adj. R^2 (proj model)                     0.21    
F statistic (full model)               1310.74    
F (full model): p-value                   0.00    
F statistic (proj model)               1310.74    
F (proj model): p-value                   0.00    
==================================================
*** p < 0.001, ** p < 0.01, * p < 0.05

createTexreg功能允许您选择要提取和显示的特定统计信息。您首先需要编写一个小函数来从对象中提取对象summary.felm,然后将其转换为texreg对象。

extract.felm <- function(model, include.f.full = TRUE, 
                         include.f.proj = TRUE,
                         include.rsquared = TRUE,
                         include.adjrs = TRUE, 
                         include.nobs = TRUE, ...) {

   s <- summary(model, ...)
   names <- rownames(s$coefficients)
   co <- s$coefficients[, 1]
   se <- s$coefficients[, 2]
   pval <- s$coefficients[, 4]

    gof <- numeric()
    gof.names <- character()
    gof.decimal <- logical()
    if (include.rsquared == TRUE) {
      rs <- s$r.squared
      gof <- c(gof, rs)
      gof.names <- c(gof.names, "R$^2$")
      gof.decimal <- c(gof.decimal, TRUE)
      }
   if (include.adjrs == TRUE) {
     adj <- s$adj.r.squared
     gof <- c(gof, adj)
     gof.names <- c(gof.names, "Adj.\\ R$^2$")
     gof.decimal <- c(gof.decimal, TRUE)
     }
   if (include.nobs == TRUE) {
     n <- s$N
     gof <- c(gof, n)
     gof.names <- c(gof.names, "Num.\\ obs.")
     gof.decimal <- c(gof.decimal, FALSE)
   }
    if (include.f.full == TRUE) {
      ffs <- s$fstat
      ffpval <- round(s$F.fstat[4],4)
      gof <- c(gof, ffs, ffpval)
      gof.names <- c(gof.names, "F statistic (Full model)", "F (full model): p-value")
      gof.decimal <- c(gof.decimal, TRUE, TRUE)
    }
    if (include.f.proj == TRUE) {
      fps <- s$P.fstat[5]
      fppval <- s$P.fstat[4]
      gof <- c(gof, fps, fppval)
      gof.names <- c(gof.names, "F statistic (proj. model)", "F (proj. model): p-value") #Modify the names as you see fit
      gof.decimal <- c(gof.decimal, TRUE, TRUE)
    }
     tr <- createTexreg(
       coef.names = names,
       coef = co,
       se = se,
       pvalues = pval,
       gof.names = gof.names,
       gof = gof,
       gof.decimal = gof.decimal
       )
   return(tr)
   }
setMethod("extract", signature = className("felm", "stats"),
             definition = extract.felm)

现在,运行函数,设置参数include.f.prof = F并将其发送到screenreg

> m <- extract.felm(temp_felm, include.f.proj = F)
> screenreg(list(temp_lm, m))

==================================================
                          Model 1      Model 2    
--------------------------------------------------
(Intercept)                  0.03         0.03    
                            (0.03)       (0.03)   
x                            1.03 ***     1.03 ***
                            (0.03)       (0.03)   
--------------------------------------------------
R^2                          0.21         0.21    
Adj. R^2                     0.21         0.21    
Num. obs.                 5000         5000       
RMSE                         2.01                 
F statistic (Full model)               1310.74    
F (full model): p-value                   0.00    
==================================================
*** p < 0.001, ** p < 0.01, * p < 0.05
于 2017-05-16T15:13:13.680 回答
1

对于您的问题,这是一个不完全令人满意的解决方案。
我希望这可以帮助你。

从 获取 F 统计量lfe:::summary.felm

(Fstat <- summary(temp_felm)$F.fstat)

###############
            F           df1           df2             p 
 1.310740e+03  1.000000e+00  4.998000e+03 4.252163e-255

然后在使用生成的表的注释中添加 F 统计量stargazer

stars <- ifelse(Fstat[4]<0.01,"***",ifelse(Fstat[4]<0.05,"**",ifelse(Fstat[4]<0.1,"*","")))
notes <- c(paste("F Statistic(full) \\hfill      ", round(Fstat[1],3),stars," (df = ",Fstat[2],"; ", Fstat[3],")",sep=""),
"Note:\\hfill *p<0.1; **p<0.05; ***p<0.01")

stargazer(temp_felm, notes=notes, notes.append=F, notes.label="", notes.align="l")

最终的 LaTeX 表格是: 在此处输入图像描述

于 2017-05-16T15:17:16.413 回答