R stargazer package output: Missing F statistic for felm regression (lfe package)

Question

I am trying to use the stargazer package to output my regression results. I performed my regressions using felm from the lfe package. The stargazer output tables shows everything properly except the F statistic values which remain blank. The issue does not arise with the lm results.

What is the reason and how can I get F statistic values for my felm regressions to appear in the stargazer output?

I know I can manually add a line to show the F-values but I would prefer a more automatic approach if it's possible.

Below is a sample code using data provided here

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")

Output:

====================================================================
                                        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

paqmo · Accepted Answer · 2017-05-23T13:54:37.017

There doesn't seem to be a way to automate within stargazer, which is great package, but is not extensible. The option keep.stat = "f" does not produce an f-stat for the felm object. However, texreg has an option that includes the f-stat for felm objects.

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)

Produces:

==================================================
                          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

The createTexreg function allows you to choose the specific stats you wish to extract and display. You first need to write a little function to extract objects from the summary.felm object and then turn that into a texreg object.

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)

Now, run the function, setting the argument include.f.prof = F and send it to 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

Thanks. I have never used 'texreg' but this looks really helpful. However, this way extends the height of table unnecessarily - do you know of a way the R^2 and F-statistic values from different kinds of models can be arranged in a single row instead of them taking different rows? — Learner Yoda, May 23 '17 at 07:06
Fortunately, `texreg` is highly extensible. I recommend checking out the [manual](https://cran.r-project.org/web/packages/texreg/vignettes/texreg.pdf) to see how to use the `createTexreg` function. I will add a function above that does the trick. — paqmo, May 23 '17 at 13:49

score 1 · Answer 2 · answered May 16 '17 at 15:17

Here is a not completely satisfactory solution for your problem.
I hope this could help you.

Get F statistic from 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

Then add the F statistic in the notes of the table generated using 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")

The final LaTeX table is:

I would have around 8 models in my table. Inserting F values of all in the notes section might not be very useful. But your solution has given me another idea - I could extract the F values of all models, insert them into a vector and then `add.line`. This involves some effort and is not totally automated but it seems better than not having F value at all. — Learner Yoda, May 23 '17 at 07:09

R stargazer package output: Missing F statistic for felm regression (lfe package)

2 Answers2