Get stargazer to print number of observations in multinomial logistic regression

Question

is there a way to print the number of observations for the multinomial logistic regression model in a stargazer table? This sample code illustrates the problem. Thank you.

var1<-sample(c('A', 'B', 'C'), size=1000, replace=T)
var2<-rnorm(n=1000)
var3<-rnorm(n=1000)
df<-data.frame(var1, var2, var3)
library(nnet)
mod1<-multinom(var1~var2+var3, data=df)
library(stargazer)
stargazer(mod1, nobs=T, type="text")

Answer 1

Stargazer is really nice package however sometimes you have to do some tweaks "by-hand". If you want to have number of observation in you output this is how to go about it:

stargazer(mod1, 
          type="text", 
          add.lines = list(c("n", nrow(df), nrow(df))))

if you want to create a table in latex you can use:

stargazer(mod1, 
          type="latex", 
          add.lines = list(c("\\textit{$n$}", nrow(df), nrow(df))))

This approach is so that once you render it in latex "n" will be in mathematical font.

==============================================
                      Dependent variable:     
                  ----------------------------
                        B              C      
                       (1)            (2)     
----------------------------------------------
var2                  0.0002        -0.055    
                     (0.080)        (0.079)   
                                              
var3                  -0.088         0.012    
                     (0.078)        (0.077)   
                                              
Constant              -0.029         0.030    
                     (0.078)        (0.077)   
                                              
----------------------------------------------
n                      1000          1000     
Akaike Inf. Crit.   2,206.078      2,206.078  
==============================================
Note:              *p<0.1; **p<0.05; ***p<0.01

Hopefully, this is what you have been asking for.

Answer 2

Would texreg work for you instead?

library(texreg)
screenreg(list(mod1))
# ====================================
#                 B          C        
# ------------------------------------
# (Intercept)         0.01      -0.03 
#                    (0.08)     (0.08)
# var2               -0.06       0.01 
#                    (0.08)     (0.08)
# var3                0.04       0.10 
#                    (0.08)     (0.08)
# ------------------------------------
# AIC              2206.34    2206.34 
# BIC              2235.79    2235.79 
# Log Likelihood  -1097.17   -1097.17 
# Deviance         2194.34    2194.34 
# Num. obs.        1000       1000    
# ====================================
# *** p < 0.001, ** p < 0.01, * p < 0.05

I may be wrong but I'm not sure this can be easily done with nnet and stargazer. You could make your model mimic that of different output. See here for that type of approach.