CODEWITHSUNDEEP
rstargazerplm
Sulz
Sulz

Reputation: 445

stargazer output several models R

I run three different estimations of panel linear models (fixed effects model with two fixed effect (id and year)).

fixed_YIELD_mean_to_treat.100 <- plm(YIELD_mean_total ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")
fixed_YIELD_mean_fruits_treat.100<- plm(YIELD_mean_Fruit ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")
fixed_YIELD_mean_grain_treat.100<- plm(YIELD_mean_Cereal ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")

Now I try to create a stargazer output containing all three of the models:

stargazer( fixed_YIELD_mean_to_treat.100, fixed_YIELD_mean_fruits_treat.100, fixed_YIELD_mean_grain_treat.100, 
                   type = "html",
                   align = TRUE,
                   omit = c("year", "id"),
                   omit.labels = c("year FE", "id FE"),
                   add.lines= list(c("ID Fixed effects", "Yes", "Yes", "Yes"),
                                  c("Time Fixed effects", "Yes", "Yes", "Yes")),
                   out = ".test1.html" )

But than I get the error:

Error in if (is.na(s)) { : the condition has length > 1

If I only include 2 models it always works. How can I plot three models in one stargazer output?

Upvotes: 2

Views: 2169

Answers (1)

Marco
Marco

Reputation: 2817

As comment says, try to make shorter modelnames:

library("plm")
data("Produc", package="plm")

fe1 <- plm(pcap ~ hwy + water + unemp, data=Produc, index=c("state", "year"), model = "within")
fe2 <- plm(pcap ~ hwy + water + emp, data=Produc, index=c("state", "year"), model = "within")
fe3 <- plm(pcap ~ hwy + water + pc, data=Produc, index=c("state", "year"), model = "within")

stargazer(fe1, fe2, fe3, type="text")

================================================================
                                   Dependent variable:          
                          --------------------------------------
                                           pcap                 
                              (1)          (2)          (3)     
----------------------------------------------------------------
hwy                         2.023***     2.015***     1.999***  
                            (0.052)      (0.050)      (0.051)   
                                                                
water                       1.974***     1.989***     1.935***  
                            (0.043)      (0.058)      (0.063)   
                                                                
unemp                       -14.624                             
                            (19.682)                            
                                                                
emp                                       -0.073                
                                         (0.161)                
                                                                
pc                                                     0.003    
                                                      (0.004)   
                                                                
----------------------------------------------------------------
Observations                  816          816          816     
R2                           0.901        0.901        0.901    
Adjusted R2                  0.895        0.895        0.895    
F Statistic (df = 3; 765) 2,332.767*** 2,331.602*** 2,332.963***
================================================================
Note:                                *p<0.1; **p<0.05; ***p<0.01

Upvotes: 3

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