如何在 Stargazer 中为回归添加列名

Question

I am trying to use Stargazer to show regressions results in R I was wondering if it was possible to change the numbers (1), (2), etc in names in the tables?

There are 4 regressions in total and i would like to be able to name each of them like: Linear regression, linear regression NA, etc...

stargazer(H1.1,H4.1,H1,H4, type="text", title="regression results US vs Global: launches")

regression results US vs Global: launches
===============================================================================================================
                                                        Dependent variable:                                    
                    -------------------------------------------------------------------------------------------
                                                             launches                                          
                             (1)                    (2)                    (3)                    (4)          
---------------------------------------------------------------------------------------------------------------
Twitter                    0.321***               0.346***               0.254**                0.283**        
                           (0.106)                (0.107)                (0.123)                (0.124)        
                                                                                                               
likes                      0.578***               0.584***               0.584***               0.617***       
                           (0.147)                (0.148)                (0.176)                (0.178)        
                                                                                                               
retweets                   -0.279*                -0.366**                -0.269                -0.371**       
                           (0.156)                (0.157)                (0.167)                (0.168)        
                                                                                                               
replies                   -0.355***              -0.366***               -0.288**               -0.323**       
                           (0.121)                (0.122)                (0.141)                (0.142)        
                                                                                                               
Twitter:replies                                                           -0.056                 -0.005        
                                                                         (0.126)                (0.127)        
                                                                                                               
Twitter:likes                                                             -0.059                 -0.093        
                                                                         (0.202)                (0.204)        
                                                                                                               
Twitter:retweets                                                          0.013                  0.006         
                                                                         (0.212)                (0.214)        
                                                                                                               
Constant                    -0.000                 -0.000                 0.067                  0.056         
                           (0.071)                (0.072)                (0.090)                (0.091)        
                                                                                                               
---------------------------------------------------------------------------------------------------------------
Observations                 168                    168                    168                    168          
R2                          0.162                  0.151                  0.171                  0.158         
Adjusted R2                 0.142                  0.131                  0.135                  0.121         
Residual Std. Error    0.926 (df = 163)       0.932 (df = 163)       0.930 (df = 160)       0.937 (df = 160)   
F Statistic         7.893*** (df = 4; 163) 7.267*** (df = 4; 163) 4.719*** (df = 7; 160) 4.289*** (df = 7; 160)
===============================================================================================================
Note:                                                                               *p<0.1; **p<0.05; ***p<0.01

Answer 1

As the comment suggests

model1 <- lm(rating ~ complaints + privileges + learning + raises , data=attitude)

model2 <- lm(rating ~ complaints + privileges + learning + raises + critical, data=attitude)

stargazer(model1, model2, type="text", column.labels=c("FIRST", "SECOND"), model.numbers=FALSE)


=================================================================
                                 Dependent variable:             
                    ---------------------------------------------
                                       rating                    
                            FIRST                  SECOND        
-----------------------------------------------------------------
complaints                 0.691***               0.692***       
                           (0.146)                (0.149)        
                                                                 
privileges                  -0.103                 -0.104        
                           (0.132)                (0.135)        
                                                                 
learning                    0.246                  0.249         
                           (0.154)                (0.160)        
                                                                 
raises                      -0.026                 -0.033        
                           (0.184)                (0.202)        
                                                                 
critical                                           0.015         
                                                  (0.147)        
                                                                 
Constant                    11.834                 11.011        
                           (8.535)                (11.704)       
                                                                 
-----------------------------------------------------------------
Observations                  30                     30          
R2                          0.715                  0.715         
Adjusted R2                 0.670                  0.656         
Residual Std. Error    6.996 (df = 25)        7.139 (df = 24)    
F Statistic         15.697*** (df = 4; 25) 12.063*** (df = 5; 24)
=================================================================
Note:                                 *p<0.1; **p<0.05; ***p<0.01