6

这是MWE：

library(pscl)

data("bioChemists", package = "pscl")

fm_pois <- glm(art ~ ., data = bioChemists, family = poisson)
fm_qpois <- glm(art ~ ., data = bioChemists, family = quasipoisson)
fm_nb <- glm.nb(art ~ ., data = bioChemists)
fm_zinb <- zeroinfl(art ~ . | 1, data = bioChemists, dist = "negbin")

library(stargazer)
stargazer(
  fm_pois, fm_qpois,  fm_nb, fm_zinb
  , type = "text"
)

=============================================================================
                                      Dependent variable:                    
                  -----------------------------------------------------------
                                              art                            
                   Poisson   glm: quasipoisson     negative     zero-inflated
                                link = log         binomial      count data  
                     (1)            (2)              (3)             (4)     
-----------------------------------------------------------------------------
femWomen          -0.225***      -0.225***        -0.216***       -0.216***  
                   (0.055)        (0.074)          (0.073)         (0.073)   

marMarried         0.155**        0.155*            0.150*         0.150*    
                   (0.061)        (0.083)          (0.082)         (0.082)   

kid5              -0.185***      -0.185***        -0.176***       -0.176***  
                   (0.040)        (0.054)          (0.053)         (0.053)   

phd                 0.013          0.013            0.015           0.015    
                   (0.026)        (0.036)          (0.036)         (0.036)   

ment               0.026***      0.026***          0.029***       0.029***   
                   (0.002)        (0.003)          (0.003)         (0.003)   

Constant           0.305***       0.305**           0.256*         0.256*    
                   (0.103)        (0.139)          (0.137)         (0.139)   

-----------------------------------------------------------------------------
Observations         915            915              915             915     
Log Likelihood    -1,651.056                      -1,561.958     -1,560.959  
theta                                          2.264*** (0.271)              
Akaike Inf. Crit. 3,314.113                       3,135.917                  
=============================================================================
Note:                                             *p<0.1; **p<0.05; ***p<0.01

我正在寻找这样的多列输出：

=============================================================================
                                      Dependent variable:                    
                  -----------------------------------------------------------
                                              art                            
                           Poisson              Negative Binomial 

                    Poisson     QuasiPoisson         NB           ZINB

                     (1)            (2)              (3)             (4)     
-----------------------------------------------------------------------------
femWomen          -0.225***      -0.225***        -0.216***       -0.216***  
                   (0.055)        (0.074)          (0.073)         (0.073)   

marMarried         0.155**        0.155*            0.150*         0.150*    
                   (0.061)        (0.083)          (0.082)         (0.082)   

kid5              -0.185***      -0.185***        -0.176***       -0.176***  
                   (0.040)        (0.054)          (0.053)         (0.053)   

phd                 0.013          0.013            0.015           0.015    
                   (0.026)        (0.036)          (0.036)         (0.036)   

ment               0.026***      0.026***          0.029***       0.029***   
                   (0.002)        (0.003)          (0.003)         (0.003)   

Constant           0.305***       0.305**           0.256*         0.256*    
                   (0.103)        (0.139)          (0.137)         (0.139)   

-----------------------------------------------------------------------------
Observations         915            915              915             915     
Log Likelihood    -1,651.056                      -1,561.958     -1,560.959  
theta                                          2.264*** (0.271)              
Akaike Inf. Crit. 3,314.113                       3,135.917                  
=============================================================================
Note:                                             *p<0.1; **p<0.05; ***p<0.01
  1. 第一行应该有Poisson前两列和Negative Binomial接下来两列的单词。
  2. 第二行应该有列名 ，如Poisson、和。Quasi PoissonNegative BinomialZero Inflated Negative Binomial

我找到了这个链接，但不知道如何获得这个链接。

4

1 回答 1

6

像尼克肯尼迪一样，我认为这stargazer不能直接产生你想要的输出。

因此，这里有一个解决方法：将stargazer表格保存在一个对象中并手动添加所需的行。我在这里硬编码；通过更多的努力，应该可以将文本自动居中在相应的列上方。请注意，我稍微更改了您的stargazer调用以隐藏（错误的）型号名称。

library(pscl)
library(stargazer)

data("bioChemists", package = "pscl")

fm_pois <- glm(art ~ ., data = bioChemists, family = poisson)
fm_qpois <- glm(art ~ ., data = bioChemists, family = quasipoisson)
fm_nb <- glm.nb(art ~ ., data = bioChemists)
fm_zinb <- zeroinfl(art ~ . | 1, data = bioChemists, dist = "negbin")

byLine <- 
  do.call("c", 
          strsplit(
            capture.output(
              stargazer(fm_pois, fm_qpois,  fm_nb, fm_zinb, 
                        type = "text", model.names = FALSE)
              ),
            "\n"))

result <- append(
  byLine, 
  c(
  "                        Poisson               Negative Binomial",
  "",
  "                   Poisson  QuasiPoisson      NB          ZINB"
  ), 
  after = c(4, 5, 6))

cat(paste(result, collapse = "\n"))

# ==================================================================
#                                 Dependent variable:               
#                   ------------------------------------------------
#                                         art                       
#                         Poisson               Negative Binomial
# 
#                    Poisson  QuasiPoisson      NB          ZINB
#                      (1)        (2)          (3)           (4)    
# ------------------------------------------------------------------
# femWomen          -0.225***  -0.225***    -0.216***     -0.216*** 
#                    (0.055)    (0.074)      (0.073)       (0.073)  
#                                                                   
# marMarried         0.155**    0.155*        0.150*        0.150*  
#                    (0.061)    (0.083)      (0.082)       (0.082)  
#                                                                   
# kid5              -0.185***  -0.185***    -0.176***     -0.176*** 
#                    (0.040)    (0.054)      (0.053)       (0.053)  
#                                                                   
# phd                 0.013      0.013        0.015         0.015   
#                    (0.026)    (0.036)      (0.036)       (0.036)  
#                                                                   
# ment               0.026***  0.026***      0.029***      0.029*** 
#                    (0.002)    (0.003)      (0.003)       (0.003)  
#                                                                   
# Constant           0.305***   0.305**       0.256*        0.256*  
#                    (0.103)    (0.139)      (0.137)       (0.139)  
#                                                                   
# ------------------------------------------------------------------
# Observations         915        915          915           915    
# Log Likelihood    -1,651.056              -1,561.958    -1,560.959
# theta                                  2.264*** (0.271)           
# Akaike Inf. Crit. 3,314.113               3,135.917               
# ==================================================================
# Note:                                  *p<0.1; **p<0.05; ***p<0.01
于 2015-07-24T16:23:59.800 回答