回归表中的参考类别

Question

我有一个线性回归模型的结果,在R中有一个因子变量,我想要很好然后输出到LaTeX.理想情况下,因子变量将通过一个行显示在表中,该行给出变量的名称和参考类别,否则为空白,然后下面带有缩进文本的行给出因子的级别以及相应的估计值.

我一直用这个stargazer包把R的回归结果变成了LaTeX,但是看不到用它来实现我想要的结果.一个例子:

library(ggplot2)
library(stargazer)

levels(diamonds$cut)

options(contrasts = c("contr.treatment", "contr.treatment"))
model1 <- lm(price~cut,data=diamonds)
stargazer(model1,type='text')

这会产生默认输出:

===============================================
                        Dependent variable:    
                    ---------------------------
                               price           
-----------------------------------------------
cutGood                     -429.893***        
                             (113.849)         

cutVery Good                -376.998***        
                             (105.164)         

cutPremium                   225.500**         
                             (104.395)         

cutIdeal                    -901.216***        
                             (102.412)         

Constant                   4,358.758***        
                             (98.788)          

-----------------------------------------------
Observations                  53,940           
R2                             0.013           
Adjusted R2                    0.013           
Residual Std. Error   3,963.847 (df = 53935)   
F Statistic         175.689*** (df = 4; 53935) 
===============================================
Note:               *p<0.1; **p<0.05; ***p<0.01

这就是我想要的:

===============================================
                        Dependent variable:    
                    ---------------------------
                               price           
-----------------------------------------------

Cut (Reference: Fair)

   Good                     -429.893***        
                             (113.849)         

   Very Good                -376.998***        
                             (105.164)         

   Premium                   225.500**         
                             (104.395)         

   Ideal                    -901.216***        
                             (102.412)         

Constant                   4,358.758***        
                             (98.788)          

-----------------------------------------------
Observations                  53,940           
R2                             0.013           
Adjusted R2                    0.013           
Residual Std. Error   3,963.847 (df = 53935)   
F Statistic         175.689*** (df = 4; 53935) 
===============================================
Note:               *p<0.1; **p<0.05; ***p<0.01

stargazer没有太多的hackery 有没有办法实现这个目标？是否有其他包可以更容易做到？

Answer 1

不完全是您想要的，但您可以通过 covariate.labels 参数手动指定协变量标签。不过，我无法找到如何添加标题，需要您手动添加换行符。

stargazer(model1,type='text',
          covariate.labels=c("Cut (Reference: Fair) Good",
                             ".  Very good",
                             ".  Premium",
                             ".  Ideal"))


======================================================
                               Dependent variable:    
                           ---------------------------
                                      price           
------------------------------------------------------
Cut (Reference: Fair) Good         -429.893***        
                                    (113.849)         

. Very good                        -376.998***        
                                    (105.164)         

. Premium                           225.500**         
                                    (104.395)         

. Ideal                            -901.216***        
                                    (102.412)         

Constant                          4,358.758***        
                                    (98.788)          

------------------------------------------------------
Observations                         53,940           
R2                                    0.013           
Adjusted R2                           0.013           
Residual Std. Error          3,963.847 (df = 53935)   
F Statistic                175.689*** (df = 4; 53935) 
======================================================
Note:                      *p<0.1; **p<0.05; ***p<0.01