回归表中的引用类别

Question

我得到了一个线性回归模型的结果，在 R 中有一个因子变量，我想要漂亮，然后输出到 LaTeX。理想情况下，因子变量将通过一行显示在表中，该行给出变量的名称和引用类别，否则为空白，然后是下面带有缩进文本的行，这些行给出了因子的水平以及相应的估计值。

我长期使用 stargazer将回归结果从 R 获取到 LaTeX 的包，但看不到用它实现我想要的结果的方法。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

有什么办法可以在 stargazer 中实现这一点吗？没有太多的黑客？是否有其他软件包可以更简单地做到这一点？

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。但是，我无法找到如何添加标题，这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