r - 如何使用 stargazer 报告 coxph 回归的 exp(coefs)

Question

假设我有 my.model

My.model <- coxph(Surv(stop, event) ~ (rx + size + number) * strata(enum),
      cluster = id, bladder1)

我想创建一个模型报告表，其中包含 exp(coefs) 而不是 coefs

stargazer(my.model)

是否有像 exponentiate = TRUE 这样的参数会报告 exp(coefs) 而不是 coefs？或者我需要转换在传递给 stargazer() 之前对结果建模？

Answer 1

为了得到指数系数，需要添加参数apply.coef = exp, p.auto = FALSE, t.auto = FALSE。

My.model <- coxph(Surv(stop, event) ~ rx + size + number,
                  cluster = id, bladder)

原始模型未转换系数

stargazer(My.model, align=TRUE, 
          type="text",  digits = 3)
================================================
                         Dependent variable:    
                     ---------------------------
                                stop            
------------------------------------------------
rx                             -0.540*          
                               (0.200)          
                                                
size                           -0.055           
                               (0.070)          
                                                
number                        0.193***          
                               (0.046)          
                                                
------------------------------------------------
Observations                     340            
R2                              0.064           
Max. Possible R2                0.971           
Log Likelihood                -588.104          
Wald Test                12.510*** (df = 3)     
LR Test                  22.321*** (df = 3)     
Score (Logrank) Test     25.183*** (df = 3)     
================================================
Note: se in parenthesis *p<0.1; **p<0.05; ***p<0.01

使用参数apply.coef = exp取幂。

stargazer(My.model, align=TRUE, apply.coef = exp,
          type="text",  digits = 3)

================================================
                         Dependent variable:    
                     ---------------------------
                                stop            
------------------------------------------------
rx                            0.583***          
                               (0.200)          
                                                
size                          0.947***          
                               (0.070)          
                                                
number                        1.213***          
                               (0.046)          
                                                
------------------------------------------------
Observations                     340            
R2                              0.064           
Max. Possible R2                0.971           
Log Likelihood                -588.104          
Wald Test                12.510*** (df = 3)     
LR Test                  22.321*** (df = 3)     
Score (Logrank) Test     25.183*** (df = 3)     
================================================
Note: se in parenthesis *p<0.1; **p<0.05; ***p<0.01

但是，如您所见，星星提供了误导性的推论，因为 t.stat = coef/se，然而，在这种情况下，取幂的系数被用作计算 t 统计数据和 p 值的分子。

解决方案

解决方案是添加参数 p.auto = FALSE 和 t.auto = FALSE 这将允许使用原始系数来计算 t.stats 和 p。模型的值。

stargazer(My.model, align=TRUE, 
          type="text", apply.coef = exp, p.auto = FALSE, 
          t.auto = FALSE, digits = 3)


================================================
                         Dependent variable:    
                     ---------------------------
                                stop            
------------------------------------------------
rx                             0.583*           
                               (0.200)          
                                                
size                            0.947           
                               (0.070)          
                                                
number                        1.213***          
                               (0.046)          
                                                
------------------------------------------------
Observations                     340            
R2                              0.064           
Max. Possible R2                0.971           
Log Likelihood                -588.104          
Wald Test                12.510*** (df = 3)     
LR Test                  22.321*** (df = 3)     
Score (Logrank) Test     25.183*** (df = 3)     
================================================
Note: se in parenthesis *p<0.1; **p<0.05; ***p<0.01

此外，为了避免与您的读者混淆，您可以报告 t.stats 或 pvalues 而不是标准错误。

stargazer(My.model, align=TRUE, 
          type="text", apply.coef = exp, p.auto = FALSE, 
          t.auto = FALSE, digits = 3, report=('vc*p'))

================================================
                         Dependent variable:    
                     ---------------------------
                                stop            
------------------------------------------------
rx                             0.583*           
                              p = 0.070         
                                                
size                            0.947           
                              p = 0.535         
                                                
number                        1.213***          
                              p = 0.005         
                                                
------------------------------------------------
Observations                     340            
R2                              0.064           
Max. Possible R2                0.971           
Log Likelihood                -588.104          
Wald Test                12.510*** (df = 3)     
LR Test                  22.321*** (df = 3)     
Score (Logrank) Test     25.183*** (df = 3)     
================================================
Note:                *p<0.1; **p<0.05; ***p<0.01