如何分别得到 lrm() 的结果？

Question

如何分别得到lrm()的结果？

我使用lrm()建立一个逻辑模型，得到的结果如下：

n <- 1000     # define sample size
y              <- rep(0:1, 500)
age            <- rnorm(n, 50, 10)
sex            <- factor(sample(c('female','male'), n,TRUE))

f <- lrm(y ~ age + sex, x=TRUE, y=TRUE)
f


                       Model Likelihood    Discrimination    Rank Discrim.    
                             Ratio Test           Indexes          Indexes    
 Obs          1000    LR chi2      1.50    R2       0.002    C       0.520    
  0            500    d.f.            2    g        0.088    Dxy     0.040    
  1            500    Pr(> chi2) 0.4714    gr       1.092    gamma   0.040    
 max |deriv| 2e-13                         gp       0.022    tau-a   0.020    
                                           Brier    0.250                     
 
           Coef    S.E.   Wald Z Pr(>|Z|)
 Intercept  0.2206 0.3370  0.65  0.5127  
 age       -0.0030 0.0065 -0.46  0.6485  
 sex=male  -0.1455 0.1266 -1.15  0.2504  

如何分别得到上面的结果作为data.frame？喜欢：

mydf$df1

                       Model Likelihood    Discrimination    Rank Discrim.    
                             Ratio Test           Indexes          Indexes    
 Obs          1000    LR chi2      1.50    R2       0.002    C       0.520    
  0            500    d.f.            2    g        0.088    Dxy     0.040    
  1            500    Pr(> chi2) 0.4714    gr       1.092    gamma   0.040    
 max |deriv| 2e-13                         gp       0.022    tau-a   0.020    
                                           Brier    0.250        

mydf$df2

           Coef    S.E.   Wald Z Pr(>|Z|)
 Intercept  0.2206 0.3370  0.65  0.5127  
 age       -0.0030 0.0065 -0.46  0.6485  
 sex=male  -0.1455 0.1266 -1.15  0.2504  

Answer 1

试试，

res = capture.output(print(f), append = F, sep = " ")
lapply(res, function(x) write.table(data.frame(x), 'res.csv'  , append= T, sep=',' ))