Reputation: 187
I working on survival analysis and each time I use a different test set and at the end I would like to have the avg of coefficients, p for each feature and p value of the model. I can get coefficients using srFit$coefficients. But I don't know how to get the p values, although I can see them using summary(srFit).
summary(srFit)
Call:
survreg(formula = Surv(time) ~ f1 + f2 + f3 + f4 + f5 + f6 + f7 + f8 + f9 + f10, data = train, dist = dist_pred[i_dist])
Value Std. Error z p
(Intercept) 1.59e+03 632.0632 2.5092 1.21e-02
f1 -2.07e+00 1.2283 -1.6881 9.14e-02
f2 1.03e+00 1.8070 0.5677 5.70e-01
f3 -7.61e-02 1.3764 -0.0553 9.56e-01
f4 -3.24e+00 1.4836 -2.1843 2.89e-02
f5 4.37e-01 0.0961 4.5474 5.43e-06
f6 -1.36e+00 0.7555 -1.8011 7.17e-02
f7 -6.26e-03 0.0081 -0.7719 4.40e-01
f8 3.92e-03 0.0186 0.2111 8.33e-01
f9 -4.82e-01 0.4291 -1.1235 2.61e-01
f10 -7.79e-01 0.3139 -2.4809 1.31e-02
Log(scale) 2.73e+00 0.0314 86.9447 0.00e+00
Scale= 15.4
Student-t distribution: parmameters= 4
Loglik(model)= -4542.1 Loglik(intercept only)= -4570.1
Chisq= 56 on 10 degrees of freedom, p= 2.1e-08
Number of Newton-Raphson Iterations: 5
n= 1008
Upvotes: 0
Views: 1793
Reputation: 829
You can extract the p-values from the table in the summary
s = summary(srFit)
s$table
s$table[,4]
Upvotes: 1
Reputation: 71
You can examine the statistic names of Summary object using names(summary(srFit))
, then extract the statistic you want:
summary(srFit)$statistic_name_here
.
If the statistic you want is a table like in your case, you can extract it into a data.frame
for eg.
df=data.frame(summary(srFit)$statistic_name_here)
df$your_column_name
will give you what you want.
Upvotes: 1