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Glen_b
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It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

f) The robust values

summcph$robscore

It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

f) The robust values

summcph$robscore
  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

f) The robust values

summcph$robscore

It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

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Glen_b
  • 290.4k
  • 37
  • 652
  • 1.1k

It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

f) The robust values

summcph$robscore
  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

It really helps if you post a reproducible example, rather than make us go find your data set in order to check we're doing all the options the same. For example, you didn't mention you had a cluster term. (It would take an extra few moments for you, and would have saved me ten minutes while I tried to figure out why I couldn't get the last couple of values. At the least you could have mentioned which example you ran in the help!)

  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest

f) The robust values

summcph$robscore
Source Link
Glen_b
  • 290.4k
  • 37
  • 652
  • 1.1k

  1. Put summary(coxphobject) into a variable

    summcph <- summary(coxphobject)

  2. examine it with str()

    str(summcph)

Values! Values everywhere!

so we find, (proceeding line by line in your above output):

a) the Concordance values

summcph$concordance

b) the Rsquare values

summcph$rsq

c) The Likelihood ratio test values

summcph$logtest

d) The Wald test values

summcph$waldtest 

e) The score test values

summcph$sctest