using R for survival analysis

Thank you to all who made very helpful suggestions to get started with R.
Duncan Murdoch raised an excellent question, asking about my background and
reason for using R. I'm an epidemiologist, applying the marginal structural
models approach (inverse probability of treatment weights) in a Cox
proportional hazards analysis.

The statistical program which I had been using does not have functions for
doing a weighted Cox analysis.  Any advice pointing me in the direction of
resources to help probability-of-treatment-weighted Cox proportional
hazards would be most appreciated.

You can do IPW estimation with the coxph() function in the 'survival' 
package as long as you use the `robust=TRUE' option for standard errors.

The weights can be supplied as weights to coxph().

  You need to fit logistic regression models for treatment, with glm(), 
then use predict() to get probabilities of treatment (yes/no) then convert 
these into probability of observed treatment, then take the reciprocal to 
get the weights.

How messy this all is depends on the data structure -- how regular the 
observations of 'treatment' are, for example -- since this determines how 
many different logistic models for treatment you will need.

 	-thomas

Thomas Lumley			Assoc. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle