On Apr 20, 2010, at 7:31 PM, Noah Silverman wrote:

I just read the help page for predict.coxph.

It indicates that the risk score is just exp(lp)

What I'm trying to find, and have seen with some other implementations
is the "conditional probability within group".  Neither the lp or the
risk options seem to deliver this.

What am I missing?


I'm not sure that clogit lets you estimate that quantity:

http://tolstoy.newcastle.edu.au/R/help/06/02/21443.html

Do you have citations that back up your original assumption?

-- David,


-N


On 4/20/10 4:22 PM, Noah Silverman wrote:
Thanks David,

That explains a lot.  I appreciate it.

--
Noah


On 4/20/10 3:48 PM, David Winsemius wrote:

On Apr 20, 2010, at 5:59 PM, Noah Silverman wrote:


Hi,

I'm calculating a conditional logit on some data stratified by group. My understanding was that a conditional logit by definition returns a
value between 0 and 1 a a probability.  Can anyone suggest why I'm
seeing results outside of the {0,1} range??

Probably because you did not read the help page for the function
predict.coxph. Pay special attention to the type argument.

"type=c("lp", "risk", "expected", "terms")"


The call in R is:

m <- clogit(score ~ val_1 + val_2 + strata(group), data=data)

Then

prediction <- predict(m,newdata)

I do not see that you have defined any newdata.



A sample of the data with resulting predictive values is:
group score val_1 val_2 prediction
1  2009-01-04_1     1 0.5913962     -1.121589  1.62455210
2  2009-01-04_1     1 0.6175472     -3.249820 -0.20093346
3  2009-01-04_1     1 0.5439640     -2.424501  0.46651849
4  2009-01-04_1     0 0.3745209     -2.477424  0.31263855
5  2009-01-04_1     0 0.6329855     -3.424174 -0.34200448
6  2009-01-04_1     0 0.4571999     -2.770247  0.11190788
7  2009-01-04_1     0 0.3822623     -2.259422  0.50627534
8  2009-01-04_1     0 0.2605742     -4.424806 -1.44566070
9  2009-01-04_1     0 0.4449604     -2.357060  0.46174993
10 2009-01-04_1     0 0.6595178     -2.246518  0.69427842
11 2009-01-04_1     0 0.5260032     -2.977887 -0.02393871

By default (which is what you have implicitly chosen) you are
requesting "lp" = linear predictors rather than "risk".


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______________________________________________
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and provide commented, minimal, self-contained, reproducible code.

David Winsemius, MD
West Hartford, CT

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