Apr
29
The QUANTLIFE procedure for survival analysis
April 29, 2013 | Leave a Comment
Trying this live blogging from SAS Global Forum again.
The title kind of says it PROC QUANTLIFE new procedure in SAS 9.3
Why DO we need a new procedure for survival analysis?
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Survival analysis used to analyze time-to-event data
already had procs lifetes, lifereg & phreg
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Lifereg is fine if you have IID errors – but what I’d you don’t . Enter quantile regression, possibly wearing a cape #Sasgf13 #noCape
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Qy(tau) is the tau-th quantile of a random variable Y eg Qy(25) is 25th percentile
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Quantile regression – can have same slope & different intercept for each value given for tau
Quantile regression, option 2 can have different slopes for each value of tau #Sasgf13
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Cumulative distribution function is the inverse of the quantile function #Sasgf13
QUANTLIFE example shows covariate that has negative effect for those with short life but positive effect for those with longer life #Sasgf13
Interested in survival analysis when covariates have non-linear relationship to time to event? Check the QUANTLIFE procedure paper #Sasgf13
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