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The QUANTLIFE procedure for survival analysis

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?

Survival analysis used to analyze time-to-event data
already had procs lifetes, lifereg & phreg
Lifereg is fine if you have IID errors – but what I’d you don’t . Enter quantile regression, possibly wearing a cape #Sasgf13 #noCape
Qy(tau) is the tau-th quantile of a random variable Y eg Qy(25) is 25th percentile
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

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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