# 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?

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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