Fit Parametric Survival

Fit Survival Data Using Regression Models

Survival times can be expressed as a function of one or more variables. When this is the case, use a regression platform that fits a linear regression model while taking into account the survival distribution and censoring. The Fit Parametric Survival platform fits the time to event Y (with censoring) using linear regression models that can involve both location and scale effects. The fit is performed using the Weibull, lognormal, exponential, Fréchet, loglogistic, SEV, normal, LEV, and logistic distributions.

Note: The Fit Parametric Survival platform is a slightly customized version of the Fit Model platform. You can also fit parametric survival models using the Nonlinear platform.

Figure 14.1 Example of a Parametric Survival Fit 

Contents

Overview of the Fit Parametric Survival Platform

Example of Parametric Regression Survival Fitting

Launch the Fit Parametric Survival Platform

The Parametric Survival Fit Report

The Parametric Survival - All Distributions Report

Parametric Competing Cause Report

Fit Parametric Survival Options

Nonlinear Parametric Survival Models

Additional Examples of Fitting Parametric Survival

Arrhenius Accelerated Failure LogNormal Model

Interval-Censored Accelerated Failure Time Model

Analyze Censored Data Using the Nonlinear Platform

Left-Censored Data

Weibull Loss Function Using the Nonlinear Platform

Fitting Simple Survival Distributions Using the Nonlinear Platform

Statistical Details for the Fit Parametric Survival Platform

Loss Formulas for Survival Distributions