Reliability and Survival Methods > Fit Parametric Survival
Publication date: 08/13/2020

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, smallest extreme value (SEV), normal, largest extreme value (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
Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).
.