Reliability and Survival Methods > Fit Parametric Survival
Publication date: 07/08/2024

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, fit a linear regression model that takes 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 15.1 Example of a Parametric Survival Fit 

Example of a Parametric Survival Fit

Contents

Overview of the Fit Parametric Survival Platform

Example of the Fit Parametric Survival Platform

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

Example of an Arrhenius Accelerated Failure Lognormal Model
Example of an Interval-Censored Accelerated Failure Time Model
Example of Analyzing Left-Censored Data

Statistical Details for the Fit Parametric Survival Platform

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).