# Posts tagged survival analysis

## Frailty and Survival Regression Models

- 26 November 2023

This notebook uses libraries that are not PyMC dependencies and therefore need to be installed specifically to run this notebook. Open the dropdown below for extra guidance.

## Reliability Statistics and Predictive Calibration

- 26 January 2023

Duplicate implicit target name: “reliability statistics and predictive calibration”.

## Reparameterizing the Weibull Accelerated Failure Time Model

- 17 January 2023

The previous example notebook on Bayesian parametric survival analysis introduced two different accelerated failure time (AFT) models: Weibull and log-linear. In this notebook, we present three different parameterizations of the Weibull AFT model.

## Bayesian Survival Analysis

- 17 January 2023

Survival analysis studies the distribution of the time to an event. Its applications span many fields across medicine, biology, engineering, and social science. This tutorial shows how to fit and analyze a Bayesian survival model in Python using PyMC.

## Censored Data Models

- 26 May 2022

This example notebook on Bayesian survival
analysis touches on the
point of censored data. *Censoring* is a form of missing-data problem, in which
observations greater than a certain threshold are clipped down to that
threshold, or observations less than a certain threshold are clipped up to that
threshold, or both. These are called right, left and interval censoring,
respectively. In this example notebook we consider interval censoring.