Calibrate Markov Models with Clinical Data
Calibrate Your Markov Models with Survival Tables
Coming January 2026
It can be difficult to build Markov models that accurately define disease progression.
TreeAge Pro can help by auto-calibrating your model based on clinical survival data.
Help us make calibration work for you!
We welcome your input as we develop the auto-calibration feature.
Click here if you are interested in previewing Calibration.
We will also preview this feature with webinars through the fall.
Calibration Webinar Video
Clinical Source Data – KM Survival Tables
You may want to create a Markov model that matches to clinical Kaplan-Meier survival tables.
Calibrate an Existing Model
Once you have created your model, use calibration to refine existing inputs to match the clinical data.
- Choose the inputs you want to refine.
- Select the survival tables and associate them with a Markov process and survival curve.
- Run the calibration and use the new inputs in the model.
- Validate the calibration with the Markov Plot.
- Further edit the model and re-calibrate.
TreeAge Pro’s calibration functions provide all the flexibility you need.
Auto-Calibrate a New Model
Create a new model that is auto-calibrated to survival tables.
- Create a new model with the Markov Model Wizard.
- Calibrate it to Kaplan-Meier tables.
- Validate the calibration in the Markov Plot.
