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TreeAge Pro 2020 is now available!
TreeAge Pro 2020 introduces Model Calibration among many other exciting new features. Click here to see the full list.
What’s new in TreeAge Pro?
A new version is released every January and July.
Calibration (TP 2020.1)
Partitioned Survival Analysis (TP 2019.2)
Get Started, Export Results to Excel (TP 2019.1)
Dynamic Cohort, Patient Interaction (TP 2018.1)
Simulation Patient/Cohort Tracking (TP 2017.2)
Convert Markov Models to Excel (TP 2017.1)
Training/Webinars
Check the current 2020 training schedule.
Attend a free webinar to become more familiar with key features of TreeAge Pro.
Download our free intro course materials as in intro to healthcare modeling.
Decision Analysis
Build models to study simple and complex problems to choose the best possible outcome. Our visual editor makes it easy to build and present models. Use TreeAge Pro for any decision, including in the industries of healthcare, law, oil/gas exploration, business and finance.
Advanced Modeling Features
Use sophisticated modeling techniques for complex decisions. TreeAge Pro supports Markov models, patient-level simulation (Microsimulation) models and time-to-event (DES) models using a consistent set of modeling and analysis tools.
Legal/Litigation Risk
Attorneys around the world use TreeAge Pro Business to build legal models to help determine legal strategy and assess risk.
Click here for more details.
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Calibration & More – TreeAge Pro 2020
January 13, 2020
The TreeAge Pro 2020, R1 Release is now available! This release is highlighted by the introduction of a Calibration Tool. New for TreeAge Pro Healthcare: Calibration Calibration allows you to automatically adjust model input values to match results to targets based on observed clinical data. The calibration process then adjusts the input values iteratively until […]
Read moreModel Calibration is now available!
We’ve added a Calibration Tool with the TreeAge Pro 2020 January release. Click here for a quick demo. It is critical that models mirror true disease progression and treatment effects as accurately as possible. Even after creating the appropriate patient pathways, it can be challenging to derive appropriate Markov transition probabilities to accurately represent clinical […]
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