TreeAge Pro Webinars

We are pleased to present a series of free webinars to help you become more familiar with key features of TreeAge Pro. Our experienced trainers will present these webinars as 30 minute online training sessions.

Scroll down this page to view recordings of past webinars.

We currently plan to deliver webinars on the following topics:

  • PSA: How confident can you be about your model conclusions (August 2018 – register below)
    – Models contain many assumptions about parameter values. Probabilistic Sensitivity Analysis (PSA) measures the impact of combined parameter uncertainty on model outcomes, allowing you to measure confidence in your conclusions.
    – Integrate parameter distributions into your model for PSA using TreeAge Pro’s built-in distribution builder.
    – Run PSA using TreeAge Pro’s built-in analyses and reports to examine parameter uncertainty in different ways.
  • DES: Build Discrete Event Simulation models in TreeAge Pro (September 2018 – register below)
    – Compare and contrast Markov and DES models in TreeAge Pro.
    – Examine the important elements of DES models including time-to-event distributions, accumulating cost and utility over time, and other considerations.

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Webinar Registration


Past Webinar Recordings

The webinars were recorded live with no subsequent editing. Please forgive any mistakes made during the presentations.

  • COMING SOON! Sensitivity Analysis: What if your parameter assumptions are wrong?
    – Use univariate sensitivity analysis tools for model validation. Examine how parameter uncertainty affects your model outputs. Could this change your strategy recommendation?
    – Create Tornado diagrams to examine the relative effect of individual parameter uncertainties on your model.
  • Debugging TreeAge Pro Models – published from recording on 2018/02/20
    – Configure your model to review internal calculations behind model analyses.
  • Infectious Disease Modeling – published from recording on 2018/03/15.
    – Make cohort transition probabilities dependent on how the overall cohort is distributed among the Health States.
    – Use a full cohort size rather than fractions of a cohort of size 1.
    – Add to the cohort size with time.
  • Validate Your Model by Reviewing Patient Flows in Markov Models – published from recording on 2018/04/05
    – Examine how your cohort moves through health states and transitions via Markov Reporting.
    – See how cost and eff values are accumulated within the context of the cohort movement.
  • Patient Interaction with a Limited Resource – published from recording on 2018/05/10
    – Run patients through your model at the same time to facilitate patient interaction (Parallel Trials).
    – Manage patient competition for limited resources – manage resource usage and release (Stop Nodes).
    – Manage the overall model environment by storing global data accessible to all patients (Global Trackers)
  • Review Patient Pathways in a Patient Simulation Model – published from recording on 2018/06/07
    – Review every event in each patient’s disease progression including when/how cost and effectiveness was accumulated.
    – Review patient pathways with aggregated cohort-level reports to study and validate patient flows.