An interactive workshop on deriving formulas to convert transition rates to probabilities for Markov models in R and Excel

David Epstein from the University of Grenada will be giving a two hour interactive workshop on deriving the correct formulas to calculate transition probabilities for Markov models in R and Excel.

Time and date: 1am-4pm, Tuesday 10th December 2019

Location: Worsley Building, room TBA

No registration is required, but participants are asked to bring a laptop and to pre-download a computer algebra system program called Maxima, available here: http://maxima.sourceforge.net/. Advanced knowledge of the mathematical background is not required.

Lunch: There will also be an opportunity afterwards to go to lunch with David Epstein from 12pm-1pm at Assembly Underground followed by  a workshop at 2pm.

More details:

For health-economic analyses that use multistate Markov models, it is often necessary to convert from transition rates to transition probabilities, and for probabilistic sensitivity analysis and other purposes it is useful to have explicit algebraic formulas for these conversions, to avoid having to resort to numerical methods. However, if there are four or more states then the formulas can be extremely complicated. These calculations can be made using packages such as R, but many analysts and other stakeholders still prefer to use spreadsheets for these decision models. We describe a procedure for deriving formulas that use intermediate variables so that each individual formula is reasonably simple. Once the formulas have been derived, the calculations can be performed in Excel or similar software. The procedure is illustrated by several examples and we discuss how to use a computer algebra system to assist with it. The procedure works in a wide variety of scenarios but cannot be employed when there are several backward transitions and the characteristic equation has no algebraic solution, or when the eigenvalues of the transition rate matrix are very close to each other.

The workshop is based on a paper, available here: https://journals.sagepub.com/doi/full/10.1177/0272989X17696997.

Slides for the workshop are available here: https://drive.google.com/a/york.ac.uk/file/d/0B8tloG87VME8UWd0SlBYd2hUTDg/view?usp=sharing.