Downloads

Exercise files, solution files, and Shiny app templates

How to Use These Files

  1. Right-click on the download link and select “Save link as…”
  2. Save the .qmd file to your workshop project folder
  3. Open the file in RStudio
  4. Run code chunks using the green play button (▶)

Exercise files contain tasks with blank spaces (___) for you to fill in. Solution files contain completed code with interpretations.

Day 1 — Decision Trees

Session 3: GDM Diagnostic Decision Tree

File Description
gdm-exercise.qmd Exercise: Modify prevalence, OGTT cost, DIPSI sensitivity, run sensitivity analysis
gdm-solution.qmd Solution: Completed tasks with interpretations
GDM-Screening-Model.xlsx Excel model: 3 screening strategies with all formulas (for cross-validation with R)
GDM-Worksheet.docx Pen-and-paper worksheet: Diagnostic tree concepts by hand (test accuracy, costs, QALYs, ICER, NMB)
gdm-rdecision-package.qmd Bonus: Same model built with rdecision package — includes PSA, CE plane, CEAC

Session 4: DES vs BMS Therapeutic Decision Tree

File Description
des-bms-exercise.qmd Exercise: Cross-validate R vs Excel, pre-regulation prices, restenosis scenarios, sensitivity analysis
des-bms-solution.qmd Solution: Completed tasks with interpretations
DES-vs-BMS-Decision-Tree-Model.xlsx Excel model: 4-sheet decision tree with all formulas (for cross-validation with R)
DES-BMS-Worksheet.docx Pen-and-paper worksheet: Decision tree concepts by hand (pathway counts, MACE, costs, ICER, NMB)
des-bms-rdecision-package.qmd Bonus: Same model built with rdecision package — includes tree drawing, tornado, PSA, CE plane, CEAC

Day 2 — Markov Model and PSA

Session 5: CKD 4-State Markov Model

File Description
ckd-exercise.qmd Exercise: Cross-validate R vs Excel, time horizon, treatment effect, dialysis cost, two-way sensitivity
ckd-solution.qmd Solution: Completed tasks with interpretations
CKD-Markov-Model.xlsx Excel model: Parameters, transition matrices, Markov trace, cost-effectiveness (for cross-validation with R)
Markov-Worksheet.docx Pen-and-paper worksheet: Markov modelling concepts by hand (transition matrix, matrix multiplication, HCC, ICER)
ckd-markov-heemod.qmd Bonus: Same model built with heemod package — includes built-in Markov trace, tornado DSA, PSA, CE plane, CEAC

Session 6: Probabilistic Sensitivity Analysis

File Description
psa-exercise.qmd Exercise: Iteration count, uncertainty propagation, EVPI
psa-solution.qmd Solution: Completed tasks with interpretations

Day 3 — Partitioned Survival and Shiny Apps

Session 8: Breast Cancer Partitioned Survival Model

File Description
breast-cancer-exercise.qmd Exercise: Time horizon, biosimilar pricing, 9-week regimen, distribution comparison
breast-cancer-solution.qmd Solution: Completed tasks with interpretations
Breast-Cancer-PSM.xlsx Excel model: Survival curves, state occupancy, cost-effectiveness with all formulas (for cross-validation with R)
PSM-Worksheet.docx Pen-and-paper worksheet: PSM concepts by hand (state occupancy, area-under-curve, ICER, NMB)

Session 9: PSA for the Breast Cancer Model

File Description
psa-psm-exercise.qmd Exercise: Cost uncertainty, probability of cost-effectiveness at multiple WTP thresholds
psa-psm-solution.qmd Solution: Completed tasks with interpretations

Shiny App Templates

These are standalone R Shiny applications. To run them:

  1. Download the app.R file into a folder
  2. Open it in RStudio
  3. Click “Run App” (or run shiny::runApp() in the console)
App Description
Diagnostic Tree app.R GDM screening: 3 strategies, NMB ranking, real tornado DSA, CE plane
Therapeutic Tree app.R DES vs BMS: cost breakdown, break-even analysis, NMB
Markov Model app.R CKD Markov: trace plots, tornado DSA, PSA with CE plane + CEAC
Partitioned Survival app.R Breast cancer PSM: Weibull survival, distribution comparison, NMB