ICI3D R tutorials and labs
Seventh annual Clinic on Meaningful Modeling of Epidemiological Data
African Institute for Mathematical Sciences, Muizenberg, Cape Town, South Africa
May 30 - June 10, 2016
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- Tutorial 0: Introduction to R Studio - provides an introduction to the user interface (required)
- Tutorial 1: Introduction to R and its quirks (required)
- Tutorial 2: More on Vectors, Data Frames, and Functions (required)
- Tutorial 3: Probability Distributions and Control Structures (required)
- Tutorial 4: Visualizing Infectious Disease Data in R (recommended)
- Tutorial 5: Data cleaning and management in R (recommended)
- Lab 1: ODE models in R (required)
- Lab 2: Consequences of heterogeneity (required)
- Lab 3: Study Design in Epidemiology lab (recommended for Track A)
- Lab 4: Study Design for Clinical Trials (recommended for Track A)
- Lab 5: Introduction to Likelihood (required)
- Lab 6: MLE fitting of a dynamic model (required)
- Lab 7: MCMC fitting of a binomial distribution (required)
- Lab 8: MCMC fitting of a dynamic model (optional)
- Note: Download this file to avoid having to wait for long MCMC chains to be sampled.
- Participatory Coding (Dynamic Modeling) 2016 - How does diabetes prevalence affect active TB prevalence (or incidence)?
- Participatory Coding (Sampling Var & Study Desin) 2016 - Does recent travel affect prevalence of active TB amongst an immigrant population?
- Participatory Coding 2015 - Does HIV status affect TB incidence rate?
- Participatory Coding 2015 - Can XDR TB invade a population (didn’t get to XDR yet, but have a working TB model with treatment)
- Stochastic SIR Example - Gillespie Algorithm
- Stochastic SIR Example - Chain Binomial
- More to be added