Monte Carlo Simulation Reading List

(Asterisks indicated “must reads”!)

Articles

  1. *Morris, Tim P., Ian R. White, and Michael J. Crowther. “Using simulation studies to evaluate statistical methods.” Statistics in medicine 38.11 (2019): 2074-2102.

  2. *Maldonado, George, and Sander Greenland. “The importance of critically interpreting simulation studies.” Epidemiology (1997): 453-456.

  3. Rudolph, Jacqueline E., Matthew P. Fox, and Ashley I. Naimi. “Simulation as a Tool for Teaching and Learning Epidemiologic Methods.” American Journal of Epidemiology 190.5 (2021): 900-907.

  4. Burton A, Altman DG, Royston P, Holder RL. The design of simulation studies in medical statistics. Stat Med. 2006;25(24):4279-4292. doi:10.1002/sim.2673

  5. Mooney, C. “Conveying truth with the artificial: using simulated data to teach statistics in social sciences.” SocInfo Journal 1.Part 7 (1995): 1-5.

  6. Hodgson, Ted, and Maurice Burke. “On simulation and the teaching of statistics.” Teaching Statistics 22.3 (2000): 91-96.

Notes

Notes from a Stats course at NC State. Among other things, useful equations for calculating simulation error, and other estimands:

  1. NCSU Notes

Notes from a short lecture at Emory on introduction to simulation:

  1. Emory Notes

Books

Technical and challenging to read (for non-math/stats), but chapters 1-3 have been very useful to me:

  1. Casella, George, and Christian P. Robert. “Monte Carlo Statistical Methods.” (1999). Springer. New York, NY.