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Design and Analysis of Simulation Studies - Online Course

A 4-Day Livestream Seminar Taught by

Ashley Naimi
Course Dates:

Monday, May 20 –
Thursday, May 23, 2024

Schedule: All sessions are held live via Zoom. All times are ET (New York time).

10:30am-12:30pm (convert to your local time)
1:30pm-3:00pm

Watch Sample Video

This course will focus on how to use experimental principles to appropriately design and analyze Monte Carlo simulation studies. Simulations are extremely flexible, and consequently are invaluable tools for understanding and applying a staggering range of methodologies. They are particularly useful for determining how methods will perform in the (all-too-typical) case when data analytic conditions differ from textbook-perfect ideals.

For example, simulations can be used to deepen understanding of often misunderstood concepts such as confidence intervals and hypothesis testing, to plan studies by comparing sampling strategies or running power analyses, to guide analyses by determining how well methods perform when their underlying assumptions are violated, and to assess robustness of results to threats ranging from unobserved confounding to choices about how data are coded and modeled.

Figure 1. Simulation example of 95% confidence interval coverage, which can be used to understand how to better interpret them, and avoid falling in common traps such as treating confidence intervals as Bayesian credible intervals.

Figure 2. True (red) and estimated (blue) distribution of exposure effect point estimates under non-differential exposure measurement error, and non-differential exposure + confounder measurement error leading to away from the null bias.

This course will teach participants how to plan, conduct, and interpret simulation studies. Particular attention will be paid to key tasks including choosing an appropriate Monte Carlo sample size; managing computation time; applying a relevant data-generating mechanism using causal inference principles (via, e.g., DAGs); and efficiently analyzing simulated data. The course will conclude with a discussion of when more complex simulation designs are warranted, such as “plasmode” simulations or synthetic simulation (via variational autoencoders or generative adversarial networks).

Starting May 20, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.

Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

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“The instructor explained complex ideas, provided us with extensive computer programs, and interpreted outputs."

“The instructor is passionate; he explained complex ideas, provided us with extensive computer programs, and interpreted outputs. He also had excellent time management!” 

Towhid Islam

University of Guelph 

“Dr. Naimi is a great teacher!"

“Dr. Naimi is a great teacher! He is very experienced and thorough.” 

Josh Thorpe

University of North Carolina - Chapel Hill