Multilevel Models and Causal Dilemmas
The often-overlooked assumption in random effects models that can invalidate your causal conclusions.
Recent posts
Models with memories: The Beauty of Multilevel Models
Coding memory into machines might just be the best thing you do this weekend.
Simulating the Distribution of P-Values
Simulating p-values helps in study design, significance testing, and controlling false discoveries. See how they behave in different scenarios!
Maximizing performance through incentives when volunteers vary
Varying Intercept and Slope Model with a Covarying Structure
Rate of an Event Analysis
Terrors of Censoring
How Randomization Magically Works ..
We’re going to use simulation to explore randomization. This is how engineers came to understand statistics
Beta-Binomial Model and Multilevel Binomial Model: A Comparison
A moment of realization when the Beta-Binomial Model and the Multilevel Binomial Model produces similar estimates
Probability Theory Meets Survey Data
Sometimes you really wonder where examples like the Monty Hall problem are actually used.
Quantifying the Idea of Updating beliefs
Everyone has their go-to example to explain Bayesian Statistics. Mine’s just a bit… scary!