A developer introduces an experimental R package for fitting linear mixed models to complex survey data, detailing its current capabilities and limitations.
Explores using pairwise composite likelihood to fit mixed models when survey sampling and model random-effect structures differ, using genetic analysis as an example.
Debunks the myth that models can't have more parameters than data points, explaining how and when under-determined models can be solved and useful.
A tutorial on implementing Zero-Inflated Poisson models for complex survey data in R using the survey package.
A guide to visualizing and diagnosing Generalized Linear Mixed Models (GLMMs) in R, based on a presentation and blog post by Jaime Ashander.
Analyzes publication bias in scientific reporting using a humorous example of socks and Bayesian statistics.
A critique of common pitfalls and unproductive patterns in statistics research presentations, aimed at improving academic discourse.
Explores limitations of causal graph assumptions in statistical modeling, discussing when variables like poverty or diet may violate the faithfulness condition.
A technical talk on using the bbmle package in R to perform Maximum Likelihood Estimation for fitting mechanistic ecological models.
Scikit-learn and related Python libraries have students accepted for Google Summer of Code projects focused on performance and new features.
