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fharrell.com | ||
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aosmith.rbind.io
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| | | | | I walk through an example of simulating data from a binomial generalized linear mixed model with a logit link and then exploring estimates of over/underdispersion. | |
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isaacslavitt.com
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| | | | | [AI summary] The article discusses the German Tank Problem, a statistical estimation challenge where the goal is to infer the total number of tanks based on observed serial numbers, using Bayesian methods and MCMC libraries like Sampyl, PyMC3, and PyStan. | |
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www.rdatagen.net
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| | | | | We've finally reached the end of the road. This is the fifth and last post in a series building up to a Bayesian proportional hazards model for analyzing a stepped-wedge cluster-randomized trial. If you are just joining in, you may want to start at the beginning. The model presented here integrates non-linear time trends and cluster-specific random effects-elements we've previously explored in isolation. There's nothing fundamentally new in this post; it brings everything together. Given that the groundwork has already been laid, I'll keep the commentary brief and focus on providing the code. | |
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danieltakeshi.github.io
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| | | In my STAT 210A class, we frequently have to deal with the minimum of asequence of independent, identically distributed (IID) random variables. Thishappens b... | ||
