You don’t need to know the details of causal inference and causal frameworks to make a quick evaluation of a causal claim, and how much stock you should put in its veracity.
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One of the best parts about being a professor is thinking and writing for a living, and we can improve both skills with commitment and practice!
It’s helpful to remember the formula for trivial insights when reading a paper.
One of the best parts of Bayesian inference is useful predicted probabilities of an outcome—here is an example using rstanarm and data from a two-by-two experimental design
It takes three necessary things to establish a causal relationship.
A very brief primer on null hypothesis testing
A little bit about p-hacking, HARKing, and multiple comparisons
Tidying the website
Looking at whether businesses in wealthier areas have a higher survivability rate using Bayesian multilevel modeling
Taking a look at multilevel modeling from an economics perspective, and then from a psychology perspective