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indrajeetpatil.github.io | ||
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svmiller.com
Here is a how-to on bootstrapping standard errors in R in a flexible way, using some tidyverse-friendly packages like modelr and purrr. |
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easystats.github.io
You probably already have heard of the parameters package, a light-weight package to extract, compute and explore the parameters of statistical models using R (if not, there is a related publication introducing the package's main features). In this post, we like to introduce a new feature that facilitates nicely rendered output in markdown or HTML format (including PDFs). This allows you to easily create pretty tables of model summaries, for a large variety of models. |
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freerangestats.info
Stepwise variable selection is bad and dangerous, and you shouldn't do it. It increases false positives. It drops variables that should be in the model. It gives biased estimates for regression coefficients. The problems are worse for smaller samples; higher correlation between the X variables; and models with weaker explanatory power for the y (i.e. lower R-squared). |
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www.robertkubinec.com
Ordered beta regression can give you comparable, scale-free ATEs that can still be understood in the scale of the original data-all without using logs. |
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