Clustered data - such as multiple observations per individual, animal, or cell - are quite common in neuroscience research. Here I walk through an introduction to one approach to adjusting your analyses for clustering - block permutations and bootstrapping - that is widely applicable and makes very few assumptions.
Here is my analysis of 'what correlates with how well someone climbs?'.
In this series I try to convey a couple of insights about power for interactions in linear regressions. First, how to do a power analysis for a interaction in a linear regression (this post), then interpreting the effect size of a interaction (part 2), and finally thinking about how large (or small) an effect size it is reasonable to plan for (part 3).
Elizabeth Urey Baranger (born Gertrude Elizabeth Urey) (09/18/1927 - 05/30/2019) was an American theoretical physicist and senior administrator at the University of Pittsburgh.
We managed to secure postdoc positions in the same city, and were able to move there together! Here are a handful of things we did that we think helped us pull this off.
In my first post I showed how to build a simple model, using only genetic information, that predicts height, with 53% accuracy in an independent sample. In this post I’m going to improve that model, which will ultimately result in a model with 64% accuracy in an independent sample - an 11% improvement!