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.

# Tag: stats

## Correlates of rock climbing ability

Here is my analysis of 'what correlates with how well someone climbs?'.

## Interaction analyses – How large a sample do I need? (part 3)

## Interaction analyses – Interpreting effect sizes (part 2)

## Interaction analyses – Power (part 1)

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).