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multilevel models
5 answered questions tagged “multilevel models”. Browse and search all answers, or ask your own.
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What does a singular fit mean in a mixed model?
A singular fit means a variance was estimated at zero or a correlation at ±1. Why it happens, what it changes, and what to do, with R and Python code.
Read the answer →REML or ML: which should a likelihood ratio test of fixed effects use?
Restricted likelihoods from models with different fixed effects cannot be compared. Why, what goes wrong, and the ML-then-REML workflow, with R and Python code.
Read the answer →Which interaction terms belong in a regression or mixed model?
Which terms must accompany a three-way interaction, whether the others are required, and how choosing interactions from the data inflates false positives.
Read the answer →How do you interpret the ICC when random effects are nested?
With readings nested in stations nested in sites, one model gives several ICCs. Which one answers which question, with R and Python examples.
Read the answer →Fixed vs random effects in mixed models: what is the difference?
A fixed effect is a parameter you estimate for its own sake; a random effect treats groups as a sample from a wider population. An example in R and Python.
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