2 votes

Estimating risk ratio instead of odds ratio in mixed effect logistic regression in `R`

This is an older question, but might benefit from some newer approaches using marginaleffects. The difference here is that we use post estimation techniques to ...
Demetri Pananos's user avatar
1 vote

How to deal with this very nested data

Very interesting. Note that you also have nesting due to a session_n variable (in a way a time variable) It reminds me of the n:1 models and 1:1 models in time series regression (be aware quite some ...
Ggjj11's user avatar
  • 1,246
1 vote

Unreasonable estimate in mixed models with interaction terms

A linear model assumes a continuous and unbounded dependent variable. So, while your results are unreasonable, I think it's because of your model, rather than the interaction. If score is an integer, ...
Peter Flom's user avatar
  • 120k
1 vote

Unreasonable estimate in mixed models with interaction terms

With a limited set of ordered outcomes you need to use ordinal regression instead of least squares. Otherwise it’s all too easy to get model predictions outside the known limits, as you found. This ...
EdM's user avatar
  • 92.5k
1 vote
Accepted

Environmental variables explain hare weight - 80 traps in 4 zones where each trap caught unequal number of hares - Linear mixed effects model best?

You will want a linear mixed effect model. The lme4 and glmmTMB packages in R are fairly easy to use. It sounds like you have repeated measurements on tagged hares, multiple hares per trap, and you ...
N Brouwer's user avatar
  • 2,163

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