# Tutorial: Visualising statistical uncertainty using model-based graphs

R

graphs

logistic regression

mixed-effects models

multiple regression

Bayesian statistics

brms

I wrote a tutorial about visualising the statistical uncertainty in statistical models for a conference that took place a couple of months ago, and I’ve just realised that I’ve never advertised this tutorial in this blog. You can find the tutorial here: Visualising statistical uncertainty using model-based graphs.

Contents:

- Why plot models, and why visualise uncertainty?
- The principle: An example with simple linear regression
- Step 1: Fit the model
- Step 2: Compute the conditional means and confidence intervals
- Step 3: Plot!

- Predictions about individual cases vs. conditional means
- More examples
- Several continuous predictors
- Dealing with categorical predictors
- t-tests are models, too
- Dealing with interactions
- Ordinary logistic regression
- Mixed-effects models
- Logistic mixed effects models

- Caveats
- Other things may not be equal
- Your model may be misspecified
- Other models may yield different pictures