Mixed-effects Poisson regression
Shown in the app as mixed_poisson. Part of the method reference, under Mixed-effects models.
When to use
Count outcome with repeated or clustered measurements: rate ratios for predictors plus a per-cluster random intercept.
What you provide
- Outcome: one numeric column.
- Predictors: one or more columns.
- Cluster (subject or site): one column identifying the cluster.
You can also add a random slope: one numeric predictor whose effect is allowed to differ between clusters.
Options
Missing data
- Complete case (listwise deletion)
Multiple comparisons
- Not adjustable for this method. Where it makes post-hoc comparisons, the procedure applies its own correction.
Confidence level
Every interval in the result is reported at the level you choose:
- 90%
- 95%
- 99%
Related methods
Other methods under Mixed-effects models:
Guides that discuss this method
Worked examples
Celeus's result on a published or illustrative dataset, next to an independent computation and, where one exists, a published value. The data themselves are not reproduced here.
MASS::epil
- Source: Published dataset distributed with an R package
- Licence: MASS (GPL)
- Reference: Thall & Vail (1990), Biometrics 46; Breslow & Clayton (1993), JASA 88; the reference is lme4::glmer called directly (a wiring check)
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|---|---|---|---|
| Estimate | matches refit (not frozen) | (independent refit) | - | Yes |
| p-value | matches refit (not frozen) | (independent refit) | - | Yes |
| Confidence interval | matches refit (not frozen) | (independent refit) | - | Yes |
| Effect size confidence interval | matches refit (not frozen) | (independent refit) | - | Yes |
MASS::epil
- Source: Published dataset distributed with an R package
- Licence: MASS (GPL)
- Reference: Thall & Vail (1990), Biometrics 46; Breslow & Clayton (1993), JASA 88
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|---|---|---|---|
| Estimate | matches refit (not frozen) | (independent refit) | - | Yes |
| p-value | matches refit (not frozen) | (independent refit) | - | Yes |
References
- Laird, N. M., Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics 38: 963-974. doi:10.2307/2529876 doi:10.2307/2529876
- Bates, D., Machler, M., Bolker, B., Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67: 1-48. doi:10.18637/jss.v067.i01 doi:10.18637/jss.v067.i01