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Mixed Models
MixedModels.jl fits statistical mixed effects models using the Julia programming language.

About Mixed Models
MixedModels.jl is a Julia package for fitting statistical mixed-effects models. It provides LinearMixedModel for linear models and GeneralizedLinearMixedModel for models where the conditional mean relates to the linear predictor through a link function, including Bernoulli for binary data and Poisson for count data.
Users build models with formulas, fit them with fit and fit!, and query fitted models for results such as likelihood and variance components. Use requires Julia, and version 5.0.0 removed constrained optimization support and multithreading options for the bootstrap.
Key features
- Fits linear mixed models with LinearMixedModel type
- Fits generalized linear mixed models with link functions
- Defines fixed effects and grouped random effects using formulas
- Builds, fits, and queries models via statistical model API
- Handles Bernoulli responses for binary data and Poisson for counts
- Keeps fit log as Tables.jl-compatible column table
- Supports both linear and generalized linear mixed-effects models
- Uses formula syntax with fit, fit!, and query functions for fitted models
- Tested on Linux, macOS, and Windows with specified Julia versions
- Requires Julia rather than working as a standalone program
- Version 5.0 removed support for constrained optimization
- Version 5.0 removed multithreading options for the bootstrap
Mixed Models at a glance
- Category
- Development › Programming Languages
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Mixed Models FAQ
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