Metida

Mixed Models

Metida.jl is a Julia package for fitting mixed-effects models with flexible covariance structure. At this moment package is in early development stage.

Main goal to make reproducible output corresponding to SAS/SPSS.

Now implemented covariance structures:

Scaled Identity (SI)
Variance Components / Diagonal (VC)
Autoregressive (AR)
Heterogeneous Autoregressive (ARH)
Compound Symmetry (CS)
Heterogeneous Compound Symmetry (CSH)

Usage:

LMM(model, data; subject = nothing, random = nothing, repeated = nothing)

where

model is a fixed-effect model (@formula), example: @formula(var ~ sequence + period + formulation)

random vector of random effects or single random effect. Effect can be declared like this: VarEffect(@covstr(formulation), CSH). @covstr is a effect model: @covstr(formulation). CSH is a CovarianceType structure. Premade constants: SI, VC, AR, ARH, CSH.

repeated is a repeated effect (only single).

subject is a block-diagonal factor.

Metida.lmm