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Metida.jl

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.

Install / Use

/learn @PharmCat/Metida.jl

README

Metida

This program comes with absolutely no warranty. No liability is accepted for any loss and risk to public health resulting from use of this software.

| Version | Citation | Code Coverage | Build ststus| Docs | |---------|----------|---------------|-------------|------| |version| |codecov |Tier 1 Aqua QA pkgeval| Latest docs Stable docs|

Metida.jl is Julia package for fitting mixed-effects models with flexible covariance structure.

Install:

import Pkg; Pkg.add("Metida")

Using:

using Metida, CSV, DataFrames, CategoricalArrays
df = CSV.File(joinpath(dirname(pathof(Metida)),"..","test","csv","df0.csv")) |> DataFrame
transform!(df, :subject => categorical, renamecols=false)
transform!(df, :period => categorical, renamecols=false)
transform!(df, :sequence => categorical, renamecols=false)
transform!(df, :formulation => categorical, renamecols=false)

lmm = LMM(@formula(var~sequence+period+formulation), df;
random = VarEffect(@covstr(formulation|subject), CSH),
repeated = VarEffect(@covstr(formulation|subject), DIAG),
)

fit!(lmm)

# Or you can use macro @lmmformula

lmm = LMM(@lmmformula(var~sequence+period+formulation,
    random = formulation|subject:CSH,
    repeated = formulation|subject:DIAG),
    df0)
fit!(lmm)

Also you can use this package with MatidaNLopt.jl and MetidaCu.jl.

See also MixedModels.jl: powerful package for mixed models.

Copyright © 2020 Metida Author: Vladimir Arnautov mail@pharmcat.net

View on GitHub
GitHub Stars29
CategoryDevelopment
Updated3mo ago
Forks0

Languages

Julia

Security Score

92/100

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