# Random effect MixedModels
**URL:** https://discourse.julialang.org/t/random-effect-mixedmodels/12120
**Category:** General Usage
**Tags:** question
**Created:** [July 3, 2018, 5:54am UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120 "2018-07-03T05:54:45Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@ktsiamasiotis](https://discourse.julialang.org/u/ktsiamasiotis)
#### Post date: [July 3, 2018, 5:54am UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/1 "2018-07-03T05:54:45Z")
Hi,
I used MixedModels package a couple of times in the past as a faster alternative to R’s lmer. Recently I downloaded latest official Julia version (0.6.3) and tried with some datasets. I compared the results with old MixedModels and Julia version, and I found that random effects are not matching at all (using ranef(lmeModel, named=true)). Digging little deeper i managed to match them using the following snippet:
randomEff = transpose(ranef(lmeModel, named=true)[1])
rows, columns = names(randomEff)
randomDF = DataFrame(randomEff)
names!(randomEff.colindex, map(parse, columns))
randomEff[:store] = unique(lmeModel.trms[1].f)
dfCols = randomEff.colindex.names
randomEff = stack(randomEff,dfCols[1:end-1], :store)
Now random effects appear very close to old results.
The question is: Am I doing something wrong or there is an issue with random effects in new version?
Please note that I have very little experience with Julia.
---
### Author:  [@dmbates](https://discourse.julialang.org/u/dmbates)
#### Post date: [July 3, 2018, 2:32pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/2 "2018-07-03T14:32:18Z")
This is [https://github.com/dmbates/MixedModels.jl/issues/130](https://github.com/dmbates/MixedModels.jl/issues/130) which I hope to address today.
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### Author:  [@dmbates](https://discourse.julialang.org/u/dmbates)
#### Post date: [July 3, 2018, 5:01pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/3 "2018-07-03T17:01:03Z")
I am having difficulty reproducing the problem and would appreciate a reproducible example. Either I have somehow introduced a reordering or I misunderstand the relationship between the `refs` and the `levels` of a `CategoricalArray`.
I may need help from @nalimilan if it is a misunderstanding of the innards of the `CategoricalArrays` package. For some reason I am still confused by the documentation and the code in that package. The fact that this hinges on the order of `unique(lmeModel.trms[1].f)` is very, very strange to me.
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### Author:  [@nalimilan](https://discourse.julialang.org/u/nalimilan)
#### Post date: [July 3, 2018, 5:37pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/4 "2018-07-03T17:37:25Z")
I guess that’s due to the fact that you use `refs` as if its values corresponded to the order in which levels are presented, while it actually refers to the internal order of the levels (`index`). You need to use `CategoricalArrays.order(x.pool)[x.refs]` to get codes corresponding to user-visible ordering of levels.
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### Author:  [@dmbates](https://discourse.julialang.org/u/dmbates)
#### Post date: [July 3, 2018, 5:55pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/5 "2018-07-03T17:55:38Z")
Okay, thanks.
I must admit that I find that nomenclature highly unintuitive. To me it is axiomatic that for categorical data the relationship
```julia
levels(f)[f.refs] == f
```
should hold.
Would you be willing to redefine the result of `levels(f)` so that this relationship does hold? Right now I don’t understand what the purpose of having a `levels` function is if the result cannot be indexed by the refs.
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### Author:  [@dmbates](https://discourse.julialang.org/u/dmbates)
#### Post date: [July 3, 2018, 6:05pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/6 "2018-07-03T18:05:18Z")
Alternatively, would you be willing to add another extractor function, say `reflevels`, that provides the levels that can be indexed by the `refs`? I don’t object to having internal representations that allows for fast reordering, etc. In my application I want to work with the `refs` vector because the, potentially very large, model matrices for the random effects are generated from indicators of the `refs`. So really this problem for me is comparatively minor if I can just find out how to label the indicator columns.
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### Author:  [@nalimilan](https://discourse.julialang.org/u/nalimilan)
#### Post date: [July 3, 2018, 6:12pm UTC](https://discourse.julialang.org/t/random-effect-mixedmodels/12120/7 "2018-07-03T18:12:14Z")
Yeah, I know it’s somewhat confusing. The point of this level of indirection is that things like `CategoricalArray(["c", "b", "a"])` can be coded on the fly without resetting all the `refs` at the end, once we realize that `levels(x) == ["a", "b", "c"]` doesn’t match the order of appearance (which is used for `refs` since we cannot know the order beforehand). It also allows changing the order of levels without modifying the underlying data.
The purpose `levels` is to return the levels in the order the user wants to see them. What you seem to be interested in is rather the internal order of levels, which is ` CategoricalArrays.index(x.pool)`. You can always rely on the property that `CategoricalArrays.index(x.pool)[x.refs] == x`.
EDIT: I’ve added a warning in the CategoricalArrays manual: [https://github.com/JuliaData/CategoricalArrays.jl/pull/152](https://github.com/JuliaData/CategoricalArrays.jl/pull/152)