In `R`

package `lme4`

, the function `coef`

seems to return slopes for each level of the factor, but in Julia `coef`

returns only fixed effects. (see https://stats.stackexchange.com/questions/122009/extracting-slopes-for-cases-from-a-mixed-effects-model-lme4).

Is there a way to get the individual slopes like in R?

```
using RData, MixedModels
const dat = Dict(Symbol(k)=>v for (k,v) in
load(joinpath(dirname(pathof(MixedModels)), "..", "test", "dat.rda")));
sleepstudy = deepcopy(dat[:sleepstudy])
names!(sleepstudy, [:Reaction, :Days, :Subject])
fm1 = fit(LinearMixedModel, @formula(Reaction ~ Days + (Days|Subject)), sleepstudy)
coef(fm1)
# 2-element Array{Float64,1}:
# 251.40510484848375
# 10.467285959596053
```