It is best to use the generic extractor functions from the `StatsBase`

```
julia> m1 = fit(LinearMixedModel, @formula(Y ~ 1 + (1|G)), dat[:Dyestuff])
Linear mixed model fit by maximum likelihood
Formula: Y ~ 1 + (1 | G)
logLik -2 logLik AIC BIC
-163.66353 327.32706 333.32706 337.53065
Variance components:
Column Variance Std.Dev.
G (Intercept) 1388.3332 37.260344
Residual 2451.2500 49.510100
Number of obs: 30; levels of grouping factors: 6
Fixed-effects parameters:
Estimate Std.Error z value P(>|z|)
(Intercept) 1527.5 17.6946 86.326 <1e-99
julia> StatsBase.residuals(m1)
30-element Array{Float64,1}:
34.1282
-70.8718
-70.8718
9.12822
69.1282
12.1305
27.1305
-37.8695
32.1305
-32.8695
40.5253
-4.47467
50.5253
-44.4747
5.52533
-60.6986
-65.6986
89.3014
-40.6986
39.3014
13.9202
48.9202
-66.0798
53.9202
43.9202
34.9943
-30.0057
-35.0057
-5.00566
-40.0057
```

If you depend upon a field name by using, e.g., `lmm.resid`

, then everything falls apart when the internal representation changes, which, in my packages, it does frequently. My favorite Oscar Wilde quote is

Consistency is the last refuge of the unimaginative.

For the next release (not the one from earlier today), I’ll reexport the `residuals`

name so you don’t need to use `using StatsBase`

or `StatsBase.residuals`

.