[R-sig-ME] Random slope with npmlreg

[Shige Song]

Dear All,

I am trying to estimate a mixed effect model with random slope with
npmlreg. To make my question clear, I use the sample data set that was
used in the vignettes (as part of the package "nlme").

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> vc2 <- allvc(height ~ age, random=~age|Subject, data=Oxboys, random.distribution="np", k=3)
1 ..2 ..3 ..4 ..5 ..6 ..7 ..8 ..9 ..10 .. EM algorithm met convergence
criteria at iteration # 10 Disparity trend plotted.
EM Trajectories plotted.

> summary(vc2)

Call: allvc(formula = height ~ age, random = ~age | Subject, data =
Oxboys, k = 3, random.distribution = "np")

Coefficients:

            Estimate Std. Error    t value
age         7.919030  0.4065465  19.478782
MASS1     138.588240  0.2827517 490.141113
MASS2     149.249701  0.1921859 776.590184
MASS3     158.909797  0.2627202 604.863195

MASS1:age -2.350977 0.5966915 -3.940021 MASS2:age -1.701525 0.5034540 -3.379703

Mixture proportions:

    MASS1 MASS2 MASS3
0.2313332 0.5007243 0.2679425

Component distribution - MLE of sigma:	   3.586
Random effect distribution - standard deviation:	   7.161265

-2 log L:	    1315     Convergence at iteration  10
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My question is: how do I interpret the random slope coefficients
"age", "MASS1:age", and "MASS2:age"? Does it mean that the effect of
age is 7.919030 in the third component, -2.350977 in the first
component, and -1.701525 in the second, or something else?

Many thanks.

Best,
Shige