galamm-heteroscedastic.md
In galamm: Generalized Additive Latent and Mixed Models

Heteroscedastic model works

Code
  print(summary(mod), digits = 3)
Output
  GALAMM fit by maximum marginal likelihood.
  Formula: y ~ x + (1 | id)
     Data: hsced
  Weights: ~(1 | item)

       AIC      BIC   logLik deviance df.resid 
    4126.3   4151.7  -2058.1   4116.3     1195

  Scaled residuals: 
     Min     1Q Median     3Q    Max 
  -5.654 -0.711  0.029  0.683  4.326

  Random effects:
   Groups   Name        Variance Std.Dev.
   id       (Intercept) 0.988    0.994   
   Residual             0.960    0.980   
  Number of obs: 1200, groups:  id, 200

  Variance function:
     1    2 
  1.00 1.99

  Fixed effects:
              Estimate Std. Error t value Pr(>|t|)
  (Intercept)    0.129     0.0992    1.30 1.94e-01
  x              0.706     0.1213    5.82 5.82e-09