cl causes an error when passing weights variable

[S McIntyre]

Thanks for adding the cl parameter to mixed(), very nice! However, it seems to cause some problems when passing the ‘weights’ parameter. This causes an error, stopping immediately:

> mixed(F1 ~ cued + (1 + cued|pair),
+       family=binomial, weights=wt,
+       method='PB', args_test = list(nsim =10, cl = cl),
+       data = performance.expt2, cl = cl)
Fitting 2 (g)lmer() models.
Error in checkForRemoteErrors(val) : 
  2 nodes produced errors; first error: object 'wt' not found

Whereas this seems to run ok (albeit convergence warnings):

> mixed(F1 ~ cued + (1 + cued|pair),
+       family=binomial, weights=wt,
+       method='PB', args_test = list(nsim =10, cl = cl),
+       data = performance.expt2)
Fitting 2 (g)lmer() models:
[..]
Obtaining 1 p-values:
[.]
Warning messages:
1: In eval(family$initialize, rho) :
  non-integer #successes in a binomial glm!
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.0127221 (tol = 0.001, component 1)
3: In eval(family$initialize, rho) :
  non-integer #successes in a binomial glm!
4: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.00420134 (tol = 0.001, component 1)

Any idea what’s going on? (note, nsim=10 is just for troubleshooting)

• This topic was modified 3 years, 11 months ago by S McIntyre.

[henrik]

Sorry for the slow reply. Can you try using weights = performance.expt2$wt?

If this still gives an error you might have to export performance.expt2 to cl first: clusterExport(cl, "performance.expt2")

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