[R-sig-ME] clmm2() thresholds - forcing symmetry around zero
rune.haubo at gmail.com
Mon Dec 12 08:38:48 CET 2016
It seems that you are looking for clmm(...., threshold="symmetric2").
This threshold argument is valid for clmm, but apparently I forgot to
document it for clmm, so take a look at help(clm) instead.
> fmm1 <- clmm(rating ~ temp + contact + (1|judge), data=wine,
'log Lik.' -89.97856 (df=5)
If you want to fix one or more parameters while optimizing the rest,
you will have to use fmm2 <- clmm( ...., doFit=FALSE). fmm2 is a
'model environment' which you can optimize, e.g. using, say nlminb or
> fmm2 <- clmm(rating ~ temp + contact + (1|judge), data=wine,
+ threshold="symmetric2", doFit=FALSE)
> obj.fun <- ordinal:::getNLA.ssr # objective function: negative Laplace log-likelihood
> fit <- ucminf(fmm2$par, function(par) obj.fun(fmm2, par))
Fixing one or more parameters means modifying 'function(par)
obj.fun(fmm2, par)' to only optimize over select parameters.
On 7 December 2016 at 04:08, Kristin Precoda <kristin.precoda at mq.edu.au> wrote:
> I'm using clmm2() to fit a model with three possible response categories (win, tie, lose). For the particular problem, the thresholds need to be symmetric around zero, so win|tie = -1 * tie|lose. Is there a way either to force the thresholds to be symmetric around zero, or to just set the thresholds (for example, to -1 and +1) and not optimize them?
> Thanks very much,
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