[R-sig-ME] Commonly observed error message in lmer

Daniel Ezra Johnson danielezrajohnson at gmail.com
Sat Dec 27 12:22:04 CET 2008

This error came up earlier in the year and Doug Bates wrote:

>This call is returning a warning about evaluation of the gradient at
>the initial values of the parameters.  I'm not sure if it then goes on
>to optimize the approximated deviance.

>If the approximated deviance is not being minimized for this model you
>may want to start with a simpler model, omitting some of the terms in
>the fixed effects.

Your fixed effects don't seem too complicated but there is a certain
inherent non-independence between ClutchSize and HO (hatching order).
For example if ClutchSize is 1 then HO must be 1. I wonder if that's
what's causing the problem?

Maybe you could try fitting separate models for each ClutchSize and
observe the HO effect separately (when ClutchSize > 1)?

You could also add a random slope as you said you wanted, that would
be done with a term (HO|NestID).

Hope this helps,

On Sat, Dec 27, 2008 at 2:39 AM, Luciano La Sala
<lucianolasala at yahoo.com.ar> wrote:
> Dear R-people,
> It's me again with, maybe, one more silly question for you. As a remainder, I am running version 2.7.1 on Windows Vista. I have small dataset which consists of:
> # NestID: nest indicator for each chicken. Siblings sharing the same nest have the same nest indicator.
> # Chick: chick indicator consisting of a unique ID for each single chick.
> # Year: 1, 2.
> # ClutchSize: 1-, 2- , 3-eggs.
> # HO: hatching order within each clutch (1, 2, 3 [first, second and third-hatched chick]).
> # SibComp: sibling competence: present/ absent (0, 1)
> # Death10: death at ten days post-hatch (0, 1)
> In order to account for lack of independence at the nest level (many chicks are nested in nest), I'd like to run a GLMM with random slopes and intercepts for nests.
> Using lmer, whenever I try to model two-way interaction like specified below:
> model1 <- lmer(Death10~HO*ClutchSize+(1|NestID),family=binomial,1)
> .... the following error message pops up:
> In mer_finalize(ans, verbose) : gr cannot be computed at initial par (65)
> 1. What does this error mean?
> I look forward to hearing from you soon!
> Best, Luciano
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