Well spotted! This, it turns out, explains the fitting problems. I feel a bit foolish not noticing it myself.

I'm not sure if [gn]lmer should flag or ban duplicate measurements, as in principle they could be legitimate (though not in my case).

Many thanks,
Tim Cole
---
Tim.Cole@ucl.ac.uk<mailto:Tim.Cole@ucl.ac.uk> Phone +44(0)20 7905 2666 Fax +44(0)20 7905 2381
Centre for Paediatric Epidemiology and Biostatistics
UCL Institute of Child Health, London WC1N 1EH, UK

From: Emmanuel Curis <emmanuel.curis@parisdescartes.fr<mailto:emmanuel.curis@parisdescartes.fr>>
Date: Wednesday, 8 January 2014 05:46
To: Tim Cole <tim.cole@ucl.ac.uk<mailto:tim.cole@ucl.ac.uk>>
Cc: Ben Bolker <bbolker@gmail.com<mailto:bbolker@gmail.com>>, "r-sig-mixed-models@r-project.org<mailto:r-sig-mixed-models@r-project.org>" <r-sig-mixed-models@r-project.org<mailto:r-sig-mixed-models@r-project.org>>
Subject: Re: [R-sig-ME] R-sig-mixed-models Digest, Vol 85, Issue 6

Hi,

I'm not sure if this may be related or not to the issue, but in the
subset you sent you seem to have duplicate rows, differing only by
their row name (see for instance 3090 & 3697, 3156 & 3763). I guess
this is because some columns were removed, but could it be related to
the difficulties to fit, and the oddities of error occuring or not
according to the subset ?

Best regards,

On Tue, Jan 07, 2014 at 02:12:13PM +0000, Cole, Tim wrote:
Ť The dataset has 5048 records and 607 subjects. I've experimented with subsets of the data and it is rather complicated - I'll send you the data and code separately. The error message is simple to generate with a trivial dataset, restricted to subjects with 2 to 4 records and both 0 and 1 values for mat. But there is also a problem with subjects that have 10 records, though not 9 or 11 ? very odd.
Ť
Ť mat is a binary mature bone measure, which for each subject consists of zero or more 0s followed by zero or more 1s, the 0/1 transition providing useful information about the age of maturity.

Ť On 14-01-06 04:04 AM, Cole, Tim wrote:
Ť The dataset consists of longitudinal measures of bone score during
Ť puberty, where 1000 indicates maturity. The aim is to estimate median
Ť age at maturity in four groups by sex and ethnicity.
Ť This glm code works fine, but ignores the longitudinal element. lm2
Ť <- glm(I(RUSBoneScore == 1000) ~ log(DecAge) + Sex * Ethnicity,
Ť family=binomial, data=na.omit(bh[, 3:6]))
Ť This code, which adds a random subject effect, fails with the
Ť unhelpful error message below. lm3 <- glmer(I(RUSBoneScore == 1000) ~
Ť log(DecAge) + Sex * Ethnicity + (1 | BHID), family=binomial,
Ť data=na.omit(bh[, 2:6]))
Ť Error in pwrssUpdate(pp, resp, tolPwrss, GHrule(0L), compDev,
Ť verbose) : c++ exception (unknown reason)
Ť I've tried various alternatives but they all fail in the same way.
Ť Thoughts please.
Ť
Ť     Hard to say without a reproducible example. My main comment is that
Ť this is *not* a problem I have seen anyone report before.  sessionInfo()
Ť please?  Can you try with verbose=100? Can you make a reproducible
Ť example that is a reasonable size and doesn't have confidentiality problems?
Ť
Ť   Ben Bolker
Ť
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                                Emmanuel CURIS
                                emmanuel.curis@parisdescartes.fr<mailto:emmanuel.curis@parisdescartes.fr>

Page WWW: http://emmanuel.curis.online.fr/index.html



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