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Today's Topics:
1. Re: Error message (Luciano La Sala)
2. Re: Error message (Ben Bolker)
3. Re: subject level predictions with lme4 from incomplete
longitudinal profile (Tarca, Adi)
4. Re: Error message (Ken Beath)
----------------------------------------------------------------------
Message: 1
Date: Wed, 05 Nov 2014 08:55:27 -0300
From: Luciano La Sala <lucianolasala at yahoo.com.ar>
To: Daniel Wright <Daniel.Wright at act.org>
Cc: "r-sig-mixed-models at r-project.org"
<r-sig-mixed-models at r-project.org>
Subject: Re: [R-sig-ME] Error message
Message-ID: <545A102F.3030407 at yahoo.com.ar>
Content-Type: text/plain; charset="UTF-8"
Thank you Dan,
According to the new version of lme4 I refited my model as follows:
model <- glmer(Death ~ Year + Sex + Egg Volume + Hatch Order + (1|Nest
ID), family = binomial, data = Data)
summary(model)
However, the same error message keeps showing up:
Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate
Interestingly, if I reduce the model to contain only one main effect
(whichever), say Hatch_Order, things look better:
model2 <- glmer(Death 2 ~ Hatch Order + (1|Nest_ID), family = binomial,
data = Data) summary(model2)
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) ['glmerMod']
Family: binomial ( logit )
Formula: Death_2 ~ Hatch_Order + (1 | Nest_ID)
Data: surv.2
AIC BIC logLik deviance df.resid
118.5 131.8 -55.2 110.5 205
Scaled residuals:
Min 1Q Median 3Q Max
-0.7390 -0.1714 -0.1682 -0.1506 3.7689
Random effects:
Groups Name Variance Std.Dev.
Nest_ID (Intercept) 1.586 1.259
Number of obs: 209, groups: Nest ID, 115
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.4824 1.1274 -3.089 0.00201 **
Hatch_OrderSecond -0.1266 0.7576 -0.167 0.86729
Hatch_OrderThird 2.0486 0.7572 2.705 0.00682 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Htc_OS
Htch_OrdrSc -0.111
Htch_OrdrTh -0.709 0.276
Any pointers please? Best. Luciano
El 10/22/2014 6:35 PM, Daniel Wright escribi? The lme4 package has
changed some. Details are inhttp://arxiv.org/pdf/1406.5823.pdf
For your problem, the first thing to note is glmer is now used instead
of lmer for generalized linear models. Glancing at your model the other
bits look like they should work.
Dan
Daniel B. Wright, Ph.D.
Statistical Research Division
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-----Original Message-----
From:r-sig-mixed-models-bounces at r-project.org [mailto:
r-sig-mixed-models-bounces at r-project.org] On Behalf Of Luciano La Sala
Sent: Wednesday, October 22, 2014 4:20 PM
Cc:r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Error message
Hello,
A few years back I used to fit GLMM (binomial response) using lmer
function in lme4. Back then I had to specify the family of response
variable (dead /alive) as binomial. Now I have to refit those models using
quite newer versions of both R (R x64 3.1.1) and lme4 (lme4_1.1-7), but
things seem to have changed quite a bit.
My response variable is death (yes/no), and independent variables are
Year (2006 / 2007), Sex (M / F), Egg volume (continuous), and Hatching
Order (ordered factor variable, namely first, second, third). I need to
control autocorrelation among siblings, so I use "Nest ID" to fit random
intercepts for different nests.
My model is:
model.1 <- lmer(Death_2 ~ Year + Sex + Egg_Volume + Hatch_Order +
(1|Nest_ID), family = binomial, data = Data)
summary(model.1)
But I get the error and warning messages below:
Error in eval(expr, envir, enclos) :
(maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate In addition:Warning message:
In lmer(Death_2 ~ Year + Sex + Egg_Volume + Hatch_Order + (1 |
Nest_ID), :
calling lmer with 'family' is deprecated; please use glmer() instead
Question: how can I circumvent these two issues?
Thanks in advance.
Luciano
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