[R-sig-ME] Error message

[Luciano La Sala]

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 escribió:
> 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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>

-- 
Luciano F. La Sala
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
Cátedra de Epidemiología
Departamento de Biología, Bioquímica y Farmacia
Universidad Nacional del Sur
San Juan 670
Bahía Blanca (8000)
Argentina


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