Error message

The lme4 package has changed some. Details are in http://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.
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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



_______________________________________________
R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

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?

You can circumvent the second very easily (by using glmer() instead of
lmer()).  For the second, I'm a little surprised, as we don't see that
error message very often unless the data are quite badly behaved (or
using a non-standard link like cloglog).  Does it work in lme4.0?  Any
chance you can send data?