[R-sig-ME] Convergence warning message

Christopher David Desjardins cddesjardins at gmail.com
Wed Mar 16 21:33:34 CET 2016 

Thanks, I'll read through the convergence help page in the lme4 package.
Chris

On Wed, Mar 16, 2016 at 3:12 PM, Thierry Onkelinx <thierry.onkelinx at inbo.be>
wrote:

> Dear Jackie,
>
> 127.0.01 points to localhost, which will work only on your computer.
>
> Best regards,
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> and Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
>
> To call in the statistician after the experiment is done may be no
> more than asking him to perform a post-mortem examination: he may be
> able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does
> not ensure that a reasonable answer can be extracted from a given body
> of data. ~ John Tukey
>
>
> 2016-03-16 20:56 GMT+01:00 Jackie Wood <jackiewood7 at gmail.com>:
> > Hi Chris,
> >
> > You can find the example code I was talking about here if you haven't
> > tracked it down already:
> >
> > http://127.0.0.1:29918/library/lme4/html/convergence.html
> >
> > Jackie
> >
> >
> >
> > On Wed, Mar 16, 2016 at 3:44 PM, Christopher David Desjardins <
> > cddesjardins at gmail.com> wrote:
> >
> >> Thanks, Jacquelyn and Ben. Jacquelyn, did you mean to attach some code
> or
> >> just reference the site that Ben did? I had seen Ben's comments on
> >> StackOverflow about potential false convergence messages, so I'll dig a
> bit
> >> deeper. I just wanted to make sure it wasn't something obvious that I
> had
> >> overlooked first.
> >>
> >> >From what I've read online, glmmPQL is inappropriate with Bernoulli
> >> trials.
> >> Is that correct?
> >>
> >> Chris
> >>
> >>
> >>
> >> On Wed, Mar 16, 2016 at 2:35 PM, Ben Bolker <bbolker at gmail.com> wrote:
> >>
> >> >
> >> >   Good question.
> >> >
> >> >   I'm afraid that for data sets ~ 100,000 observations or bigger, our
> >> > convergence calculations aren't terribly reliable -- see e.g. the
> third
> >> set
> >> > of figures under https://rpubs.com/bbolker/lme4_convergence ... I
> would
> >> > follow Jackie's advice ...
> >> >
> >> >
> >> > On 16-03-16 02:24 PM, Jackie Wood wrote:
> >> >
> >> >> Hi Chris,
> >> >>
> >> >> Try checking ?convergence....coincidentally, I was having a similar
> >> >> problem
> >> >> just yesterday. There are some step by step
> >> >> instructions for trouble shooting/double checking convergence
> warnings.
> >> >> For
> >> >> example, a bit of example code is provided to run your model using a
> >> >> number
> >> >> of different optimizers. If all optimizers yield similar values, it's
> >> >> possible that you could be getting false convergence warnings. I'm
> not
> >> >> sure
> >> >> if that's the case with your data, but it might be a place to start!
> >> >>
> >> >> Jacquelyn
> >> >>
> >> >> On Wed, Mar 16, 2016 at 1:56 PM, Christopher David Desjardins <
> >> >> cddesjardins at gmail.com> wrote:
> >> >>
> >> >> I am trying to fit a mixed effects binomial model.
> >> >>>
> >> >>> The data consists of
> >> >>> - A dependent variable consisting of Bernoulli trials (outcome)
> >> >>> - A time variable (time), which has been mean centered
> >> >>> - An id variable (id)
> >> >>> - A categorical covariate (cat_cov)
> >> >>> - A blocking variable (block) which id is nested in. I realize in
> the
> >> >>> model
> >> >>> below that it should be (1 | id/block) but I am just trying to
> >> >>> troubleshoot
> >> >>> my problem at the moment.
> >> >>>
> >> >>> When I run the following:
> >> >>>
> >> >>> example_data <- read.csv("
> https://cddesja.github.io/example_data.csv",
> >> >>> header  = T)
> >> >>> example_data$cat_cov <- as.factor(example_data$cat_cov)
> >> >>> example_data$id <- as.factor(example_data$id)
> >> >>> example_data$block <- as.factor(example_data$block)
> >> >>> main_effects <- glmer(outcome ~ 1 + cat_cov + time + I(time^2) + (1
> |
> >> >>> id),
> >> >>> data = example_data, family = "binomial")
> >> >>>
> >> >>> That last line of code gives a warning message:
> >> >>>
> >> >>> main_effects <- glmer(outcome ~ 1 + cat_cov + time + I(time^2) + (1
> |
> >> >>>>
> >> >>> id), data = example_data, family = "binomial")
> >> >>> Warning messages:
> >> >>> 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl =
> control$checkConv,
> >> >>> :
> >> >>>    Model failed to converge with max|grad| = 4.36001 (tol = 0.001,
> >> >>> component
> >> >>> 1)
> >> >>> 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl =
> control$checkConv,
> >> >>> :
> >> >>>    Model is nearly unidentifiable: very large eigenvalue
> >> >>>   - Rescale variables?
> >> >>>
> >> >>> I am not exactly sure how to proceed. I know the issue is with
> cat_cov,
> >> >>> though it's unclear to me why. If I swap out in a different
> categorical
> >> >>> covariate in the model, not included in that data set, I don't get
> this
> >> >>> message. I am not running into complete separation with cat_cov.
> So,
> >> >>> I'm a
> >> >>> little perplexed.
> >> >>>
> >> >>> Any advice on what I should do or something I could look at it
> would be
> >> >>> very helpful.
> >> >>>
> >> >>> Thanks,
> >> >>> Chris
> >> >>> --
> >> >>> https://cddesja.github.io/
> >> >>>
> >> >>>          [[alternative HTML version deleted]]
> >> >>>
> >> >>> _______________________________________________
> >> >>> R-sig-mixed-models at r-project.org mailing list
> >> >>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >> >>>
> >> >>>
> >> >>
> >> >>
> >> >>
> >> > _______________________________________________
> >> > R-sig-mixed-models at r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >> >
> >>
> >>
> >>
> >> --
> >> https://cddesja.github.io/
> >>
> >>         [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-mixed-models at r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >>
> >
> >
> >
> > --
> > Jacquelyn L.A. Wood, PhD.
> > 224 Montrose Avenue
> > Toronto, ON
> > M6G 3G7
> > Phone: (514) 293-7255
> >
> >         [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>



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