[R-sig-ME] What does that mean?

Thierry Onkelinx th|erry@onke||nx @end|ng |rom |nbo@be
Tue Apr 30 09:42:45 CEST 2019

Dear Despina,

I'm guessing that something might be wrong with the coding of the nested
random effect. Note that (1|A/B/C) is equivalent to (1|A) + (1|A:B) +
(1|A:B:C) You'll need to tell us more on your design if you need help on
that. If possible, send a reproducible example including some data.

Another thing you'll need to worry about is (quasi) complete separation.

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel

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


Op di 30 apr. 2019 om 02:09 schreef DESPINA MICHAILIDOU <
de.michailidou using gmail.com>:

> I am trying to run the following analysis and receive the following output
> glmm_Comb_PH_tod <- glmer(Comb_PH_tod~ CA_effect + (1 | ID/SCAN_DATE/Side),
> data=TAK_data, family=binomial(link = "logit"))
> summary(glmm_Comb_PH_tod)
> Output
> Error in length(value <- as.numeric(value)) == 1L :
>   (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
> pwrssUpdate
> > summary(glmm_Comb_PH_tod)
> Error in summary(glmm_Comb_PH_tod) : object 'glmm_Comb_PH_tod' not found
> How can I fix that? Any suggestions? I am very new to R.
> Thank you in advance.
> Despina
>         [[alternative HTML version deleted]]
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

	[[alternative HTML version deleted]]

More information about the R-sig-mixed-models mailing list