[R] checkConv and as.data.frame.default problems in R

[John Fox]

Dear Saudi Sadiq,

If you want answers to most of your questions, you'll likely have to provide your data so that people can reproduce the errors. I can, however, answer part of your last question without the data:

plot(allEffects(modelqaaf1)) fails because the data set is named q, and there is a standard R function named q(). Obviously there is a scoping issue that confuses allEffects() for a reason I don't yet understand.

Here's a simple example that reproduces this error:

---------- snip ------------

> library(lme4)
Loading required package: Matrix
Loading required package: Rcpp
> library(effects)
> fm1 <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), cake)
> allEffects(fm1)
 model: angle ~ recipe * temperature

 recipe*temperature effect
      temperature
recipe      175      185      195      205      215      225
     A 29.13333 31.53333 30.80000 33.53333 38.66667 35.06667
     B 26.86667 29.40000 31.73333 32.13333 34.46667 35.26667
     C 27.93333 28.93333 31.73333 30.86667 34.40000 35.73333
> q <- cake
> fm1 <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), data=q)
> allEffects(fm1)

 Error in as.data.frame.default(data, optional = TRUE) : 
  cannot coerce class ""function"" to a data.frame 

------------- snip -------------

Why, as you claim, you get the same error with plot(allEffects(modelqaaf)), where the data set is qaaf rather than q, is hard to understand, and perhaps you're mistaken.

I hope this helps,
 John

------------------------------------------------
John Fox, Professor
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/
	
	
On Wed, 1 Jul 2015 15:40:48 +0100
 Saudi Sadiq <ss1272 at york.ac.uk> wrote:
> Hi All,
> 
> I have two datasets, vowels and qaaf, and both have 8 columns clarified as
> follows:
> 
> 1.  convergence: DV (whether participants succeeded to use CA (Cairene
> Arabic) or fail to do so; hence, they use MA (Minia Arabic)
> 
> 2.  speaker: 62 participants
> 
> 3.  lexical.item: as pronounced
> 
> 4.  style: careful and casual
> 
> 5.  gender: males and females
> 
> 6.  age: continues variable
> 
> 7.  residence: urbanite, migrant to town or villager
> 
> 8.  education: secondary or below, university or postgraduate
> 
> The only difference between the two datasets is the number of items. With
> the vowels dataset, there are 1339 items; in the qaaf dataset there are
> 4064 items.
> 
> The aim of the test done was to know which independent variable is more
> responsible for using CA forms. I used the lme4 package, function glmer.
> 
> I ran the model:
> 
> 1.  modelvowels <- glmer(convergence ~ gender + age + residence +
> education +  style+ (1|lexical.item) + (1|speaker), data=vowels,
> family='binomial')
> 
> The message came on the screen:
> 
> 2.  Warning message:
> 
> In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
> 
>   Model failed to converge with max|grad| = 0.00210845 (tol = 0.001,
> component 1)
> 
> Then I ran the model after removing STYLE as follows:
> 
> 3.  modelvowels <- glmer(convergence ~ gender + age + residence +
> education + (1|lexical.item) + (1|speaker), data=vowels,
> family='binomial')
> 
> This produced a result. Then, I ran
> 
> 4.  plot(allEffects(modelvowels))
> 
> 
> 
> and this gave four charts (for the four independent variables: gender, age,
> residence and education).
> 
> Then, I moved to the qaaf dataset (4064 items) and ran the same model
> 
> 5.  modelqaaf <- glmer(convergence ~ gender + age + residence +
> education + (1|lexical.item) + (1|speaker), data=qaaf,
> family='binomial')
> 
> which gave results with the vowels dataset but there was a warning message
> this time
> 
> 6.  Warning message:
> 
> In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
> 
>   Model failed to converge with max|grad| = 0.429623 (tol = 0.001, component 8)
> 
> So, I removed one independent variable (residence) and ran this model again:
> 
> 7.  modelqaaf <- glmer(convergence ~ gender + age + education +
> (1|lexical.item) + (1|speaker), data=qaaf, family='binomial')
> 
> This gave a result. I removed another independent variable (gender) after
> returning (residence) and ran the model:
> 
> 8.  modelqaaf1 <- glmer(convergence ~ residence + age + education +
> (1|lexical.item) + (1|speaker), data=q, family='binomial')
> 
> This gave a result as well. Then, I tried to create some graphs using
> 
> 9.  plot(allEffects(modelqaaf)) and
> 
> 10. plot(allEffects(modelqaaf1))
> 
> 
> 
> but there was the same error for both
> 
> 11. Error in as.data.frame.default(data, optional = TRUE) :
> 
>   cannot coerce class ""function"" to a data.frame
> 
>  Now, my questions:
> 
> a.  why 1 did not work, why 3 worked, why 5 did not work though it has
> the same four IVs of 3, why 7 and 8 worked with only three IVs, and
> why 9 and 10 did not work though they are like 4 which worked well.
> 
> 
> 
> b.  What are the packages that must be installed with, before or after
> the lme4 package?
> 
> 
> 
>  Best
> 
> -- 
> Saudi Sadiq,
> Assistant Lecturer, English Department,
> Faculty of Al-Alsun,Minia University,
> Minia City, Egypt &
> PhD Student, Language and Linguistic Science Department,
> University of York, York, North Yorkshire, UK,
> YO10 5DD
> http://york.academia.edu/SaudiSadiq
> https://www.researchgate.net/profile/Saudi_Sadiq
> Certified Interpreter by Pearl Linguistics
> 
> Forum for Arabic Linguistics conference ???? ???????
> 28-30th July 2015 - call for papers now open
> https://sites.google.com/a/york.ac.uk/fal2015/
> 
> 	[[alternative HTML version deleted]]
> 
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