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

[Saudi Sadiq]

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 رواق العربية
28-30th July 2015 - call for papers now open
https://sites.google.com/a/york.ac.uk/fal2015/

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