Hi Jim,
So many thanks for your reply. I actually made a mistake in presenting the
problem; I should have clarified that the 1-10 linear scale questions went
as: 10 most humorous/closest to Egyptian culture and 1 the least. Also, I
should have attached some examples so the participant issue could be clear.
Here is attached the dataset (if there is no problem or I am not going
against the rules of the R-help group).
Actually, I wanted better to be the only dependent factor and asking
participants 'which subtitle is better?' could be enough, but I wanted to
have detailed information of why a subtitle is better by asking
participants specific questions (regarding which subtitle is more humorous
and closer to Egyptian culture). Most of the time, the total of the hum +
cul = better, but sometimes it is not (e.g. the sum for subtitle EA could
be bigger than for SA, but the participant prefers SA in the better
column).
The WF (*watched first*) is the mode via which participants watched the two
subtitles; some participants watched the SA subtitle first and other
watched the EA first.
Does this make sense?
All the best
On Thu, 11 Jun 2020 at 05:24, Jim Lemon <drjimle...@gmail.com> wrote:
> Hi Saudi,
> I can only make a guess, but that is that a variable having a unique
> value for each participant has been read in as a factor. I assume that
> "better" is some combination of "hum" and "cul" and exactly what is
> WF?
>
> Jim
>
> On Thu, Jun 11, 2020 at 5:27 AM Saudi Sadiq <saudisa...@gmail.com> wrote:
> >
> > Dear Sir/Madam,
> >
> > Hope everyone is safe and sound. I appreciate your help a lot.
> >
> > I am evaluating two Arabic subtitles of a humorous English scene and
> asked
> > 263 participants (part) to evaluate the two subtitles (named Standard
> > Arabic, SA, and Egyptian Arabic, EA) via a questionnaire that asked them
> to
> > rank the two subtitles in terms of how much each subtitle is
> >
> > 2) more humorous (hum),
> >
> > 5) closer to Egyptian culture (cul)
> >
> >
> >
> > The questionnaire contained two 1-10 linear scale questions regarding
> the 2
> > points clarified, with 1 meaning the most humorous and closest to
> Egyptian
> > culture, and 1 meaning the least humorous and furthest from Egyptian
> > culture. Also, the questionnaire had a general multiple-choice question
> > regarding which subtitle is better in general (better). General
> information
> > about the participants were also collected concerning gender (categorical
> > factor), age (numeric factor) and education (categorical factor).
> >
> > Two versions of the questionnaire were relied on: one showing the ‘SA
> > subtitle first’ and another showing the ‘EA subtitle first’. Nearly half
> > the participants answered the first and nearly half answered the latter.
> >
> > I am focusing on which social factor/s lead/s the participants to
> evaluate
> > one of the two subtitles as generally better and which subtitle is more
> > humorous and closer to Egyptian culture. Each of these points alone can
> be
> > the dependent factor, but the results altogether can be linked.
> >
> > I thought that mixed effects analyses would clarify the picture and
> answer
> > the research questions (which factor/s lead/s participants to favour a
> > subtitle over another?) and, so, tried the lme4 package in R and ran
> many
> > models but all the codes I have used are not working.
> >
> > I ran the following codes, which yielded Error messages, like:
> >
> > model1<- lmer (better ~ gender + age + education + WF + (1 | part),
> > data=sub_data)
> >
> > Error: number of levels of each grouping factor must be < number of
> > observations (problems: part)
> >
> >
> >
> > Model2 <- glmer (better ~ gender + age + education + WF + (1 | part),
> data
> > = sub_data, family='binomial')
> >
> > Error in mkRespMod(fr, family = family) :
> >
> > response must be numeric or factor
> >
> >
> >
> > Model3 <- glmer (better ~ age + gender + education + WF + (1 | part),
> data
> > = sub_data, family='binomial',
> control=glmerControl(optimizer=c("bobyqa")))
> >
> > Error in mkRespMod(fr, family = family) :
> >
> > response must be numeric or factor
> >
> >
> >
> > Why does the model crash? Does the problem lie in the random factor part
> (which
> > is a code for participants)? Or is it something related to the mixed
> > effects analysis?
> >
> > Best
> > Saudi Sadiq
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
--
Saudi Sadiq,
Lecturer, Minia University, Egypt
Academia <http://york.academia.edu/SaudiSadiq>, Reserachgate
<https://www.researchgate.net/profile/Saudi_Sadiq>, Google Scholar
<https://scholar.google.co.uk/citations?user=h0latzcAAAAJ&hl=en>, Publons
<https://publons.com/researcher/2950905/saudi-sadiq/>
Certified Translator by (Egyta) <https://www.egyta.com/>
Associate Fellow of the Higher Education Academy, UK
<https://www.heacademy.ac.uk/>
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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