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Questionnaire Analysis virtually without continuous Variables

3 messages · Sacha Viquerat, R. Michael Weylandt, Joshua Wiley

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Hello!
I am doing an analysis on a questionnaire of hunters taken in 4 
different districts of some mysterious foreign country. The aim of the 
study was to gather info on the factors that determine the hunting 
success of a peculiarly beautiful bird in that area. All variables are 
factors, i.e. they are variables such as "Use of Guns - yes / no", "Use 
of Dogs - yes / no" and the likes. The response is upposed to be "number 
of Birds caught", which was designed to be the only continuous variable. 
However, in reality the number of caught birds is between 0 and 1, 
sometimes hunters answered with 2. Unfortunately, it is not the 
questioner who is burdened with the analysis, but me. I am struggling to 
find an appropriate approach to the analysis. I don't really consider 
this as count data, since it would be very vulnerable to overinflation 
(and a steep decline for counts above 0). I can't really suggest 
binomial models either, since the lack of explanatory, continuous data 
renders such an approach quite vague. I also struggle with the random 
design of the survey (households nested within villages nested within 
districts). Adding to that, hunters don't even target the bird as their 
prime objective. The bird is essentially a by-catch, most often used for 
instant consumption on the hunting trip. I therefore doubt that any 
analysis makes more than a little sense, but I will not yet succumb to 
failure. Any ideas?

Thanks in advance!

PS: I just realized that this is not a question related to R but to 
statistics in general. Apologies for that!
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On Sat, Aug 4, 2012 at 9:12 AM, Sacha Viquerat
<dawa.ya.moto at googlemail.com> wrote:
Hi Sacha,

This sounds a good deal like homework to me ("some mysterious foreign
country") and this list has a "no homework" policy so unfortunately, I
don't think you'll be able to get much help here.

Best of luck with your analysis however!

Michael
#
Hi Sacha,

You're right that this is not an R related question really (would be better somewhere like crossvalidated.com).

If basically everyone catches 0/1 birds, then I would consider dichotomizing:

Y <- as.integer(caught >= 1)

then check cross tabs to make sure there are no zero cells between predictors and outcome:

xtabs(~Y + dogs + guns, data=yourdata)

then use the glmer() function to model the nested random effects.

m <- glmer(Y ~ dog + gun + (1 | household) + (1 | village) + (1 | district), data = yourdata, family=binomial)

summary(m)

Cheers,

Josh
On Aug 4, 2012, at 7:12, Sacha Viquerat <dawa.ya.moto at googlemail.com> wrote: