Hey guys,
I have a data set that is made of qualitatives variables that I'm trying to correlate. To that end I'm trying to perform a multiple correspendence analysis with the package CA, and the function mjca
Here is what my data look like : N= NO, O= Yes
> head(data3,20)
dens_ville climat prov promo sub_mail GDP_ca benef_quali
1 moderate cold semi-arid Instagram N O 60k +
2 very_low cold semi-arid direct N O 40k +
3 moderate cold semi-arid Instagram O O 60k -
4 low cold semi-arid Facebook N O 60k +
5 very_low cold semi-arid Facebook N O 60k +
6 moderate hot semi-arid Facebook N O 60k +
7 moderate hot semi-arid Instagram N O 60k -
8 moderate continental Facebook N O 50k +
9 moderate continental direct N N 50k +
10 moderate continental Instagram N N 50k +
11 moderate continental direct N N 50k +
12 moderate continental Instagram N O 50k -
13 moderate continental Facebook N N 50k -
14 low continental direct O O 60k -
15 low continental direct N O 50k +
16 moderate continental Instagram O O 50k +
17 moderate continental Instagram O O 50k +
18 moderate continental Facebook N N 60k -
19 moderate continental Instagram N N 60k -
20 low continental Instagram N N 50k -
My Goal is : I'm looking to see what correlates with benefice +.
My Question is : which map type should I chose for plotting (and why)?
I not too familiar with this method and I've read the paper by Nenadié & Greenacre, but that doesn't really tell me which map type I should chose for the plot. (I'm relatively new to statistics btw)
Rowgab or Rowgreen seem the only readables ones, but that doesn't mean they are actually appropriate vs the default symmetrical one.
Cheers
PS:
If you know of a better analysis to do what I want to do, please feel free to suggest it !
I have tried randomforest regression and logistic regression with poor success (for those, all numbered values (density, GDP, benef) were not converted to qualitative (except benef for logistic regression).