Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors.
I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm()) without the correlation between variables. I thought I could use for the continous (numerical) and ordered factor a spearman correlation that is using the ranks. But I thought also that I have to use a contingency table for the dichotomous factors. I read also that it is possible to use a point-biserial correlation to calculate the correlation between dichotomous and continuous variables. Now I am confused what I should use to calculate the correlation using all my variables and how I could do that in R. Is it possible with cor(), rcorr(), cormat() or other R-functions using one of the available correlation-coefficients. I would be very happy if somebody could enlighten my darkness. Many thanks in advance. B. ----- The art of living is more like wrestling than dancing. (Marcus Aurelius) -- View this message in context: http://www.nabble.com/Correlation-dichotomous-factor%2C-continous-%28numerical%29-and-ordered-factor-tp18852158p18852158.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list 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.
