subset a data frame by largest frequencies of factors
A consulting client has a large data set with a binary response (negative) and two factors (ctry and member) which have many levels, but many occur with very small frequencies. It is far too sparse with a model like glm(negative ~ ctry+member, family=binomial). > str(Dataset) 'data.frame': 10672 obs. of 5 variables: $ ctry : Factor w/ 31 levels "Barbados","Belize",..: 21 21 5 22 18 18 18 18 26 18 ... $ member : Factor w/ 163 levels "","ADHOPIA, PREETI ",..: 150 19 19 111 120 1 1 4 55 18 ... $ negative: int 0 1 0 1 1 1 1 0 0 0 ... > For analysis, we'd like to subset the data to include only those that occur with frequency greater than a given value, or the top 10 (say) in frequency, or the highest frequency categories accounting for 80% (say) of the total. I'm not sure how to do any of these in R. Can anyone help?
Michael Friendly Email: friendly AT yorku DOT ca Professor, Psychology Dept. & Chair, Quantitative Methods York University Voice: 416 736-2100 x66249 Fax: 416 736-5814 4700 Keele Street Web:http://www.datavis.ca Toronto, ONT M3J 1P3 CANADA