James -
I wonder why you would actually want to use the rank correlation method? <
Spearman's correlation is most appropriate when you want a correlation
measure for two variables that are ordinal categorical measures (instead of
numerical measures). For example, it may not make sense to arbitrarily
assign numerical values (1,2,3,4,5) to ordinal responses on a survey
questionnaire (Strongly Disagree, Disagree, Indifferent, Agree, Strongly
Agree)
I always thought it was a remnant of the days when more exact calculation
was tedious but I'd be glad to be enlightened. <
Pearson's correlation (Excel's CORREL worksheet function) summarizes a
linear relationship, so Spearman's correlation could be used to summarize a
nonlinear relationship between two numerical variables. Also, Spearman's is
not influenced as much by outliers. But, if you truly have a linear
relationship between two numerical variables, you lose information if you
convert the numbers to ranks before computing correlation.
- Mike
www.mikemiddleton.com