I have three questions:
For data with different response categories (likert type or ordinal) what type of correlation should be calculated? I know for ordinal variables Spearman's rank correlation can be used. Am I right?
Do I need to order the categories and recode the responses according to their importance to calculate these correlations? I think I should clarify my question.
Suppose that I have two variables that I believe responsible behind profitability of a company. I have the following variables:
For variable 'regular staff meetings', responses are collected as:
1='yes' and 2='no'
For variable 'proportion of staffs given formal performance appraisals', responses are collected as:
1=10%, 2=20%,..., 10=100%
Now as intuitively I believe that the more regular staff meetings are held or performance appraisals are given the better will be the profit of that company, so should we recode for variable 'regular staff meetings' 'yes'=2 and 'no'=1 that responses with 'yes' receives the first rank while spearman's rank correlation is calculated?
Similarly for variable 'proportion of staffs given formal performance appraisals' responses with 10 (100% staffs receiving performance appraisal) will receive the first rank while spearman's rank correlation is calculated. Otherwise if I don't recode the responses from the variable 'regular staff meetings' then the ranks the responses receive becomes of opposite direction as responses with 'yes'=1 receives the second rank but it was supposed to increase profitability!
What if I want correlation between mixed type of variables (both interval and ordinal)? Is it possible to calculate?
Thanks for your patience and upcoming kind clarification. :)