Program CONTRAST [1/17/2001]Instructions:
Tests hypotheses about survival or recovery rates. Method: See Sauer & Williams (1989) Generalized Procedures For Testing Hypotheses About Survival Or Recovery Rates., J. Wildl. Manage. 53:137-142.
The idea is to assign each of the survival rates to a group. Contrast then tests the null hypothesis that the average survival for each group is the same. A significant chi-square value is reason to reject the null hypothesis meaning at least one of the groups is different.
For example, if you have 3 survival rates for males and 3 survival rates for females, assign '1' to the group for the 1st 3 rows, and '2' for the group for the last 3 rows. If the chi-square is 'significant', then we would reject the hypothesis that males survival = female survival.
The default groups (different group for each survival rate) tests whether at least one of the survival rates is significantly different from the others.
A group value of zero omits that survival rate from the analysis.
If you have covariances, you may enter them after clicking the "var-cov matrix" button.
You may copy and paste from a spreadsheet using Ctrl-C and Ctrl-V.