Good afternoon all: I am looking for some statistical advice, in a situation that has me temporarily stumped.
We have data which includes a categorical predictor variable (a landscape attribute, habitat patch size), two continuous dependent variables (measures of plant and rodent abundance), and many years of observations. Experimental hypotheses involve the question of how patch size affects organism abundance, and also about correlations between plant and rodent abundance. This seems to be set up exactly for the repeated measures ANOVA function in SPSS within the GLM section, only no information is given in the printout about associations between the dependent variables. What would you recommend we do to formally investigate the relations between plant and rodent abundance (the dependent variables), in the light of time and patch size? So far we can run a RMANOVA to investigate time and patch size, and then to run separate analyses (e.g. correlations within each year) to look at the association between plant and rodent abundance, but there may be a more holistic way to do this. Thanks for any advice you can give. Bill Cook William M. Cook Assistant Professor Department of Biological Sciences St. Cloud State University 720 4th Avenue South St. Cloud, MN 56301 USA Phone: (320) 308-2019 E-mail: [EMAIL PROTECTED]
