Hello, When I run a simple GLM with say 4 terms I would like to know the percent contribution of each term to the model. Here is an example: I constructed a simple model that includes river, age of fish, sex of fish and condition factor K as independent variables. I would like to know what the contribution of each of these terms is to the overall variance in the model. I read that 1 basic method is to divide the sum of squares for each term by the total model-wide sum of squares and multiply by 100. Is that correct? I have the following: and The error source above is the residual sum of squares, correct? So I would divide each of these sums of squares, including error, by 964645712, which is the total sum of squares (model plus error). However, when I do this the percentages only add up to 84% and not 100%. So, am I on the right track or is there a better method? Ultimately I would like to know what term has teh most influence on changes to my dependent variable. Thanks!
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