[R] Standard errors of sexual dimorphism?

[ErikiLund]

Hello!

I am working on a manuscript on sexual dimorphism in an aquatic
invertebrate, where we have estimated sexual dimorphism (SD) for 7 different
traits in four populations (a total of 28 SD-estimates). We have used the
following formula for estimating SD: 100 * (mean male trait value - mean
female trait value)/overall trait mean).

Then, we have used these SD-estimates to perform a GLM against other
interesting variables, such as the intersexual genetic correlations for each
of the traits.

Here are my questions:

1. Is there any procedure in "R" you would recommend that takes in to
account the sampling variance of the SD-estimates, rather than using the
mean value of each (which is supposed to reduce error and increase Type
I-error rates?

2. Is there a procedure to estimate SE for ratios such as this SD-estimate?

3. The data in these GLM:s might not be entirely statistically
non-independent (i. e. intersexual genetic correlations). Can you recommend
any R-procedure (package) that can deal with this problem (e. g.
bootstrapping or resampling)?

Many thanks in advance for input!

Erik Svensson

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