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Calcite | Level 5

In a paper on reintroduced cranes, I have data like this: ID, Sex, Year, Dispersal* (e.g., 1-01, M, 2002, 1)

I want to show that females disperse more than males.

I used chi-square. Reviewer indicated this violated assumption of independence because of multiple years of data for same birds and that I should use GLIMMIX.

What are lines of code needed to set up model?

SAS version 9.x (latest)

*Dispersal: 1 = in reintroduction area; 0 = out (dispersed).


Thanks, Richard

Super User
Or proc mixed. make ID as Subject variable, Year as a random effect. You should call @Steve or @lvm
Calcite | Level 5

id = identification code for each bird.

out = dispersal value (=1 if out of reintro. area); each bird has data in 1 or more years (observations).

This code:

proc glimmix;

title 'difference in dispersal by sex including all birds';

class sex id;

model out = sex / link=logit dist=binomial;

random int / subject=id;



Produces these results: Type III Tests of Fixe Effects:
Effect = Sex, Num DF = 1, Den DF = 568, F Value = 5.26, Pr > F = 0.0221

Does this look correct? Thank you.

Super User
Sorry. I am not expert about proc glimmix.
You should post it at Statistical Forum. 
@Steve @lvm ...   are there .



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