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We tested whether tissue isotope ratios varied over the nesting period by performing general linear models, with repeated measures of δ13C and δ15N for each tissue in relation to the time (in days) of each clutch after the first clutch was observed.
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The Matlab package ffmanova was used to perform general linear modeling with multiple responses (MANCOVA).
This test performs general linear modeling for multiple responses that are also likely covariates.
We performed general linear model statistical analysis using SAS software, version 9.1 for Windows (SAS Institute, Cary, NC).
A vertex-by-vertex analysis was carried out performing a general linear model to analyze whether any difference in mean cortical thickness existed between groups (low: a3/a2 < 1 μV; middle: 1 < a3/a2 < 1.16 μV; high: a3/a2 > 1.17 μV).
The Q model was performed using general linear model (GLM).
Comparisons between treatment groups were performed with general linear models.
Main comparisons between groups will be performed using general linear mixed modelling.
Comparisons among native Japanese, Japanese-American and Caucasian women were performed using general linear modeling methods.
Between-group variations in cortical thickness were assessed using a vertex-by-vertex general linear model performed with SurfStat (http://www.math.mcgill.ca/keith/surfstat/). Regional differences in grey matter between control and disease groups were assessed using the same covariates as the voxel-based morphometry analysis.
We tested for differences in absolute and relative eye size, lens surface area, total lens number, and relative quantification of opsin mRNA transcripts (2-ΔΔCT values [ 28]) by performing a full factorial general linear model (GLM) analysis with sex and seasonal form as fixed factors.
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