Supplement 1. R code to compute model-averaged regression coefficients for Burnham and Anderson (2002) college gpa example and to simulate multi-part compositional predictors and model-averaged estimates similar to Rice et al (2013) zero-truncated Poisson regression count model for Greater Sage-Grouse.

2016-08-10T10:17:47Z (GMT) by Brian S. Cade
<h2>File List</h2><div> <p><a href="Supplement1.txt">Supplement1.txt</a> (MD5: faff226df1ad4adfa82f2ca1700d5010)</p> <p><a href="Supplement2.txt">Supplement2.txt</a> (MD5: 51eeb647483834e7ea0742d81ffc4372)</p> </div><h2>Description</h2><div> <p>Supplement1.txt has R script to read in the college GPA example data from Burnham and Anderson 2002:226, estimates the 16 linear least squares regression models, computes AICc, AICc weights, variance inflation factors, partial standard deviations of predictors, standardizes estimates by partial standard deviations, computes model-averaged standardized estimates and their standard errors, and computes the model-averaged ratio of <i>t</i> statistics for unstandardized estimates (equivalent to model-averaged ratio of standardized estimates). The code is written to be transparent with respect to the mathematical operations rather than for efficiency.</p> <p>Supplement2.txt has R script to generate the simulations in <a href="appendix-B.pdf">Appendix B</a> for multi-part compositional predictors within a zero-truncated Poisson regression count model similar to the breeding sage-grouse count model of Rice et al. (2013).</p> </div>