Power analysis

We have provided links to two pieces of software that we find useful for power analyses, GPower, and the software provided by Russ Lenth, of the Univesity of Iowa. Both are free, but you should acknowledge the use software in papers. Lenth has developed software for several years, beginning with PowerPack, through to his current Java applets that allow you to do power analysis on line. He has also created a small add-in for Microsoft Excel, PiFace, which includes the non-central probability distribution functions need to compute power. This add-in allows you to program pretty much any power analysis into excel.

Hierarchical partitioning

In Section 6.1.16 (pp. 141-142), we describe hierarchical partitioning, a procedure for decomposing the variability contributed by each predictor variable in a multiple linear regression model. Chris Walsh and Ralph Mac Nally from Monash University have written a program in the R language for doing hierarchical partitioning. The program can be cited as: Walsh, C., and Mac Nally, R. 2003. The hier.part package Version 0.5-1. Hierarchical Partioning. Documentation for R (R project for statistical computing).

Multivariate analyses

Two of the best places for new, interesting multivariate approaches are web sites of Marti Anderson and Pierre Legendre. Marti’s site includes distance-based redundancy analysis (Chapter 17) and her robust, non-parametric MANOVA approach (Chapter 18). Pierre Legendre’s page largely supports his Numerical Ecology book, but also has lots of other useful software.

If you are interested in environmental monitoring, you might also want to check out this book:

mon book cover Downes B.J., Barmuta L.A., Fairweather P.G., Faith D.P.,Keough M.J.,Lake P.S., Mapstone B.D. & Quinn G.P. (2002) Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters. xii + 434 pp. Cambridge University Press, Cambridge, UK