PERMANOVA+, Online Workshop

This workshop is now FULL – join the WAITLIST!

Please download and read the workshop documents listed in the blue box labelled “Download Information”, above. If you would like to go on our waitlist, please send your completed registration form to the PRIMER-e office at: [email protected]. We will notify you directly in the event that a spot becomes available, and will only send you an invoice for your registration at that time.

Keen for another PERMANOVA+ workshop in a similar time-zone?

To register your interest contact the PRIMER-e office at: [email protected]. Let us know your preferred time-zone and how many of your colleagues or students are keen. If we have critical mass, we’ll put on another workshop between now and the end of the year!

Online Workshop Details

PERMANOVA+ will be presented by Distinguished Professor Marti J. Anderson (Massey University and PRIMER-e, FRSNZ, Auckland, New Zealand)

PERMANOVA+ allows analysis of multivariate data in response to complex designs, partitioning variation in multivariate data on the basis of a resemblance measure of choice, with rigorous inferences via permutation methods. The tools in PERMANOVA+ provide formal models, tests and predictions for multivariate (or univariate) ecological (and other) systems that are over-parameterised (i.e., have too many variables) or that demonstrate substantial non-normality.

Participants will explore: analysis and estimation of components of variation in complex experimental designs, including interactions, covariates, contrasts, fixed or random effects, crossed or nested models, unbalanced designs, environmental impact designs, randomised blocks or repeated measures (PERMANOVA); tests for homogeneity of multivariate dispersions and analyses of beta diversity (PERMDISP); multivariate regression and model selection procedures (DISTLM); unconstrained (PCO) or constrained ordinations using distance-based redundancy analysis (dbRDA) or canonical analysis of principal coordinates (CAP), leave-one-out allocation success for discriminant analysis or canonical correlation analyses based on resemblance matrices and the placement of new points into existing predictive canonical models.

The online workshop will flow between lectures and lab sessions, with the final day of the workshop (Friday) devoted to Masterclass / Own-data sessions. Participants can ask questions, interact with other workshop participants in small (breakout) groups, and also consult one-on-one with the presenter to analyse their own datasets, using the tools learned during the week. Familiarity with the core methods in PRIMER 6 or 7 (e.g., having previously attended a PRIMER workshop) and/or some prior knowledge of basic multivariate methods and experimental design is desirable for a PERMANOVA+ workshop.