PERMANOVA+, Online Workshop

How to Register

For further information please download and read the workshop documents listed in the blue box labelled “Download Information”, above. To register, please send your completed registration form to the PRIMER-e office at: [email protected]. Please send a separate registration form for each individual participant and contact the PRIMER-e office directly if you wish to receive a single invoice for multiple registrations.

If you have registered for a PRIMER 7 workshop within the past 12 months, you are eligible for a discount of 10% off the workshop registration fee.

Online Workshop Details

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

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, metric and threshold-metric MDS) 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. No formal training in statistics is required, but participants are expected to have some familiarity with the core methods in PRIMER (such as MDS, PCA and ANOSIM).