PRIMER 8 with PERMANOVA+ is a substantial upgrade on its predecessor, offering a host of marvelous new tools and statistical methods. These range from simple utilities to make your life easier through to sophisticated novel analytical methods that are found no-where else.
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Summarise your variables (or samples) with ease, using a host of standard statistics (e.g., average, median, range, min, max, nominated quantiles, skewness, kurtosis, etc.) and/or using several other bespoke diagnostic measures, such as frequencies of occurrence, the number of singletons or doubletons, or the smallest value above a given threshold, etc. You can also calculate summaries on data split by a factor (or indicator).
Create raw or cumulative empirical distributions and view them graphically. Run robust Kolmogorov-Smirnov tests to compare the empirical distributions of two groups, also within levels of another factor.
Dot plots and violin plots offer a fantastic way to visualise the empirical shape of distributions of sample values across multiple groups for any individual variable.
Run any one of a whole new suite of non-parametric univariate statistical tests. PRIMER’s implementation of these tests is novel in that all of these rely on robust permutation algorithms and automatically output relevant graphics as well. Available tests include:
Test of Association (between 2 variables).
PERMANOVA in PRIMER 8 provides a solution to the multivariate Behrens-Fisher problem for multivariate dissimilarity-based analyses (Anderson et al. 2017). Now you can test for differences in multivariate centroids while allowing for heterogeneity in multivariate dispersions.
The notion of a fixed vs a random factor need not be seen as a strict dichotomy, but rather as a progression (Anderson et al. 2025). PERMANOVA in PRIMER 8 has a new factor type called ‘Finite’, which permits the user to specify the number of levels in the population from which sampled levels have been drawn. This can greatly increase the power of inferential tests, especially in studies of environmental impact.
PERMANOVA in PRIMER 8 has a new factor type called ‘Subject/Whole-plot error’, so you can specify sources of error at multiple levels in the study design. This enables repeated measures, split-plot (and split-split-plot, etc.) study designs to be analysed easily and directly.
You can group multiple covariates together (using an indicator) in PERMANOVA for PRIMER 8. This opens the door to a plethora of new models for analysing multivariate patterns of periodicity, cyclicity and other spatio-temporal models.
New centroid plots allow you to visualise the relative importance of main effects from a multi-factorial PERMANOVA model (Main Effects Plot) and to explore the patterns among cell centroids from complex PERMANOVA study designs (Interaction Plot), all constructed in the space of your chosen resemblance measure.
Remove the effects of one or more dominant factors (via PERMANOVA) or regressors (via DISTLM) and output a residual distance/dissimilarity matrix among the sampling units. Ordination of a residual distance matrix permits instant visualisation of non-dominant factors.
Create a multivariate control chart on the basis of a chosen resemblance measure. You can build a chart through time (using progressive, baseline or moving-window criteria) and detect when an individual observation is ‘out-of-control’, given previous observations. This is a fantastic tool for monitoring applications.
Perform standardisations of samples (or variables) separately within groups/levels of indicators (or factors), output values as raw or cumulative percentages or proportions, with ordering specified by you.
Generate a new factor which consists of ordered groups, based on any chosen continuous variable, with a plethora of optional criteria for defining suitable group boundaries. For example, you can specify quantiles as ‘breaks’, or create a given number of groups with equal sample sizes per group, or minimise the within-group sum-of-squares, etc.
