What's New in PRIMER 8
Find out what's new in the latest version!
by Marti J. Anderson (2026)
Citation
Anderson, M.J. (2026). "What's New in PRIMER 8." PRIMER-e Learning Hub. PRIMER-e, Auckland, New ...
Table of Contents
Citation Summary Introduction New Statistical Methods in P8 New Tools & Utilities in P8...
Summary
Introduction
PRIMER 8 with PERMANOVA+ is a substantial upgrade on its predecessor, offering a host of marvelou...
New Statistical Methods in P8
Most of the methods in the list below are unique to PRIMER 8 and are not available in any other s...
New Tools & Utilities in P8
New default colour palette - The new colour palette for PRIMER graphics ensures distinctive col...
1. Expanded summary statistics
1.1 Expansion from P7 to P8
Summary statistics provide essential information to help you get to know your variables, their fu...
1.2 Definitions of statistics
Given a set of values $\{ y_1, y_2, ..., y_n \}$ for any individual variable $Y$, the following s...
1.3 Biotic data: summary stats
To show the utility of this tool, we will calculate some summary statistics from a study examinin...
1.4 Split summary stats results by groups
To run summary statistics on your variables separately for multiple groups of data, just choose a...
1.5 Environmental data: summary stats
For environmental data, we might choose to calculate different sorts of summary statistics than t...
2. Empirical distributions
3. Dot plots and Violin plots
3.1 Plots of empirical densities
Suppose we have measured a given variable in each of several groups. To visualise the distributio...
3.2 Example: Dotplot of oyster sizes
Let's re-visit the data on oyster sizes (,). We have already seen some variation in the cumulativ...
3.3 Example: Violin plot of kelp holdfast volumes
studied organisms colonising holdfasts of the kelp, Ecklonia radiata, sampled from four differen...
4. Univariate non-parametric methods
4.1 Wilcoxon signed-rank test
Overview The Wilcoxon signed-rank test was described by . It is designed for the situation where ...
4.2 Example: Plankton hauls
An example of a paired design with two groups is provided by , who described a study by to inves...
4.3 Mann-Whitney U test
Overview The Mann-Whitney U test was described by and . Here, interest lies in comparing two gro...
4.4 Example: Snapper in marine reserves
As an example of the Mann-Whitney U test, we will look at a dataset consisting of counts of the s...
4.5 Kruskal-Wallis test
Overview The Kruskal-Wallis test was described by and . Its purpose is to compare two or more in...
4.6 Example: A bivalve species from Ekofisk
We will use the Kruskal-Wallis test to compare counts of a bivalve species, Abra prismatica, occu...
4.7 Kolmogorov-Smirnov test
Overview The Kolmogorov-Smirnov test is a non-parametric test for comparing two distributions of ...
4.8 Example: Sizes of oysters
To demonstrate the Kolmogorov-Smirnov test in PRIMER, we shall return to the dataset consisting o...
4.9 Test of Association
Overview PRIMER 8 offers several options to achieve a non-parametric bivariate test of associatio...
4.10 Example: Ekofisk diversity
To demonstrate the test of association, we shall re-visit a dataset of macrofauna assemblages col...
4.11 Example: Associations between species
It is instructive to consider some additional examples of the test of association where the varia...
5. New PERMANOVA Design file
6. Allow heterogeneous dispersions in PERMANOVA
6.1 Overview - Allow heterogeneity
An important assumption of classical analysis of variance (ANOVA) is that the errors come from a ...
6.2 ANOVA in a nutshell
The one-way ANOVA model In one-way univariate analysis of variance (ANOVA), interest lies in comp...
6.3 The Behrens-Fisher problem (BFP)
Overview The Behrens-Fisher problem (BFP) is one of the oldest puzzles in statistics (; ; ). The ...
6.4 Multivariate Behrens-Fisher problem
Overview In a multivariate context, there are many ways that groups of sampling units can differ ...
6.5 Solution to the multivariate BFP
Overview described a general dissimilarity-based solution to the multivariate Behrens-Fisher pro...
6.6 Example: one-way PERMANOVA allowing heterogeneity
Let's look now at an example where there is a single factor in the study design, the number of re...
6.7 Heterogeneity in more complex designs
Handling heterogeneity with multiple factors The most important question to answer when you are d...
6.8 Example: two-way crossed PERMANOVA allowing heterogeneity
We shall look at the diets of $N$ = 346 juvenile steelhead / rainbow trout (Oncorhynchus mykiss) ...
7. Finite factors
7.1 Overview - Finite factors
ANOVA is one of the most widely used statistical techniques, providing a partitioning of the meas...
7.2 Dichotomy: fixed vs random factors
Consider the classical one-way linear ANOVA model, as described in section 6.2 above. Specificall...
7.3 Not a dichotomy: a progression from fixed to random
What is meant by a 'finite' factor? Suppose, for any factor, there are a total of $A$ levels in t...
7.4 Example: environmental impact on molluscs
The study design We consider here a study examining effects of a sewage outfall for $p$ = 151 mol...
7.5 Broader implications for detecting impact
Comparison of results treating 'Locations' as random Historical wisdom for such a design would ha...
8. Specify Subject/Whole-plot error in PERMANOVA
8.1 Designs lacking replication
In some cases, experiments are done in a way that lacks replication, often at the smallest spatia...
8.2 Example: Split-plot - Woodstock vegetation
The study design An example of a split-plot design is provided by a study of the effect of fire d...
8.3 Example: Repeated measures - Victorian avifauna
The study design An example of a repeated-measures sampling design (Fig. 8.5) is provided in a st...
9. Group covariates
9.1 Why group covariables together?
There are situations where it may be useful or important to include one or more quantitative co-v...
9.2 Periodic and cyclical models
Natural cycles in biology and ecology Important situations where the treatment of multiple covari...
9.3 Example: Annual monthly cycles - B.C. macroalgae
Consider the study described by consisting of regular surveys of macroalgal cover from a rocky i...
10. Centroid plots
10.1 Ordinations for multi-factor designs
Rationale When considering the response of a whole set of variables (such as the abundances of sp...
10.2 Main effects plot
What is a 'main effects plot'? In a main effects plot, we calculate and then show in an ordinatio...
10.3 Interaction plot
What is an 'interaction plot'? Although main effects plots can help us to visualise the main effe...
10.4 Example: NZ fish assemblages
To further demonstrate the utility of main effects plots and interactions for multi-way study des...
11. Residual distances
12. Control charts
12.1 Overview - Control charts
Rationale Suppose you have multivariate data (e.g., abundances of multiple species) sampled repea...
12.2 Classical univariate control chart
A classical univariate control chart arises in the context of process control for industrial and ...
12.3 Classical multivariate control chart
A suitable criterion for a control chart designed to detect shifts in the population mean vector ...
12.4 Bivariate normal example: NZ fish
To demonstrate the use of Hotelling's $T^2$ in a multivariate control-chart setting, it is useful...
12.5 Dissimilarity-based multivariate control chart
Essential steps Suppose we have an $(N \times p)$ data matrix, $\bm{Y}$, and we can capture the i...
12.6 Additional notes on implementing control charts
We offer here a few additional notes regarding the implementation of control charts in real appli...
12.7 Example: Birds from Grand Forks
We shall implement a control chart on data from the North American Breeding Bird Survey (BBS) ()....
13. New standardisation options
13.1 Overview
PRIMER 8 offers a host of new options for standardising data (either samples or variables), via t...
13.2 Analysing cumulative standardised data
Rationale Suppose we have data where the variables consist of different size classes of mussels (...
13.3 Example: Mussel sizes in the Gulf of Alaska
To implement the new standardisation routine in PRIMER 8 and (simultaneously) demonstrate the uti...
13.4 Example: Gulf of Maine invertebrates - functional resemblance
There are many situations where the standardisation of samples is required as a pre-treatment pri...
14. Create ordered groups
15. Other new tools & utilities
15.1 New default colour palette
Accessibility It is important to make graphics accessible to those with color vision deficiencies...
15.2 New selection options
In PRIMER 8, the options available for selecting samples or selecting variables have been expande...
15.3 Re-name levels of a factor (or indicator)
There are many situations where it would be very handy to be able to change the names of levels o...
15.4 Add customised values/labels to graphical axes
In PRIMER 8, there is a new tool that allows us to add customised values and labels to coordinate...
15.5 Split data sheet by factor/indicator
In PRIMER 8 there is a new tool, accessed by clicking Tools > Split Data..., which allows you to ...
15.6 Line plots for samples
There is a new facility in PRIMER 8 to create Line plots in two different ways: with one line fo...
15.7 Output group-level stats from dispersion (or variability) weighting
In PRIMER 8, you can now output more detailed statistical information from either dispersion-weig...
15.8 Output diagnostic plots from CAP
In PRIMER 8, it is now possible to output diagnostic plots from the CAP routine (i.e., canonical ...
15.9 New diagnostics for PCA/PCO plots
Background Consider a cloud of $N$ points (sampling units) in a $p$-dimensional multivariate spac...
References
Adegoke (2019) Adegoke, N. (2019) Contributions to improve power, efficiency and s...