# Overview

If you have purchased a subscription to ***PRIMER 8 with PERMANOVA+***, then you will have access to the **PERMANOVA+** main menu item that allows you to perform a broad range of additional analyses using a suite of routines that are not available in the basic ***PRIMER 8 Lite*** package. Check out our website to see a [**Detailed list of all features**](https://primer.website.org.nz/features/detailed-list-of-all-features/). 

Note also that the **PERMANOVA** routine has been expanded substantially in the leap from PRIMER 7 to PRIMER 8. For a more complete guide to all of these important improvements, please see the essential resource: '[**What's new in PRIMER 8**'](https://learninghub.primer-e.com/books/whats-new-in-primer-8). You can also consult the historical [**PERMANOVA+ user manual**](https://learninghub.primer-e.com/books/permanova-for-primer-guide-to-software-and-statistical-methods) for fundamental information and references regarding some of these routines and their underlying statistical details.

Here, we will run through a quick example of how to set up and run a multi-factor PERMANOVA analysis in PRIMER 8. **Permutational multivariate analysis of variance** (PERMANOVA) partitions variation in the space of a chosen dissimilarity measure in response to one or more factors in a specified sampling protocol or experimental design ({{@483#bkmrk-anderson2001a}}, {{@483#bkmrk-anderson2017}}). Tests of individual terms in a PERMANOVA model are achieved by constructing correct (pseudo-)*F* ratios on the basis of expectations of mean squares (EMS), and p-values are obtained using correct permutation algorithms given the full study design. *We know of no other software package that accomplishes this.*

Importantly, the PERMANOVA routine in PRIMER allows the user:
+ to specify whether factors are **fixed**, **random**, **finite**, or of a type called '**whole-plot/subject**' that caters to designs lacking replication at different scales,
+ to account for **heterogeneity** in multivariate dispersions when testing for differences in centroids,
+ to specify whether a factor is **nested** in one or more other factors,
+ to test **interaction terms**,
+ to include one or more quantitative **covariates** in the analysis,
+ to **group covariates** (accommodating cyclical/seasonal models),
+ to **re-order**, **pool** or **remove** individual terms from a model,
+ to handle correctly:
  + **mixed models**
  + user-specified **contrasts**
  + **BACI designs** (before-after/control-impact), 
  + **asymmetrical designs** (e.g., in environmental impact studies),
  + **randomised blocks**,
  + **split plots** and **splt-split-plots**,
  + **hierarchical designs**,
  + **repeated measures**,
  + **unbalanced designs** (Type I, II or III sums of squares),
  + ... and more.