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1.35 Designs with covariates (Holdfast invertebrates, revisited)
A topic that is related (perhaps surprisingly) to the topic of unbalanced designs is the analysis...
1.16 Additivity
Central to an understanding of what an interaction means for linear models25 is the idea of addit...
1.34 Types of sums of squares (Birds from Borneo)
When the design is unbalanced, there will be a number of different ways to do the partitioning, w...
1.33 Unbalanced designs
Virtually all of the examples thus far have involved the analysis of what are known as balanced e...
1.32 Repeated measures (Victorian avifauna, revisited)
While randomised blocks, latin squares and split-plot designs lack spatial replication, a special...
1.31 Split-plot designs (Woodstock plants)
Another special case of a design lacking appropriate replication is known as a split-plot design....
1.30 Designs that lack replication (Plankton net study)
A topic related to the issue of pooling is the issue of designs that lack replication. Familiar e...
1.29 Pooling or excluding terms
For a given design file, PERMANOVA, by default, will do a partitioning according to all terms tha...
1.28 Estimating components of variation
The EMS’s also yield another important insight: they provide a direct method to get unbiased esti...
1.27 Nested design (Holdfast invertebrates)
We have seen how a crossed design is identifiable by virtue of every level of one factor being pr...
1.26 Testing the design
Given the fact that so many important aspects of the results (pseudo-F ratios, P-values, power, t...
1.25 Inference space and power
It is worthwhile pausing to consider how the above tests correspond to meaningful hypotheses for ...
1.23 Constructing $F$ from EMS
The determination of the EMS’s gives a direct indication of how the pseudo-F ratio should be cons...
1.22 Expected mean squares (EMS)
An important consequence of the choice made for each factor as to whether it be fixed or random i...
1.20 Fixed vs random factors (Tasmanian meiofauna)
All of the factors considered so far have been fixed, but factors can be either fixed or random. ...
1.19 Contrasts
In some cases, what is of interest in a particular experimental design is not necessarily the com...
1.18 Additional assumptions
Recall that we assume for the analysis of a one-way design by PERMANOVA that the multivariate obs...
1.17 Methods of permutations
As for the one-way case, the distribution of each of the pseudo-F ratios in a multi-way design is...
1.14 Two-way crossed design (Subtidal epibiota)
The primary advantage of PERMANOVA is its ability to analyse complex experimental designs. The pa...
1.12 Monte Carlo P-values (Victorian avifauna)
In some situations, there are not enough possible permutations to get a reasonable test. Consider...