Genstat has a comprehensive set of commands to do an analysis of variance. These directives define the models to be fitted:

`BLOCKSTRUCTURE` |
defines the blocking structure of the design, and hence the strata and error terms |
---|---|

`COVARIATE` |
specifies covariates for analysis of covariance |

`TREATMENTSTRUCTURE` |
defines the treatment (or systematic) terms |

For unstructured designs with a single error term, `BLOCKSTRUCTURE`

need not be specified, and `COVARIATE`

is needed only for analysis of covariance. Balanced designs can be analysed using the `ANOVA`

directive.

`ANOVA` |
performs analysis of variance |
---|

Directives and procedures are available to produce plots, checks and further output from an `ANOVA`

analysis, or to save information in Genstat data structures:

`ADISPLAY` |
displays further output from analyses produced by `ANOVA` |
---|---|

`AGRAPH` |
plots tables of means from `ANOVA` |

`APLOT` |
plots residuals from an `ANOVA` analysis |

`AFIELDRESIDUALS` |
display residuals in field layout |

`ACHECK` |
checks assumptions for an `ANOVA` analysis |

`AMCOMPARISON` |
performs pairwise multiple comparison tests for `ANOVA` means |

`AKEEP` |
copies information from an `ANOVA` analysis into Genstat data structures |

`ASPREADSHEET` |
saves results from an analysis of variance in a spreadsheet |

Unbalanced designs with a single error term can be be analysed using the `AUNBALANCED`

procedure. (Unbalanced designs with several error terms should be analysed using the commands for REML analysis of linear mixed models.)

`AUNBALANCED` |
performs analysis of variance for unbalanced designs |
---|---|

`AUDISPLAY` |
produces further output for an unbalanced design (after `AUNBALANCED` ) |

`AUGRAPH` |
plots tables of means from `AUNBALANCED` |

`AUPREDICT` |
forms predictions from an unbalanced design (after `AUNBALANCED` ) |

`AUSPREADSHEET` |
Saves results from an analysis of an unbalanced design (by `AUNBALANCED` ) in a spreadsheet |

`AUMCOMPARISON` |
performs pairwise multiple comparison tests for means from an unbalanced analysis of variance, performed previously by `AUNBALANCED` |

`AUKEEP` |
saves output from analysis of an unbalanced design (by `AUNBALANCED` ) |

There are also specialized procedures for designs (balanced or unbalanced) with a single error term and one or two treatment factors.

`A2WAY` |
performs analysis of variance of a balanced or unbalanced design with up to two treatment factors |
---|---|

`A2DISPLAY` |
provides further output following an analysis of variance by `A2WAY` |

`A2KEEP` |
copies information from an `A2WAY` analysis into Genstat data structures |

If you are unsure what method to use, you can use the `AOVANYHOW`

procedure to see which method is most appropriate.

`AOVANYHOW` |
performs analysis of variance using `ANOVA` , `AUNBALANCED` , `A2WAY` or `REML` as appropriate |
---|---|

`AOVDISPLAY` |
provides further output from an analysis by `AOVANYHOW` |

Other procedures relevant to analysis of variance include:

`ABOXCOX` |
estimates the power λ in a Box-Cox transformation, that maximizes the partial log-likelihood in `ANOVA` |
---|---|

`AFCOVARIATES` |
defines covariates from a model formula for `ANOVA` |

`AFMEANS` |
forms tables of means classified by `ANOVA` treatment factors |

`ASTATUS` |
provides information about the settings of `ANOVA` models and variates |

`APERMTEST` |
does random permutation tests for analysis-of-variance tables |

`ABIVARIATE` |
produces graphs and statistics for bivariate analysis of variance |

`ALIAS` |
finds out information about aliased model terms in analysis of variance |

`ACONFIDENCE` |
calculates simultaneous confidence intervals |

`AMDUNNETT` |
forms Dunnett’s simultaneous confidence interval around a control |

`AMTIER` |
analyses a multitiered design by analysis of variance specified by up to 3 model formulae |

`AMTDISPLAY` |
displays further output for multitiered designs analysed by `AMTIER` |

`AMTKEEP` |
saves information from the analysis of a multitiered design by `AMTIER` |

`ACANONICAL` |
determines the orthogonal decomposition of the sample space for a design, using an analysis of the canonical relationships between the projectors derived from two or more model formulae |

`ACDISPLAY` |
provides further output from an analysis by `ACANONICAL` |

`ACKEEP` |
saves information from an analysis by `ACANONICAL` |

`VSPECTRALCHECK` |
forms the spectral components from the canonical components of a multitiered design, and constrains any negative spectral components to zero |

`AN1ADVICE` |
aims to give useful advice if a design that is thought to be balanced fails to be analysed by `ANOVA` |

`APOLYNOMIAL` |
forms the equation for a polynomial contrast fitted by `ANOVA` |

`ADPOLYNOMIAL` |
plots single-factor polynomial contrasts fitted by `ANOVA` |

`AREPMEASURES` |
produces an analysis of variance for repeated measurements |

`ARETRIEVE` |
retrieves an `ANOVA` save structure from an external file |

`ASTORE` |
stores an `ANOVA` save structure in an external file |

`ASCREEN` |
performs screening tests for designs with orthogonal block structure |

`AYPARALLEL` |
does the same analysis of variance for several y-variates, and collates the output |

`A2RDA` |
saves results from an analysis of variance in R data frames |

`AU2RDA` |
saves results from an unbalanced analysis of variance, by `AUNBALANCED` , in R data frames |

`MAANOVA` |
does analysis of variance for a single-channel microarray design (parallel anova) |

`SED2ESE` |
calculates effective standard errors that give good approximate standard errors of differences |

`SEDLSI` |
calculates least significant intervals |

`LSIPLOT` |
plots least significant intervals, saved from `SEDLSI` |

`RTCOMPARISONS` |
calculates comparison contrasts within a multi-way table of means |

`A2PLOT` |
plots effects and robust s.e. estimates from designs with two-level factors |

`CENSOR` |
pre-processes censored data before analysis by `ANOVA` |

`CINTERACTION` |
clusters rows and columns of a two-way interaction table |

`DIALLEL` |
analyses full and half diallel tables with parents |

`AMMI` |
allows exploratory analysis of genotype × environment interactions |

`FMEGAENVIRONMENTS` |
forms mega-environments based on winning genotypes from an AMMI-2 model |

`FRIEDMAN` |
performs Friedman’s nonparametric analysis of variance |

`NLCONTRASTS` |
fits non-linear contrasts to quantitative factors in `ANOVA` |

`VHOMOGENEITY` |
tests homogeneity of variances |

`WSTATISTIC` |
calculates the Shapiro-Wilk test for Normality |