Provides further output from an analysis by `AOVANYHOW`

(R.W. Payne).

### Options

`PRINT` = string tokens |
Controls printed output from the analysis (`aovtable` , `information` , `means` , `residuals` ); default `aovt` , `info` , `mean` |
---|---|

`FPROBABILITY` = string token |
Printing of probabilities for variance ratios in the analysis-of-variance table (`yes` , `no` ); default `no` |

`PLOT` = string tokens |
Which residual plots to provide (`fittedvalues` , `normal` , `halfnormal` , `histogram` ); default `*` i.e. none |

`COMBINATIONS` = string token |
Factor combinations for which to form predicted means (`present` , `estimable` ); default `esti` |

`ADJUSTMENT` = string token |
Type of adjustment to be made when predicting means (`marginal` , `equal` , `observed` ); default `marg` |

`PSE` = string tokens |
Types of standard errors to be printed with the predicted means (`differences` , `alldifferences` , `lsd` , `alllsd` , `means` ; default `diff` |

`LSDLEVEL` = scalar |
Significance level (%) for least significant differences; default 5 |

`EFLOSS` = scalar |
Maximum loss of efficiency occurring on any treatment contrast if the analysis is done by regression |

`EXIT` = scalar |
Code indicating the method of analysis |

### Parameters

`SAVE` = identifiers |
Save structure from `AOVANYHOW` ; default uses the save structure from the most recent `AOVANYHOW` analysis |
---|

### Description

The `AOVANYHOW`

procedure assesses a data set to select the most appropriate method for analysis of variance. If the design is orthogonal or balanced it uses the `ANOVA`

directive. Otherwise, if there is no blocking in the design (i.e. there is only one random term) it uses the Genstat regression facilities through procedure `A2WAY`

or `AUNBALANCED`

. Finally, if there are additional random terms, it looks to see if these contain any useful information about the treatments in order to choose between regression and `REML`

.

This procedure, `AOVDISPLAY`

, allows further output to be produced from an analysis by `AOVANYHOW`

. By default, the output is from the most recent analysis done by `AOVANYHOW`

. However, you can print the output from an earlier analysis by setting the `SAVE`

parameter to a pointer containing the analysis information, saved earlier using the `SAVE`

parameter of `AOVANYHOW`

.

The printed output is controlled by the `PRINT`

option. The settings are limited to those that can produce analogous output from any of the analysis methods:

`aovtable` |
analysis-of-variance table from `ANOVA` or regression, or Wald and F tests for fixed effects from `REML` , |
---|---|

`information` |
design type, efficiency factors and name of the command used for the analysis, |

`means` |
tables of (predicted) means, and |

`residuals` |
residuals (fitted values are printed too for analyses by regression or `REML` ). |

Probabilities can be printed for variance ratios by setting option `FPROBABILITY=yes`

.

Tables of means from regression and `REML`

are calculated using the `PREDICT`

and `VPREDICT`

directives, respectively. The first step (A) of their calculations forms the full table of predictions, classified by every factor in the model. The second step (B) averages the full table over the factors that do not occur in the `table of means. `

The `COMBINATIONS`

option specifies which cells of the full table are to be formed in Step A. The default setting, `estimable`

, fills in all the cells other than those that involve parameters that cannot be estimated, for example because of aliasing. Alternatively, setting `COMBINATIONS=present`

excludes the cells for factor combinations that do not occur in the data. The `ADJUSTMENT`

option then defines how the averaging is done in Step B. The default setting, `marginal`

, forms a table of marginal weights for each factor, containing the proportion of observations with each of its levels; the full table of weights is then formed from the product of the marginal tables. The setting `equal`

weights all the combinations equally. Finally, for regression analyses, the setting `observed`

uses the `WEIGHTS`

option of `PREDICT`

to weight each factor combination according to its own individual replication in the data.

The `PSE`

option controls the types of standard errors that are produced to accompany the tables of means, with settings:

`differences` |
summary of standard errors for differences between pairs of means, |
---|---|

`alldifferences` |
standard errors for differences between all pairs of means, |

`lsd` |
summary of least significant differences between pairs of means, |

`alllsd` |
least significant differences between all pairs of means, |

`means` |
effective standard errors for analyses by `ANOVA` , or approximate effective standard errors for analyses by regression or `REML` – these are formed by procedure `SED2ESE` with the aim of allowing good approximations to the standard errors for differences to be calculated by the usual formula of sed_{i}_{,j} = √( ese_{i}^{2} + ese_{j}^{2} ). |

The default is `differences`

. The `LSDLEVEL`

option sets the significance level (as a percentage) for the least significant differences.

The `PLOT`

option allows various residual plots to be requested: `fittedvalues`

for a plot of residuals against fitted values, `normal`

for a Normal plot, `halfnormal`

for a half Normal plot, and `histogram`

for a histogram of residuals.

You can save a scalar indicating the recommended method of analysis by using the `EXIT`

option. The scalar can take values with the following meanings.

0. The design is orthogonal. Analyse by `ANOVA`

.

1. The design is balanced. Analyse by `ANOVA`

.

2. The design unbalanced. It has 1 or 2 treatment factors and no blocking. Analyse by `A2WAY`

.

3. The design unbalanced and has 1 or 2 treatment factors. No more than a proportion defined by the `EFLIMIT`

option of the information on any treatment contrast is estimated between block terms. Analyse by `A2WAY`

.

4. The design unbalanced, and there are either weights or more than 2 treatment factors. There is no blocking. Analyse by `AUNBALANCED`

.

5. The design is unbalanced, and there either are weights or more than 2 treatment factors. No more than a proportion defined by the `EFLIMIT`

option of the information on any treatment contrast is estimated between block terms. Analyse by `AUNBALANCED`

.

6. The design unbalanced with several block (i.e. random) terms. Analyse by `REML`

.

The `EFLOSS`

option can save the maximum loss of efficiency that would occur on any treatment contrast if the analysis is done by regression.

Options: `PRINT`

, `FPROBABILITY`

, `PLOT`

, `COMBINATIONS`

, `ADJUSTMENT`

, `PSE`

, `LSDLEVEL`

, `EFLOSS`

, `EXIT`

.

Parameter: `SAVE`

.

### Action with `RESTRICT`

If the `Y`

variate or any of the factors or covariates was restricted, only the units not excluded by the restriction will have been analysed.

### See also

Procedure: `AOVANYHOW`

.

Commands for: Analysis of variance.

### Example

CAPTION 'AOVANYHOW example 1',\ 'Split plot design, see Guide to Genstat, Part 2, Section 4.2.1.';\ STYLE=meta,plain FACTOR [NVALUES=72; LEVELS=6] Blocks & [LEVELS=3] Wplots & [LEVELS=4] Subplots GENERATE Blocks,Wplots,Subplots FACTOR [LABELS=!T('0 cwt','0.2 cwt','0.4 cwt','0.6 cwt')] Nitrogen & [LABELS=!T(Victory,'Golden rain',Marvellous)] Variety VARIATE Yield; DECIMALS=2; EXTRA=' of oats in cwt. per acre' READ [SERIAL=yes] Nitrogen,Variety,Yield 4 3 2 1 1 2 4 3 1 2 3 4 3 1 2 4 4 1 2 3 2 1 3 4 2 3 4 1 4 2 3 1 1 4 2 3 3 4 1 2 1 3 4 2 2 3 4 1 4 1 3 2 3 4 1 2 3 4 2 1 3 1 4 2 4 3 1 2 1 2 3 4 : 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 1 1 1 1 3 3 3 3 2 2 2 2 1 1 1 1 2 2 2 2 1 1 1 1 3 3 3 3 1 1 1 1 2 2 2 2 3 3 3 3 : 156 118 140 105 111 130 174 157 117 114 161 141 104 70 89 117 122 74 89 81 103 64 132 133 108 126 149 70 144 124 121 96 61 100 91 97 109 99 63 70 80 94 126 82 90 100 116 62 96 60 89 102 112 86 68 64 132 124 129 89 118 53 113 74 104 86 89 82 97 99 119 121 : " Define the treatment structure: factorial effects of V and N." TREATMENTS Variety*Nitrogen " Subplots nested within whole-plots nested within blocks." BLOCK Blocks/Wplots/Subplots AOVANYHOW [PRINT=aovtable,information] Yield AOVDISPLAY [PRINT=means] CAPTION 'AOVANYHOW example 2',\ 'Unbalanced design with almost all information within blocks.';\ STYLE=meta,plain SPLOAD '%GENDIR%/Data/Product.gsh' BLOCKSTRUCTURE day TREATMENTSTRUCTURE A*B*C AOVANYHOW [PRINT=aovtable,information] Y AOVDISPLAY [PRINT=means]