Redefines block and treatment variables as factors (R.W. Payne).

### No options

### Parameter

`FACTOR` = variates or texts |
Other variates or texts to convert into factors (if required) |
---|

### Description

`G2AFACTORS`

is one of a suite of procedures provided to simplify the use of Genstat to analyse data from the Agronomix Generation II system (see agronomix.com).

Data can be transferred to Genstat by writing a dbase file within Generation II, and reading this into Genstat using the `IMPORT`

procedure. By default, `IMPORT`

loads columns containing textual strings into Genstat text structures, and columms of numbers into variates. So, before data are analysed, some of the columns will need to be defined as factors. `IMPORT`

allows this to be done by setting its `COLUMNS`

parameter. An alternative (and simpler) method may be to use `G2AFACTORS`

.

If analysis of variance is to be used, the `BLOCKSTRUCTURE`

and `TREATMENTSTRUCTURE`

directives will need to be used to define the block and treatment models for the analysis. If you then call `G2AFACTORS`

, it will look through the models and redefines any texts or variates that they contain as factors, automatically, ready for the analysis (by the `ANOVA`

directive).

If the analysis is to be done in some other way (e.g. by `REML`

) you can still use `G2AFACTORS`

, and use the `FACTOR`

parameter specify the variates and texts that need to be converted,

Options: none.

Parameter: `FACTOR`

.

### Method

The `GET`

directive is used to access the current settings define by the `BLOCKSTRUCTURE`

and `TREATMENTSTRUCTURE`

directives. The `FCLASSIFICATION`

directive obtains the list of variables involved in the model, and the `GROUPS`

directive (with option `REDEFINE=yes`

) does the redefinition.

### See also

Directives: `ANOVA`

, `BLOCKSTRUCTURE`

, `TREATMENTSTRUCTURE`

, `REML`

.

Procedures: `G2AEXPORT`

, `G2VEXPORT`

.

Commands for: Analysis of variance, REML analysis of linear mixed models.

### Example

CAPTION 'G2AEXPORT example',\ !t('Randomized block design to assess five different diets',\ 'using rats from eight litters i.e. blocks (John & Quenouille,',\ '1977, Experiments Design and Analysis, page 32).');\ STYLE=meta,plain " read data into variates and text " TEXT Diet READ Litter,Rat,Diet,Gain 1 1 E 76.0 1 2 C 70.7 1 3 D 68.3 1 4 A 57.0 1 5 B 64.8 2 1 A 55.0 2 2 D 67.1 2 3 B 66.6 2 4 C 59.4 2 5 E 74.5 3 1 C 64.5 3 2 A 62.1 3 3 D 69.1 3 4 E 76.5 3 5 B 69.5 4 1 D 72.7 4 2 B 61.1 4 3 A 74.5 4 4 C 74.0 4 5 E 86.6 5 1 A 86.7 5 2 E 94.7 5 3 B 91.8 5 4 D 90.6 5 5 C 78.5 6 1 B 51.8 6 2 C 55.8 6 3 E 43.2 6 4 A 42.0 6 5 D 44.3 7 1 D 53.8 7 2 A 71.9 7 3 C 63.0 7 4 B 69.2 7 5 E 61.1 8 1 E 54.4 8 2 D 40.9 8 3 B 48.6 8 4 C 48.1 8 5 A 51.5 : BLOCKSTRUCTURE Litter/Rat TREATMENTSTRUCTURE Diet " redefine the block and treatment variables as factors " G2AFACTORS " analysis of variance of the gain in weight " ANOVA [FPROBABILITY=yes] Gain