Description Usage Arguments Details Value Author(s) See Also

View source: R/block_effects.r

Fits a single linear model for all data in a specific condition and estimates the main effect of each abcterial block

1 2 | ```
block_effects(Dat, var.name, cond1, cond2, keep.vars = c("Plate",
"Experiment"), create.design = TRUE)
``` |

`Dat` |
A data.frame. Must contain the following columns: 'Bacteria', 'StartP' and 'EndP'. It must further contain a column matching the var.name and keep.var parameters. |

`var.name` |
A string character indicating the name of the variable in Dat that has the lef-hand side of the linear model (i.e. the dependent variable) |

`cond1` |
The value for the 'StartP' variable in Dat. Only data where Dat$StartP == cond1 will be kept. |

`cond2` |
The value for the 'EndP' variable in Dat. Only data where Dat$EndP == cond2 will be kept. |

`keep.vars` |
A vector of character objects indicating which variables from Dat should be kept as covariates in the model |

`create.design` |
logcial indicats whether the desing must be created for the main effects. If FALSE, a linear model with the variables indicated by keep.vars will be produced. |

This function will create a design matrix based on SynCom names. Therefore,
it assumes that the SynCom names are named *B#B#*, where 'B' is replaced
by the functiona group type ('P', "I' or 'N') and # is the block number
within each functional type. It assumes that exactly nine blocks (3 per functional
type) exist.

The function will also include any variable named in keep.vars as a covariate in the linear models.

Only the data that matches where Dat$StartP == cond1 & Dat$EndP == cond2 will be used to fit the model. The rest is discarded.

Returns an object of class 'lm', see `lm`

for more info

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