Description Usage Arguments Details Value Author(s) Examples

View source: R/GroupClustering.R

Group effects given the pairwise p-values

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`PvaluesMatrix` |
a matrix containing the p-values of the comparisons of each possible pairs of effects in the lower triangle (excluding the diagonal) |

`CI` |
a matrix containing with three columns containint the effects, the lower limits and the upper limits of a confidence interval for the effects (default = NULL, indicating that no confidence intervals are available) |

`Effects` |
a vector containing the effects |

`SignificanceLevel` |
the significance level of the pairwise comparisons (default = 0.05) |

`UpperCase` |
should upper case letters be used for labelling the groups (default is FALSE) |

`RankLabels` |
should the labels of the grouping be sorted according to the value of the response (default=TRUE) |

`PlotAdj` |
should the associated graph be printed(default = FALSE) |

`padjust` |
method for correcting the p-values (before the calculations are performed) as in the function p.adjust (Default is NULL, indicating that no multiple testing corrections are used) |

`CalcClusters` |
should the clusters be calculated and displayed instead of grouping (Default is FALSE) |

`digits` |
number of digits in the output (default = 4) |

This is an auxiliar function forming a contrast matrix of all possible. Generates an error if n is smaller than 2. The function contructs, using the supplied matrix of p-values for all pairwise comparisosns, an undirected graph with vertices representing the levels of the effects, using the convention that two vertices are connected by an edge iff the p-value for testing equality the two vertices is larger than the prefixed significance level. The maximal cliques of this graph form the grouping of the levels of the effects.

an object of (S3) class "PostHoc" with methods for print, summary, plot, barplot and lines defined. An object of class "PostHoc" contails the effects, grouping, the matrix of p-values of all pairwise comparisons, the graph (Gr) of adjacency, the confidence intervals of the effects, the significance levels, the number of digits to be used for printing, the list of maximal cliques of the graph Gr, the clusters (if calculated).

Rodrigo Labouriau

1 2 3 4 5 6 | ```
MM <- glm(Y ~ Treatment+0, data=DeIdentifiedExample)
GG <- posthoc(MM)
Effects <- coef(MM)
PvaluesMatrix <- GG$PvaluesMatrix
TT <- FormGroupsClusters(PvaluesMatrix = PvaluesMatrix, Effects = Effects)
plot(TT)
``` |

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