Jolliffe test for multiple comparisons — jolliffe

I.T. Jolliffe test for multiple comparisons. Implements a cluster-based alternative closely linked to the Student-Newman-Keuls multiple comparison method. Single-linkage cluster analysis is applied, using the p-values obtained with the SNK test for pairwise mean comparison as a similarity measure. Groups whose means join beyond \(1 - \alpha\) are statistically different. Alternatively, complete linkage cluster analysis can also be applied.

Usage

jolliffe_test(
  y,
  trt,
  alpha = 0.05,
  method = "single",
  show_plot = TRUE,
  console = TRUE,
  abline_options,
  ...
)

Arguments

y: Either a model (created with lm() or aov()) or a numerical vector with the values of the response variable for each unit.
trt: If y is a model, a string with the name of the column containing the treatments. If y is a vector, a vector of the same length as y with the treatments for each unit.
alpha: Numeric value corresponding to the significance level of the test. The default value is 0.05.
method: string indicating the clustering method to be used. For single linkage (the default method) either "single" or "slca". For complete linkage, either "complete" or "clca".
show_plot: Logical value indicating whether the constructed dendrogram should be plotted or not.
console: Logical value indicating whether the results should be printed on the console or not.
abline_options: list with optional arguments for the line in the dendrogram.
...: Optional arguments for the plot() function.

Value

A list with three data.frame and one hclust:

stats: data.frame containing summary statistics by treatment.
groups: data.frame indicating the group to which each treatment is assigned.
parameters: data.frame with the values used for the test. treatments is the total number of treatments, alpha is the significance level used, n is either the number of repetitions for all treatments or the harmonic mean of said repetitions, MSE is the mean standard error from the ANOVA table and SEM is an estimate of the standard error of the mean.
dendrogram_data: object of class hclust with data used to build the dendrogram.

References

Jolliffe, I. T. (1975). Cluster analysis as a multiple comparison method. Applied Statistics: Proceedings of Conference at Dalhousie University, Halifax, 159-168.

Author

Santiago Garcia Sanchez

Examples

data("PlantGrowth")
# Using vectors -------------------------------------------------------
weights <- PlantGrowth$weight
treatments <- PlantGrowth$group
jolliffe_test(y = weights, trt = treatments, alpha = 0.1, show_plot = FALSE)
#>      group
#> trt1     1
#> ctrl     1
#> trt2     2
#> Treatments within the same group are not significantly different
# Using a model -------------------------------------------------------
model <- lm(weights ~ treatments)
jolliffe_test(y = model, trt = "treatments", alpha = 0.1, show_plot = FALSE)
#>      group
#> trt1     1
#> ctrl     1
#> trt2     2
#> Treatments within the same group are not significantly different