bss_test {ClustMC} | R Documentation |
Bautista, Smith and Steiner test for multiple comparisons
Description
Bautista, Smith and Steiner (BSS) test for multiple comparisons. Implements a procedure for grouping treatments following the determination of differences among them. First, a cluster analysis of the treatment means is performed and the two closest means are grouped. A nested analysis of variance from the original ANOVA is then constructed with the treatment source now partitioned into "groups" and "treatments within groups". This process is repeated until there are no differences among the group means or there are differences among the treatments within groups.
Usage
bss_test(
y,
trt,
alpha = 0.05,
show_plot = TRUE,
console = TRUE,
abline_options,
...
)
Arguments
y |
Either a model (created with |
trt |
If |
alpha |
Numeric value corresponding to the significance level of the test. The default value is 0.05. |
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 |
|
... |
Optional arguments for the |
Value
A list with three data.frame
and one hclust
:
stats |
|
groups |
|
parameters |
|
dendrogram_data |
object of class |
Author(s)
Santiago Garcia Sanchez
References
Bautista, M. G., Smith, D. W., & Steiner, R. L. (1997). A Cluster-Based Approach to Means Separation. Journal of Agricultural, Biological, and Environmental Statistics, 2(2), 179-197. doi:10.2307/1400402
Examples
data("PlantGrowth")
# Using vectors -------------------------------------------------------
weights <- PlantGrowth$weight
treatments <- PlantGrowth$group
bss_test(y = weights, trt = treatments, show_plot = FALSE)
# Using a model -------------------------------------------------------
model <- lm(weights ~ treatments)
bss_test(y = model, trt = "treatments", show_plot = FALSE)