TreeMinD: Minimum Difference Test for Tree Ordered Alternatives

In TreeOrderTests: Tests for Tree Ordered Alternatives in One-Way ANOVA

Minimum Difference Test for Tree Ordered Alternatives

Description

Computes a test statistic based on the minimum standardized difference between the treatment means and the control mean under the tree order restriction.

Usage

TreeMinD(sample_data, significance_level, n.boot = 1e+05, seed = NULL)

Arguments

sample_data	A list of numeric vectors. The first element represents the control group, the others represent treatment groups.
significance_level	A numeric value between 0 and 1 specifying the significance level for the test (e.g., 0.05).
n.boot	Number of bootstrap replications to estimate the critical value (default is 100000).
seed	Optional random seed for reproducibility.

Details

The test statistic is the minimum of standardized differences between each treatment mean and the control mean. The critical value is estimated by a bootstrap procedure.

Value

A character string with the critical value, the Min-D test statistic, and the test decision.

Author(s)

Subha Halder

See Also

Halder, Mondal, and Kumar (2025) "Testing Against Tree Ordered Alternatives in One-way ANOVA" <https://arxiv.org/abs/2507.17229>

Examples

# Generate data
set.seed(456)
control <- rnorm(10, mean = 5)
treatment1 <- rnorm(10, mean = 6)
treatment2 <- rnorm(10, mean = 7)

sample_data <- list(control, treatment1, treatment2)

# Run MinD test at 5% significance level
TreeMinD(sample_data, 0.05, n.boot = 10000)


TreeMinD(sample_data, 0.05, n.boot = 100000)

TreeOrderTests documentation built on Aug. 8, 2025, 6:40 p.m.