View source: R/TreeOrderTests.R
TreeMaxD | R Documentation |
Computes a test statistic based on the maximum standardized difference between the treatment means and the control mean under the tree order restriction.
TreeMaxD(sample_data, significance_level, n.boot = 1e+05, seed = NULL)
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. |
The test statistic is the maximum of standardized differences between each treatment mean and the control mean. The critical value is estimated by a bootstrap procedure.
A character string with the critical value, the Max-D test statistic, and the test decision.
Subha Halder
Halder, Mondal, and Kumar (2025) "Testing Against Tree Ordered Alternatives in One-way ANOVA" <https://arxiv.org/abs/2507.17229>
# 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 MaxD test at 5% significance level
TreeMaxD(sample_data, 0.05, n.boot = 10000)
TreeMaxD(sample_data, 0.05, n.boot = 100000)
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