hiddenf.test: Franck et al.'s test for interaction

In sdateam/combinIT: Combine Interaction Tests for testing interaction in unreplicated two-way tables

Description

computes Franck et al's. (2013) test statistic,ACMIF, and corresponding p-value.

Usage

hiddenf.test(x, nsim = 1000, dist = "sim", ...)

Arguments

x	A b-by-t data matrix, which rows corresponding to b-block effects and columns are t-treatment effects
nsim	Number of simulation for compueting exact p-value
dist	If dist="sim", we used Monte Carlo simulation for estimating exact p-value, and if dist="asy", Bonferroni-adjusted p-value computed. The defaut value is "sim"

Details

If rows numer(b) of data matrix is less than it's columns number(t) at fiest transposing data matrix. In addition requires that data matrix has more than two rows or columns

Value

A p-value for input

Author(s)

Zahra. Shenavari, ...

References

Franck, C., Nielsen, D., Osborne, J. A. (2013). A method for detecting hidden additivity in two-factor unreplicated experiments. Computational Statistics and Data Analysis 67:95-104.

Examples

## Not run: this is an example
data(cnv6)
hiddenf.test(cnv6,nsim=1000,dist = "sim")

sdateam/combinIT documentation built on May 6, 2019, 12:10 p.m.