#' Testing for interaction in the two way ANOVA with single sub-class numbers. #' #' @name additivityTests-package #' @aliases additivityTests #' @docType package #' @title Additivity tests in the two way ANOVA with single sub-class numbers. #' @author Petr Simecek <[email protected]@gmail.com> #' @description In many applications of statistical methods, it is assumed that the response variable is #' a sum of several factors and a random noise. In a real world this may not be an appropriate model. #' For example, some patients may react differently to the same drug treatment or the effect of fertilizer #' may be influenced by the type of a soil. There might exist an interaction between factors. #' #' If there is more than one observation per cell then standard ANOVA techniques may be applied. Unfortunately, #' in many cases it is infeasible to get more than one observation taken under the same conditions. #' For instance, it is not logical to ask the same student the same question twice. #' #' Six tests of additivity hypothesis (under various alternatives) are included in this package: #' Tukey test, modified Tukey test, Johnson-Graybill test, LBI test, Mandel test and Tussel test. #' #' @keywords package NULL #' @name Boik #' @title Multi-headed Machine Data #' @description Performance of a multiple-headed machine used to fill bottles. Weights for six heads on five occasions were recorded. #' @docType data #' @usage data(Boik) #' @source Robert J. Boik: A comparison of three invariant tests of additivity in two-way classifications with no replications, Computational Statistics \& Data Analysis, 1993. #' @keywords datasets NULL
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