tests/testthat/test-MRtest().R

In bendeivide/midrangeMCP: Multiples Comparisons Procedures Based on Studentized Midrange and Range Distributions

library(testthat)
library(midrangeMCP)

test_that("Test of MRtest function",
          {
            # Response variable
            rv <- c(100.08, 105.66, 97.64, 100.11, 102.60, 121.29, 100.80,
                    99.11, 104.43, 122.18, 119.49, 124.37, 123.19, 134.16,
                    125.67, 128.88, 148.07, 134.27, 151.53, 127.31)

            # Treatments
            treat <- factor(rep(LETTERS[1:5], each = 4))

            # Anova
            res     <- anova(aov(rv~treat))
            DFerror <- res$Df[2]
            MSerror <- res$`Mean Sq`[2]

            # Loading the midrangeMCP package
            library(midrangeMCP)

            # applying the tests
            results <- MRtest(y = rv,
                              trt = treat,
                              dferror = DFerror,
                              mserror = MSerror,
                              alpha = 0.05,
                              main = "Multiple Comparison Procedure: MGM test",
                              MCP = c("MGM"))
            # Other option for the MCP argument is "all". All tests are used.

            results$Groups     # Results of the tests
            results$Statistics # Main arguments of the tests
            results$Summary    # Summary of the response variable

            # Using the y argument as aov or lm model
            res  <- aov(rv~treat)

            MRtest(y = res, trt = "treat", alpha = 0.05,
                   main = "Multiple Comparison Procedure: MGM test",
                   MCP = c("MGM"))

            # For unbalanced data: It will be used the harmonic mean of
            #                       the number of experiment replicates

            # Using the previous example
            rv <- rv[-1]
            treat <- treat[-1]

            res  <- lm(rv~treat) # Linear model

            # Multiple comparison procedure: MGR test
            MRtest(y = res, trt = "treat", alpha = 0.05,
                   main = "Multiple Comparison Procedure: MGR test",
                   MCP = c("MGR"))

            # Assuming that the available data are the averages
            #  of the treatments and the analysis of variance

            # Analysis of Variance Table

            # Response: rv
            #            Df Sum Sq Mean Sq F value    Pr(>F)
            # treat      4 4135.2 1033.80  14.669 4.562e-05 ***
            # Residuals 15 1057.1   70.47

            mean.treat <- c(100.87, 105.95, 117.62, 127.97, 140.30)
            treat <- factor(LETTERS[1:5])
            DFerror <- 15
            MSerror <- 70.47488
            replic <- 4

            MRtest(y = mean.treat,
                   trt = treat,
                   dferror = DFerror,
                   mserror = MSerror,
                   replication = replic,
                   alpha = 0.05,
                   main = "Multiple Comparison Procedure: MGM test",
                   MCP = c("MGM"),
                   ismean = TRUE)
          })