snk.evaluate.core {EvaluateCore} R Documentation

Student-Newman-Keuls Test

Description

Test difference between means of entire collection (EC) and core set (CS) for quantitative traits by Newman-Keuls or Student-Newman-Keuls test (Newman 1939; Keuls 1952).

Usage

snk.evaluate.core(data, names, quantitative, selected)


Arguments

 data The data as a data frame object. The data frame should possess one row per individual and columns with the individual names and multiple trait/character data. names Name of column with the individual names as a character string quantitative Name of columns with the quantitative traits as a character vector. selected Character vector with the names of individuals selected in core collection and present in the names column.

Value

A data frame with the following components.

 Trait The quantitative trait. EC_Min The minimum value of the trait in EC. EC_Max The maximum value of the trait in EC. EC_Mean The mean value of the trait in EC. EC_SE The standard error of the trait in EC. CS_Min The minimum value of the trait in CS. CS_Max The maximum value of the trait in CS. CS_Mean The mean value of the trait in CS. CS_SE The standard error of the trait in CS. SNK_pvalue The p value of the Student-Newman-Keuls test for equality of means of EC and CS. SNK_significance The significance of the Student-Newman-Keuls test for equality of means of EC and CS.

References

Keuls M (1952). “The use of the ,,studentized range" in connection with an analysis of variance.” Euphytica, 1(2), 112–122.

Newman D (1939). “The distribution of range in samples from a normal population, expressed in terms of an independent estimate of standard deviation.” Biometrika, 31(1-2), 20–30.

SNK.test

Examples


####################################
# Use data from R package ccChooser
####################################

library(ccChooser)
data("dactylis_CC")
data("dactylis_EC")

ec <- cbind(genotypes = rownames(dactylis_EC), dactylis_EC[, -1])
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
function(x) cut(x, breaks = 4))
ec[, c("X1", "X6", "X7")] <- lapply(ec[, c("X1", "X6", "X7")],
function(x) factor(as.numeric(x)))

core <- rownames(dactylis_CC)

quant <- c("X2", "X3", "X4", "X5", "X8")
qual <- c("X1", "X6", "X7")

####################################
# EvaluateCore
####################################

snk.evaluate.core(data = ec, names = "genotypes",
quantitative = quant, selected = core)



[Package EvaluateCore version 0.1.2 Index]