levene.evaluate.core: Levene's Test

View source: R/levene.evaluate.core.R

levene.evaluate.coreR Documentation

Levene's Test

Description

Test for of variances of the entire collection (EC) and core set (CS) for quantitative traits by Levene's test \insertCitelevene_robust_1960EvaluateCore. \loadmathjax

Usage

levene.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 columns

Trait

The quantitative trait.

EC_V

The variance of the EC.

CS_V

The variance of the CS.

EC_CV

The coefficient of variance of the EC.

CS_CV

The coefficient of variance of the CS.

Levene_Fvalue

The test statistic.

Levene_pvalue

The p value for the test statistic.

Levene_significance

The significance of the test statistic (*: p \mjseqn\leq 0.01; **: p \mjseqn\leq 0.05; ns: p \mjseqn > 0.05).

References

\insertAllCited

See Also

leveneTest

Examples


data("cassava_CC")
data("cassava_EC")

ec <- cbind(genotypes = rownames(cassava_EC), cassava_EC)
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL

core <- rownames(cassava_CC)

quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW",
           "ARSR", "SRDM")
qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
          "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
          "PSTR")

ec[, qual] <- lapply(ec[, qual],
                     function(x) factor(as.factor(x)))

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


EvaluateCore documentation built on July 3, 2022, 5:06 p.m.