signtest.evaluate.core: Sign Test

In EvaluateCore: Quality Evaluation of Core Collections

Sign Test

Description

Test difference between means and variances of entire collection (EC) and core set (CS) for quantitative traits by Sign test (\mjseqn+ versus \mjseqn-) \insertCitebasigalup_development_1995,tai_core_2001EvaluateCore. \loadmathjax

Usage

signtest.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.

Details

The test statistic for Sign test (\mjseqn\chi^2) is computed as follows.

\mjsdeqn\chi

^2 = \frac(N_1-N_2)^2N_1+N_2

Where, where \mjseqnN_1 is the number of variables for which the mean or variance of the CS is greater than the mean or variance of the EC (number of \mjseqn+ signs); \mjseqnN_2 is the number of variables for which the mean or variance of the CS is less than the mean or variance of the EC (number of \mjseqn- signs). The value of \mjseqn\chi^2 is compared with a Chi-square distribution with 1 degree of freedom.

Value

A data frame with the following components.

Comparison	The comparison measure.
ChiSq	The test statistic (\mjseqn\chi^2).
p.value	The p value for the test statistic.
significance	The significance of the test statistic (*: p \mjseqn\leq 0.01; **: p \mjseqn\leq 0.05; ns: p \mjseqn > 0.05).

References

\insertAllCited

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)))

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

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