Test for of variances of the entire collection (EC) and core set (CS) for quantitative traits by Levene's test (Levene 1960) .
levene.evaluate.core(data, names, quantitative, selected)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.
Name of column with the individual names as a character string.
Name of columns with the quantitative traits as a character vector.
Character vector with the names of individuals selected in
core collection and present in the names column.
A data frame with the following columns
The quantitative trait.
The variance of the EC.
The variance of the CS.
The coefficient of variance of the EC.
The coefficient of variance of the CS.
The test statistic.
The p value for the test statistic.
The significance of the test statistic (*: p \(\leq\) 0.01; **: p \(\leq\) 0.05; ns: p \( > \) 0.05).
Levene H (1960). “Robust tests for equality of variances.” In Olkin I, Ghurye SG, Hoeffding W, Madow WG, Mann HB (eds.), Contribution to Probability and Statistics: Essays in Honor of Harold Hotelling, 278–292. Stanford University Press, Palo Alto, CA.
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)
#> Trait EC_V CS_V EC_CV CS_CV Levene_Fvalue Levene_pvalue
#> 1 NMSR 59.087307 66.982464 0.6557556 0.7513439 0.08138887 7.754559e-01
#> 2 TTRN 3.650995 5.168937 0.4957973 0.5784099 4.48085067 3.440983e-02
#> 3 TFWSR 20.545565 37.050176 0.8349124 0.9588343 9.73620667 1.834623e-03
#> 4 TTRW 2.745559 8.185938 0.8730338 1.0929363 32.17078669 1.635197e-08
#> 5 TFWSS 34.723261 52.465146 0.8487110 0.9348325 5.47834742 1.935920e-02
#> 6 TTSW 4.008444 9.527677 0.8385793 1.0057366 20.99595381 4.910026e-06
#> 7 TTPW 95.800602 158.740945 0.7911214 0.8937898 8.23203952 4.162436e-03
#> 8 AVPW 11.312159 29.789173 0.7848312 0.9597393 32.84901670 1.160456e-08
#> 9 ARSR 5.082044 3.862988 1.2132652 1.1545293 0.37336766 5.412494e-01
#> 10 SRDM 25.329950 18.184402 0.1332473 0.1130209 5.02652477 2.508002e-02
#> Levene_significance
#> 1 ns
#> 2 *
#> 3 **
#> 4 **
#> 5 *
#> 6 **
#> 7 **
#> 8 **
#> 9 ns
#> 10 *