Skip to contents

Levene's Test

Source: R/levene.evaluate.core.R
levene.evaluate.core.Rd

Test for of variances of the entire collection (EC) and core set (CS) for quantitative traits by Levene's test (Levene 1960) .

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 ≤ 0.01; **: p ≤ 0.05; ns: p > 0.05).

References

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.

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)
#>    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                   *