van_vark {TestDimorph}

Graphical and statistical representation of dimorphism differences.

Description

Provides testing for differences in patterning of sexual dimorphism between populations, as well as for evolutionary trends that may characterize other species. The test is based on the computation of the first q canonical variates (q=2 by default) or multiple discriminant functions to develop various tests of sexual dimorphism in any two populations A and B.

Usage

van_vark(
  x,
  W = NULL,
  q = 2,
  Trait = 1,
  Pop = 2,
  plot = TRUE,
  lower.tail = FALSE,
  digits = 4
)

Arguments

x

A Data frame of means and sample sizes for different populations or a list of the summary data frame with Pooled within-group variance-covariance matrix.

W

Pooled within-group variance-covariance matrix supplied if x is a dataframe , Default:NULL

q

Number of canonical variates to retain for chi square test, Default: 2

Trait

number of column containing names of traits Default: 1.

Pop

Number of the column containing populations' names, Default: 2

plot

Logical; if TRUE returns a graphical representation of dimorphism differences, Default: TRUE

lower.tail

Logical; if TRUE probabilities are 'P[X <= x]', otherwise, 'P[X > x]'., Default: FALSE

digits

Number of significant digits, Default: 4

Details

Input is a data frame of means and sample sizes similar to Howells_summary with the same naming conventions used throughout the functions but with the standard deviation columns removed.

Value

The output includes a two-dimensional plot that illustrate the existing differences between tested populations and a statistical test of significance for the difference in dimorphism using chi square distribution.

Note

For plot labels to be fully visualized, maximizing image size is advised.

References

Van Vark, G. N., et al. "Some multivariate tests for differences in sexual dimorphism between human populations." Annals of human biology 16.4 (1989): 301-310.

Examples

# selecting means and sample sizes
van_vark_data <- Howells_summary[!endsWith(
  x = names(Howells_summary),
  suffix = "dev"
)]
# running the function
van_vark(van_vark_data, Howells_V)