t_greene {TestDimorph}

Greene t test of Sexual Dimorphism

Description

Calculation and visualization of the differences in degree sexual dimorphism between two populations using summary statistics as input.

Usage

t_greene(
  x,
  Pop = 1,
  plot = FALSE,
  colors = c("#DD5129", "#985F51", "#536D79", "#0F7BA2", "#208D98", "#319F8E", "#43B284",
    "#7FB274", "#BCB264", "#FAB255"),
  alternative = c("two.sided", "less", "greater"),
  padjust = "none",
  letters = FALSE,
  digits = 4,
  CI = 0.95
)

Arguments

x

A data frame containing summary statistics.

Pop

Number of the column containing populations' names, Default: 1

plot

Logical; if TRUE graphical matrix of p values, Default: FALSE

colors

color palette used in the corrplot

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided", "greater" or "less", Default:"two.sided"

padjust

Method of p.value adjustment for multiple comparisons following p.adjust Default: "none".

letters

Logical; if TRUE returns letters for pairwise comparisons where significantly different populations are given different letters, Default: FALSE'

digits

Number of significant digits, Default: 4

CI

confidence interval coverage takes value from 0 to 1, Default: 0.95.

Details

The input is a data frame of summary statistics where the column containing population names is chosen by position (first by default), other columns of summary data should have specific names (case sensitive) similar to baboon.parms_df.For the visualization of pairwise comparisons using the corrplot, the rounder the image in the plot grid the lower the p-value (see the color scale for similar information). The default colors used in the corrplot are from the "MetBrewer" "Egypt" palette which is listed under the "colorblind_palettes". Different colors palettes can be selected from "RColorBrewer" package.

Value

data frame of t.test results

References

# for the t-test

Greene, David Lee. "Comparison of t-tests for differences in sexual dimorphism between populations." American Journal of Physical Anthropology 79.1 (1989): 121-125.

Relethford, John H., and Denise C. Hodges. "A statistical test for differences in sexual dimorphism between populations." American Journal of Physical Anthropology 66.1 (1985): 55-61.

#For the femur head diameter data

F. Curate, C. Umbelino, A. Perinha, C. Nogueira, A.M. Silva, E. Cunha, Sex determination from the femur in Portuguese populations with classical and machinelearning classifiers, J. Forensic Leg. Med. (2017) , doi:http://dx.doi.org/10.1016/j. jflm.2017.08.011.

O. Gulhan, Skeletal Sexing Standards of Human Remains in Turkey (PhD thesis), Cranfield University, 2017 [Dataset].

P. Timonov, A. Fasova, D. Radoinova, A.Alexandrov, D. Delev, A study of sexual dimorphism in the femur among contemporary Bulgarian population, Euras. J. Anthropol. 5 (2014) 46–53.

E.F. Kranioti, N. Vorniotakis, C. Galiatsou, M.Y. Iscan , M. Michalodimitrakis, Sex identification and software development using digital femoral head radiographs, Forensic Sci. Int. 189 (2009) 113.e1–7.

Examples

# Comparisons of femur head diameter in four populations
df <- data.frame(
  Pop = c("Turkish", "Bulgarian", "Greek", "Portuguese"),
  m = c(150.00, 82.00, 36.00, 34.00),
  f = c(150.00, 58.00, 34.00, 24.00),
  M.mu = c(49.39, 48.33, 46.99, 45.20),
  F.mu = c(42.91, 42.89, 42.44, 40.90),
  M.sdev = c(3.01, 2.53, 2.47, 2.00),
  F.sdev = c(2.90, 2.84, 2.26, 2.90)
)
t_greene(
  df,
  plot = TRUE,
  padjust = "none"
)