TestDimorph (version 0.4.0)

aov_ss: Sex Specific One way ANOVA From Summary statistics

Description

Calculates sex specific one way ANOVA from summary statistics.

Usage

aov_ss(
  x,
  Pop = 1,
  pairwise = TRUE,
  letters = FALSE,
  es_anova = "none",
  digits = 4,
  CI = 0.95
)

Arguments

x

A data frame containing summary statistics.

Pop

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

pairwise

Logical; if TRUE runs multiple pairwise comparisons on different populations using Tukey's post hoc test, Default: TRUE

letters

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

es_anova

Type of effect size either "f" for f squared,"eta" for eta squared or "none", Default:"none".

digits

Number of significant digits, Default: 4

CI

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

Value

Sex specific ANOVA tables and pairwise comparisons in tidy format.

Details

Data is entered as 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

Examples

# NOT RUN {
# Comparisons of femur head diameter in four populations
library(TestDimorph)
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)
)
aov_ss(x = df)
# }