univariate: Univariate Analysis Of Sexual Dimorphism

In bassam-abulnoor/TestDimorph: Analysis Of The Interpopulation Difference In Degree of Sexual Dimorphism Using Summary Statistics

Description

Calculation and visualization of the differences in degree sexual dimorphism between multiple populations using a modified one way ANOVA and summary statistics as input

Usage

univariate(
  x,
  Pop = 1,
  type_anova = "II",
  interact_anova = TRUE,
  es_anova = "none",
  pairwise = FALSE,
  padjust = "none",
  ...,
  lower.tail = FALSE,
  CI = 0.95,
  N = NULL,
  digits = 4
)

Arguments

x	A data frame containing summary statistics.
Pop	Number of the column containing populations' names, Default: 1
type_anova	type of ANOVA test "I","II" or "III", Default:"II".
interact_anova	Logical; if TRUE calculates interaction effect, Default: TRUE.
es_anova	Type of effect size either "f" for f squared,"eta" for eta squared or "none", Default:"none".
pairwise	Logical; if TRUE runs multiple pairwise comparisons on different populations using t_greene Default: FALSE
padjust	Method of p.value adjustment for multiple comparisons following p.adjust.methods Default: "none".
...	Additional arguments that could be passed to the t_greene function
lower.tail	Logical; if TRUE probabilities are 'P[X <= x]', otherwise, 'P[X > x]'., Default: FALSE
CI	confidence interval coverage takes value from 0 to 1, Default: 0.95.
N	Number of pairwise comparisons for [p.adjust.methods], if left 'NULL' it will follow the formula 'n(n 1)/2' where 'n' is the number of populations , Default: NULL
digits	Number of significant digits, Default: 4

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

Value

ANOVA tale.

Examples

# 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),
    M.mu = c(49.39, 48.33, 46.99, 45.20),
    M.sdev = c(3.01, 2.53, 2.47, 2.00),
    f = c(150.00, 58.00, 34.00, 24.00),
    F.mu = c(42.91, 42.89, 42.44, 40.90),
    F.sdev = c(2.90, 2.84, 2.26, 2.90)
  )
univariate(df, pairwise = TRUE, padjust = "bonferroni")

bassam-abulnoor/TestDimorph documentation built on Jan. 29, 2021, 8:21 a.m.