multivariate: Multivariate Analysis Of Sexual Dimorphism

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

Description

Multivariate extension of Greene t test t_greene

Usage

multivariate(
  x,
  R.res = NULL,
  Trait = 1,
  Pop = 2,
  type_manova = "II",
  manova_test_statistic = "W",
  interact_manova = TRUE,
  es_manova = "none",
  univariate = FALSE,
  padjust = "none",
  ...,
  lower.tail = FALSE,
  CI = 0.95,
  digits = 4
)

Arguments

x	Data frame or list containing summary statistics for multiple parameters measured in both sexes in two or more populations.
R.res	Pooled within correlational matrix, Default: NULL
Trait	Number of the column containing names of measured parameters, Default: 1
Pop	Number of the column containing populations' names, Default: 2
type_manova	type of MANOVA test "I","II" or "III", Default:"II".
manova_test_statistic	type of test statistic used either "W" for "Wilks","P" for "Pillai", "HL" for "Hotelling-Lawley" or "R" for "Roy's largest root", Default: "W".
interact_manova	Logical; if TRUE calculates MANOVA for the interaction effects,Default: TRUE.
es_manova	effect size either ,"eta" for eta squared, or "none"for not reporting an effect size, Default:"none".
univariate	Logical; if TRUE conducts multiple univariate analyses on different parameters separately, Default: FALSE
padjust	Method of p.value adjustment for multiple comparisons following p.adjust.methods Default: "none".
...	Additional arguments that could be passed to univariate
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.
digits	Number of significant digits, Default: 4

Details

Data can be entered either as a data frame of summary statistics as in baboon.parms_df. In that case the pooled within correlational matrix 'R.res' should be entered as a separate argument as in baboon.parms_R. Another acceptable format is a named list of matrices containing different summary statistics as well as the correlational matrix as in baboon.parms_list. By setting the option 'univariate' to 'TRUE', multiple 'ANOVA's can be run on each parameter independently with the required p.value correction using p.adjust.methods.

Value

MANOVA table. When the term is followed by '(E)' an exact f-value is calculated.

Examples

# x is a data frame with separate correlational matrix
library(TestDimorph)
multivariate(baboon.parms_df, R.res = baboon.parms_R)
# x is a list with the correlational matrix included
library(TestDimorph)
multivariate(baboon.parms_list, univariate = TRUE, padjust = "bonferroni")
# reproduces results from Konigsberg (1991)
multivariate(baboon.parms_df, R.res = baboon.parms_R)[3, ]
multivariate(baboon.parms_df, R.res = baboon.parms_R, interact_manova = FALSE)

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