TestDimorph (version 0.4.0)

univariate_pairwise: post hoc univariate analysis to MANOVA

Description

post hoc univariate analysis to MANOVA

Usage

univariate_pairwise(x, out, padjust, digits, lower.tail, ...)

Arguments

x

A data frame containing summary statistics.

out

output of multivariate function

padjust

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

digits

Number of significant digits, Default: 4

lower.tail

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

...

Arguments passed on to multivariate

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

CI

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