my_pValueF

<p>This is simply a wrapper around <code><a rd-options="" href="/link/pf?package=ffmanova&version=1.1.1" data-mini-rdoc="ffmanova::pf">pf</a></code>: <code>my_pValueF(f, ny1,
ny2)</code> is equivalent to <code>pf(f, ny1, ny2, lower.tail = FALSE)</code>.</p>

internal

htest

General linear modeling with multiple responses (MANCOVA). An overall p-value for each model term is calculated by the 50-50 MANOVA method by Langsrud (2002) <doi:10.1111/1467-9884.00320>, which handles collinear responses. Rotation testing, described by Langsrud (2005) <doi:10.1007/s11222-005-4789-5>, is used to compute adjusted single response p-values according to familywise error rates and false discovery rates (FDR). The approach to FDR is described in the appendix of Moen et al. (2005) <doi:10.1128/AEM.71.4.2086-2094.2005>. Unbalanced designs are handled by Type II sums of squares as argued in Langsrud (2003) <doi:10.1023/A:1023260610025>. Furthermore, the Type II philosophy is extended to continuous design variables as described in Langsrud et al. (2007) <doi:10.1080/02664760701594246>. This means that the method is invariant to scale changes and that common pitfalls are avoided.

Oyvind Langsrud

ffmanova

Fifty-Fifty MANOVA

<c3><98>yvind Langsrud

Bj<c3><b8>rn-Helge Mevik

my_pValueF function

<p>This is simply a wrapper around <code><a rd-options='' href='pf'>pf</a></code>: <code>my_pValueF(f, ny1,
ny2)</code> is equivalent to <code>pf(f, ny1, ny2, lower.tail = FALSE)</code>.</p>

my_pValueF: F-test p-values

Description

Usage

Arguments

Value

See Also