hot.test: Hotelling's T square test

In svanbelle/multiagree: Comparaison of dependent kappa coefficients

Hotelling's T square test

Description

This function performs Hotelling's T square test when the vector of coefficients and the variance-covariance matrix are provided

Usage

hot.test(kappa, var_kappa, a.level, NN)

Arguments

kappa	a vector of length G with the coefficients to be compared
var_kappa	the G x G variance-covariance matrix of the coefficients. It can be provided in general or obtained with the delta.pair, the boot.pair, the boot.many1, the boot.many2, the delta.many1 and the delta.many2 functions in the kappa context.
a.level	the significance level
NN	the number of clusters if the delta method is used to determine the variance-covariance matrix or the number of bootstrap iterations if the bootstrap method is used

Details

This function performs Hotelling's T square test to compare dependent coefficients when the vector of coefficients and the variance-covariance matrix are provided.

Value

$kappa a G x 2 matrix with the coefficients in the first column and their corresponding standard error in the second column

$T_test a vector of length 2 with the value of Hotelling's T square test as first element and the corresponding p-value as second element

$confidence confidence intervals for the pairwise comparisons of the coefficients

$cor the G x G correlation matrix of the coefficients

Author(s)

Sophie Vanbelle [e-mail]

Examples

 
vect<-c(0.3,0.4,0.5)#vector of coefficients
v_c<-matrix(c(0.01,0.005,0.007,0.005,0.015,0.006,0.007,0.006,0.05),ncol=3)#variance-covariance matrix
hot.test(kappa=vect,var_kappa=v_c,a.level=0.05,NN=50)

svanbelle/multiagree documentation built on Feb. 9, 2023, 2:37 p.m.