hot.test | R Documentation |
This function performs Hotelling's T square test when the vector of coefficients and the variance-covariance matrix are provided
hot.test(kappa, var_kappa, a.level, NN)
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 |
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 |
This function performs Hotelling's T square test to compare dependent coefficients when the vector of coefficients and the variance-covariance matrix are provided.
$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
Sophie Vanbelle sophie.vanbelle@maastrichtuniversity.nl
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)
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