TwoSamplesHT2 {MVTests}

Two Independent Samples Hotelling T^2 Test

Description

TwoSamplesHT2 function computes Hotelling T^2 statistic for two independent samples and gives confidence intervals.

Usage

TwoSamplesHT2(data, group, alpha = 0.05, Homogenity = TRUE)

Arguments

data

a data frame.

group

a group vector consisting of 1 and 2 values.

alpha

Significance Level that will be used for confidence intervals. default=0.05

Homogenity

a logical argument. If sample covariance matrices are homogeneity,then Homogenity=TRUE. Otherwise Homogenity=FALSE The homogeneity of covariance matrices can be investigated with BoxM function.

Details

This function computes two independent samples Hotelling T^2 statistics that is used to test whether two population mean vectors are equal to each other. When H0 is rejected, this function computes confidence intervals for all variables to determine variable(s) affecting on rejection decision. Moreover, when covariance matrices are not homogeneity, the approach proposed by D. G. Nel and V. D. Merwe (1986) is used.

Value

a list with 8 elements:

HT2

The value of Hotelling T^2 Test Statistic

F

The value of F Statistic

df

The F statistic's degree of freedom

p.value

p value

CI

The lower and upper limits of confidence intervals obtained for all variables

alpha

The alpha value using in confidence intervals

Descriptive1

Descriptive Statistics for the first group

Descriptive2

Descriptive Statistics for the second group

Author(s)

Hasan BULUT <[e-mail]>

References

Rencher, A. C. (2003). Methods of multivariate analysis (Vol. 492). John Wiley & Sons.

Tatlidil, H. (1996). Uygulamali Cok Degiskenli Istatistiksel Yontemler. Cem Web.

D.G. Nel & C.A. Van Der Merwe (1986) A solution to the multivariate behrens fisher problem, Communications in Statistics:Theory and Methods, 15:12, 3719-3735

Examples

data(iris)
G<-c(rep(1,50),rep(2,50))
# When covariances matrices are homogeneity
results1 <- TwoSamplesHT2(data=iris[1:100,1:4],group=G,alpha=0.05)
summary(results1)
# When covariances matrices are not homogeneity
results2 <- TwoSamplesHT2(data=iris[1:100,1:4],group=G,Homogenity=FALSE)
summary(results2)