Cat_GG {homnormal}

Computational Approach Test for Homogeniety

Description

Tests the homogeniety of variances for more than two normal groups using standartized likelihood ratio test.

Usage

Cat_GG(x1, x2, alfa = 0.05, m = 2000, table = TRUE, graph = "none")

Arguments

x1

a numeric matrix containing the values of groups.

x2

numeric matrix containing the values of group numbers.

alfa

significance level of the test. Default number is 0.05.

m

number of resampling.

table

a logical variable that indicates table will appear or not. Default is TRUE.

graph

box plot of groups of raw or centered data.

Value

if table is TRUE, then it gives a detailed table, else it gives a vector of r value(r=1 when null hypothesis was rejected and r=0 when null hypothesis was accepted) p-value and test statistic value.

References

Gokpinar, E., & Gokpinar, F. (2017). Testing equality of variances for several normal populations. Communications in Statistics-Simulation and Computation, 46(1), 38-52.

See Also

Brown_Forsythe, bdai, Cat_LR, genp, slrt, levene

Examples

    data(FH_data)
   x1=FH_data$SurvivalTime
   x2=FH_data$HospitalNo
   Cat_GG(x1,x2)
   readline(prompt = "Pause. Press <Enter> to continue...")
   Cat_GG(x1,x2,alfa=0.10)
   readline(prompt = "Pause. Press <Enter> to continue...")
    Cat_GG(x1,x2,alfa=0.10,table=FALSE)
    readline(prompt = "Pause. Press <Enter> to continue...")
    Cat_GG(x1,x2,alfa=0.10,table=FALSE,graph="raw")
    readline(prompt = "Pause. Press <Enter> to continue...")
    Cat_GG(x1,x2,alfa=0.10,table=FALSE,graph="none")
# ---THIS VERSION IS ESPECIALLY USEFUL FOR COMPARISON STUDIES BY SIMULATION---
#    #first value of the vector is r value(r=1 when rejected and r=0 when accepted null hypothesis)
# second value of the vector is the p-value and third value is the tests statistic value