Ztest: Wald's test on the Concordance Correlation Coefficient

In cccrm: Concordance Correlation Coefficient for Repeated (and Non-Repeated) Measures

Wald's test on the Concordance Correlation Coefficient

Description

Wald's test is applied to assess whether the CCC (ICC) is greater than a reference value. Additionally, Wald's test is also used to compare two independent CCC (ICC).

Usage

Ztest(cccfit, cccfit2 = NULL, r0 = 0, info = TRUE)

Arguments

cccfit	An object of class ccc.
cccfit2	An object of class ccc.
r0	Integer. Null hypothesis value.
info	Logical. Should information about the transformation used be printed?

Details

If only one ccc is provided, the function runs a one sided test to the null hypothesis value

\rho_0

.

z=\frac{\hat{\theta}-\rho_0}{SE\left(\hat{\theta}\right)}

where

\hat{\theta}

stands for the CCC estimate and

SE\left(\hat{\theta}\right)

its standard error. If a second CCC is provided, the function runs a two-sided test to the null hypothesis of equality of CCCs.

z=\frac{\hat{\theta_1}-\hat{\theta_2}}{\sqrt{Var\left(\hat{\theta_1}\right)}+Var\left(\hat{\theta_2}\right)}

. In both cases, the p-value is computed as

P\left(X>z\right)

where X follows a standard Normal distribution. The test uses the transformation indicated when the ccc object was generated.

Value

A data frame with two columns: Z, the statistical test value; and the P-value associated.

Examples

# Testing the CCC is above 0.8
ccc_mc=ccc_vc(bpres,"DIA","ID","METODE")
ccc_mc
Ztest(ccc_mc,r0=0.8)

# Comparing two CCC

bpres_Male <- bpres |> dplyr::filter(SEXO==1)
bpres_Female <- bpres |> dplyr::filter(SEXO==2)

ccc_DIA_Male=ccc_vc(bpres_Male,"DIA","ID","METODE")
ccc_DIA_Female=ccc_vc(bpres_Female,"DIA","ID","METODE")
Ztest(ccc_DIA_Male,ccc_DIA_Female)

cccrm documentation built on Oct. 19, 2024, 9:06 a.m.