NMA (version 2.1-1)

global.ict: Higgins' global inconsistency test

Description

Higgins' global inconsistency test based on the design-by-treatment interaction model. REML-based Wald test for the all possible design-by-treatment interactions on the network is performed.

Usage

global.ict(x)

Value

The results of the global inconsistency test are prrovided.

• coding: A table that presents the correspondence between the numerical code and treatment categories (the reference category is coded as 1).

• reference: Reference treatment category.

• number of studies: Number of studies.

• designs: Study designs (combinations of treatments of individual trials) on the network.

• Coefficients of the design-by-treatment interaction model: Regression coefficients estimates and their SEs, 95% confidence intervals and P-values.

• Between-studies_SD: Between-studies SD estimate.

• Between-studies_COR: Between-studies correlation coefficient estimate (=0.50).

• X2-statistic: Chi-squared statistic of the global inconsistency test.

• df: Degree of freedom.

• P-value: P-value of the global inconsistency test.

Arguments

x

Output object of setup

References

Higgins, J. P., Jackson, D., Barrett, J. K., Lu, G., Ades, A. E., and White, I. R. (2012). Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Research Synthesis Methods 3, 98-110.

Jackson, D., Boddington, P., and White, I. R. (2016). The design-by-treatment interaction model: a unifying framework for modelling loop inconsistency in network meta-analysis. Research Synthesis Methods 7, 329-332.

White, I. R., Barrett, J. K., Jackson, D., and Higgins, J. P. (2012). Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression. Research Synthesis Methods 3, 111-125.

Examples

data(heartfailure)

hf2 <- setup(study=study,trt=trt,d=d,n=n,measure="OR",ref="Placebo",data=heartfailure)

global.ict(hf2)