global.ict {NMA}

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)

Arguments

x

Output object of setup

Value

Results of the global inconsistency test are presented.

• 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.

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.

Examples

data(heartfailure)

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

global.ict(hf2)