sidesplit {NMA}

Sidesplitting for quantifying direct and indirect evidence for all possible treatment pairs and the inconsistency test

Description

Noma's sidesplitting for quantifying direct and indirect evidence for all possible treatment pairs based on network meta-regression and the inconsistency tests are performed. For the bias correction that causes the involvement of multi-arm trials, we adopted the adjustment method of Noma et al. (2017) and Noma (2023).

Usage

sidesplit(x)

Arguments

x

Output object of setup

Value

Results of the sidesplitting for all possible treatment pairs 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.

• Direct evidence: Summary estimates, SEs, 95% confidence intervals, and P-values for the direct evidence.

• Indirect evidence: Summary estimates, SEs, 95% confidence intervals, and P-values for the indirect evidence.

• Difference: Differences of the summary estimates of direct and indirect evidence, and their inconsistency tests.

References

Dias, S., Welton, N. J., Caldwell, D. M., and Ades, A. E. (2010). Checking consistency in mixed treatment comparison meta-analysis. Statistics in Medicine 29, 932-944.

Noma, H. (2023). Sidesplitting using network meta-regression. Jxiv, 493. doi:10.51094/jxiv.493.

Noma, H., Tanaka, S., Matsui, S., Cipriani, A., and Furukawa, T. A. (2017). Quantifying indirect evidence in network meta-analysis. Statistics in Medicine 36, 917-927.

Examples

data(smoking)

smk2 <- setup(study=study,trt=trt,d=d,n=n,measure="OR",ref="A",data=smoking)

sidesplit(smk2)