nmareg function

Network meta-regression based on contrast-based approach

Network meta-regression based on contrast-based approach

Network meta-regression based on contrast-based approach using the multivariate meta-regression model. Effect modifications by study-level covariates (specified in the setup function) can be assessed. In many network meta-analysis, some treatment contrasts involve only 1 or 2 (or 0) direct comparisons, and the regression coefficients of the corresponding outcomes cannot be validly estimated (non-identifiable). Thus, the nmareg function can specify a subset of outcome variables to be modelled by the regression model (to be assessed the effect modifications) by treats. Currently, the parameter estimation is performed by the ordinary REML method.

nmareg(x, z, treats)

Arguments

  • x: Output object of setup
  • z: Covariate name vector
  • treats: A vector that specifies treatments to be assessed effect modifications that correspond to the elements of outcome vectors y in x (please specify the treatment numbers of coding; multiple outcomes can be specified jointly, as a vector).

Returns

Results of the network meta-regression analysis are presented.

  • coding: A table that presents the correspondence between the numerical code and treatment categories (the reference category is coded as 1).
  • Covariates: Covariate that specified in setup.
  • Outcome evaluated the effect modifications: Treatment contrasts that the effect modifications are evaluated.
  • Coefficients: Estimates, their SEs, Wald-type 95% confidence intervals, and P-values for the regression parameters (cons: intercept, beta: regression coefficient for the explanatory variable).
  • Between-studies_SD: Between-studies SD (tau) estimate.
  • Between-studies_COR: Between-studies correlation coefficient (should be 0.50).

References

Nikolakopoulou, A., White, I. R., Salanti, G. (2021). Network meta-analysis. In: Schmid, C. H., Stijnen, T., White, I. R., eds. Handbook of Meta-Analysis. CRC Press; pp. 187-217.

Noma, H., Hamura, Y., Gosho, M., and Furukawa, T. A. (2023). Kenward-Roger-type corrections for inference methods of network meta-analysis and meta-regression. Research Synthesis Methods 14 , 731-741.

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,z=c(SBP,DBP,pubyear),measure="OR",
ref="Placebo",data=heartfailure)

nmareg(hf2,z=SBP,treats=3)
nmareg(hf2,z=c(SBP,DBP),treats=c(3,4,6))
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