Learn R Programming

PINMA (version 1.1-2)

KR: Kenward-Roger-type adjustment for constructing prediction intervals of network meta-analysis

Description

Kenward-Roger-type adjustment for constructing prediction intervals of network meta-analysis.

Usage

KR(y, S)

Value

Results of the Kenward-Roger-type adjustment for inference of multivariate random-effects model and prediction intervals for network meta-analysis.

  • Estimates: Restricted maximum likelihood (REML) estimates, their SE, and Wald-type 95% confidence intervals by the Kenward-Roger-type adjustment.

  • Between-studies_SD: Between-studies SD estimate.

  • 95%PI: 95% prediction intervals by the Kenward-Roger-type adjustment.

Arguments

y

Contrast-based summary data of the outcome measure

S

Covariance estimates of y

References

Noma, H., Hamura, Y., Sugasawa, S. and Furukawa, T. A. (2022+). Improved methods to construct prediction intervals for network meta-analysis. Forthcoming.

Examples

Run this code
data(dstr)
attach(dstr)

# Transforming the arm-level data to the contrast-based summaryies
edat <- data.edit(study,trt,d,n)

y <- edat$y
S <- edat$S

KR(y,S)    # Results of the NMA analysis (log OR scale)

Run the code above in your browser using DataLab