pairwiseHR: Computation of log hazard ratio estimate and its standard...

In survNMA: Network Meta-Analysis Combining Survival and Count Outcomes

Computation of log hazard ratio estimate and its standard error estimate from dichotomized dataset

Description

Log hazard ratio estimate and its standard error estimate are calculated from dichotomized dataset simultaneously.

Usage

pairwiseHR(treat, studlab, event, n, data)

Arguments

treat	The treatments of individual arms.
studlab	ID variable of studies.
event	The number of events of individual arms.
n	The number of sample size of individual arms.
data	The dataset object.

Value

• studlab: ID variable of studies.

• treat1: The treatment of arm 1.

• treat2: The treatment of arm 2.

• TE: The log hazard ratio estimate.

• seTE: Standard error estimate for the log hazard ratio.

• n1: The sample size of arm 1.

• n2: The sample size of arm 2.

References

Noma, H. and Maruo, K. (2025). Network meta-analysis combining survival and count outcome data: A simple frequentist approach. medRxiv: 10.1101/2025.01.23.25321051.

Salika, T., Turner, R. M., Fisher, D., Tierney, J. F. and White, I. R. (2022). Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews. BMC Medical Research Methodology 22, 73.

Examples

data(woods2)

pairwiseHR(treat, studlab=study, event=d, n, data=woods2)

survNMA documentation built on April 3, 2025, 6:02 p.m.