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13 changes: 13 additions & 0 deletions vignettes/references.bib
Original file line number Diff line number Diff line change
@@ -1,3 +1,16 @@
@article{chandler,
author = {Chandler, Conor O. and Proskorovsky, Irina},
title = {Uncertain about uncertainty in matching-adjusted indirect comparisons? A simulation study to compare methods for variance estimation},
journal = {Research Synthesis Methods},
volume = {15},
number = {6},
pages = {1094-1110},
keywords = {bootstrap, matching-adjusted indirect comparison, robust sandwich estimator, simulation study, uncertainty, variance},
doi = {https://doi.org/10.1002/jrsm.1759},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jrsm.1759},
year = {2024}
}

@article{Bucher,
title = {The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials},
journal = {Journal of Clinical Epidemiology},
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4 changes: 4 additions & 0 deletions vignettes/unanchored_binary.Rmd
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Expand Up @@ -162,3 +162,7 @@ result_boot <- maic_unanchored(

result_boot$inferential$fit$boot_res_AB
```

Note that the bootstrap in unanchored analysis only uses resampling of internal IPD trial population and assumes there is no uncertainty in the comparator trial population (i.e. estimated mean outcomes). [@chandler] Therefore, we recommend the use of sandwich estimators for the variance calculation in the unanchored analysis.

# References
4 changes: 4 additions & 0 deletions vignettes/unanchored_survival.Rmd
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Expand Up @@ -165,3 +165,7 @@ result_boot <- maic_unanchored(

result_boot$inferential$fit$boot_res_AB
```

Note that the bootstrap in unanchored analysis only uses resampling of internal IPD trial population and assumes there is no uncertainty in the comparator trial population (i.e. estimated mean outcomes). [@chandler] Therefore, we recommend the use of sandwich estimators for the variance calculation in the unanchored analysis.

# References
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