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wiki:synthesis:quantitative:methods [2022/06/30 18:36]
kholub 		wiki:synthesis:quantitative:methods [2023/09/07 12:56] (current)
jthurnham [Data Analyzed]
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 ===== Data Analyzed ===== ===== Data Analyzed =====
  
-Any study included (adjudicated, in dual screening) during [[:wiki:autolit:screening|]] and with Extraction was marked "Complete" is analyzed on QNS. If dual extraction is configured for the nest, only adjudicated data is analyzed in QNS.+Any study included (adjudicated, in dual screening) during [[:wiki:autolit:screening|]] and with [[:wiki:autolit:meta_analytical_extraction|extraction]] marked "Complete" is analyzed on QNS. If dual extraction is configured for the nest, only adjudicated data is analyzed in QNS. 
  
 ===== Analyses ===== ===== Analyses =====
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 For medians, pooled estimates & inferentials are computed as the Weighted Median of Medians, described in [[https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8013|McGrath et al.]] For medians, pooled estimates & inferentials are computed as the Weighted Median of Medians, described in [[https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8013|McGrath et al.]]
 +
 +=== Sources of Computational Methods ===
  
 All computational methods are implemented as a transcription, with minor modifications, of the peer-reviewed work in the R packages [[https://CRAN.R-project.org/package=meta|meta]], [[https://CRAN.R-project.org/package=metafor|metafor]], and [[https://CRAN.R-project.org/package=metamedian|metamedian]]. As these are open source, our modifications are open source, made publicly available for audit & modification in the Javascript package [[https://github.com/holub008/shukra|shukra]]. Pooled estimates specifically are computed by the [[https://github.com/holub008/shukra/blob/master/src/pooling.js|pooling module]]. To ensure correctness, all methods in shukra, and therefore used in QNS, are [[https://github.com/holub008/shukra/blob/master/test/test_pooling.js|tested]] for equality to estimates computed in the upstream packages. All computational methods are implemented as a transcription, with minor modifications, of the peer-reviewed work in the R packages [[https://CRAN.R-project.org/package=meta|meta]], [[https://CRAN.R-project.org/package=metafor|metafor]], and [[https://CRAN.R-project.org/package=metamedian|metamedian]]. As these are open source, our modifications are open source, made publicly available for audit & modification in the Javascript package [[https://github.com/holub008/shukra|shukra]]. Pooled estimates specifically are computed by the [[https://github.com/holub008/shukra/blob/master/src/pooling.js|pooling module]]. To ensure correctness, all methods in shukra, and therefore used in QNS, are [[https://github.com/holub008/shukra/blob/master/test/test_pooling.js|tested]] for equality to estimates computed in the upstream packages.
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 Direct effects are computed as Mean Differences (continuous data elements) or Odds Ratios (dichotomous data elements) between all pairs of within-study arms. Consistent indirect effects are computed using the Aitken estimator (described in [[https://journals.sagepub.com/doi/10.1177/0962280211432220|Senn et. al]]), with an pairwise-effect weighting correction for multi (3+) arm studies (described in [[https://onlinelibrary.wiley.com/doi/10.1002/sim.6236|Rücker et. al, 2014]]). For full details on computation of the Aitken estimator see [[https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1058|Rücker et. al, 2012]]. When random effects are specified, between-study variance is estimated using the DerSimonian-Laird estimator. All inferential statistics, at the study (used in forest plots) and intervention level, are computed using Normal approximations (logit transformed, for dichotomous data) on the consistent treatment effects. Intervention rankings are computed with P-scores, described in [[https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-015-0060-8|Rücker and Schwarzer, 2015]]. Direct effects are computed as Mean Differences (continuous data elements) or Odds Ratios (dichotomous data elements) between all pairs of within-study arms. Consistent indirect effects are computed using the Aitken estimator (described in [[https://journals.sagepub.com/doi/10.1177/0962280211432220|Senn et. al]]), with an pairwise-effect weighting correction for multi (3+) arm studies (described in [[https://onlinelibrary.wiley.com/doi/10.1002/sim.6236|Rücker et. al, 2014]]). For full details on computation of the Aitken estimator see [[https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1058|Rücker et. al, 2012]]. When random effects are specified, between-study variance is estimated using the DerSimonian-Laird estimator. All inferential statistics, at the study (used in forest plots) and intervention level, are computed using Normal approximations (logit transformed, for dichotomous data) on the consistent treatment effects. Intervention rankings are computed with P-scores, described in [[https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-015-0060-8|Rücker and Schwarzer, 2015]].
 +
 +Funnel plots are generated using all contrasts available on the selected intervention. "Comparison-adjusted" effects ([[https://doi.org/10.1371/journal.pone.0076654|Chaimani et. al]]) center all direct effects at a common value using their summary effect estimates, making trending and symmetry analysis feasible on the plot.
 +
 +=== Sources of Computational Methods ===
  
 All computational methods are implemented as a transcription, with modification, of the peer-reviewed work in the R packages [[https://CRAN.R-project.org/package=netmeta|netmeta]] and [[https://CRAN.R-project.org/package=metafor|metafor]]. As these are open source, our modifications are open source, made publicly available for audit & modification in the Javascript package [[https://github.com/holub008/shukra|shukra]]. NMAs specifically are computed by the [[https://github.com/holub008/shukra/blob/master/src/nma.js|nma module]]. To ensure correctness, all methods in shukra, and therefore used in QNS, are [[https://github.com/holub008/shukra/blob/master/test/test_nma.js|tested]] for equality to estimates computed in the upstream packages. All computational methods are implemented as a transcription, with modification, of the peer-reviewed work in the R packages [[https://CRAN.R-project.org/package=netmeta|netmeta]] and [[https://CRAN.R-project.org/package=metafor|metafor]]. As these are open source, our modifications are open source, made publicly available for audit & modification in the Javascript package [[https://github.com/holub008/shukra|shukra]]. NMAs specifically are computed by the [[https://github.com/holub008/shukra/blob/master/src/nma.js|nma module]]. To ensure correctness, all methods in shukra, and therefore used in QNS, are [[https://github.com/holub008/shukra/blob/master/test/test_nma.js|tested]] for equality to estimates computed in the upstream packages.
  
  
wiki/synthesis/quantitative/methods.1656614199.txt.gz · Last modified: 2022/06/30 18:36 by kholub

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