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gemtc (version 0.3)

mtc.anohe: Analysis of heterogeneity (ANOHE)

Description

(EXPERIMENTAL) Generate an analysis of heterogeneity for the given network. Three types of model are estimated: unrelated study effects, unrelated mean effects, and consistency. Output of the summary function can passed to plot for a visual representation.

Usage

mtc.anohe(network, likelihood=NULL, link=NULL, ...)

Arguments

network
An object of S3 class mtc.network.
likelihood
The likelihood to be used (see mtc.model).
link
The link function to be used (see mtc.model).
...
Arguments to be passed to mtc.run.

Value

  • For mtc.anohe: an object of class mtc.anohe. This is a list with the following elements:
  • result.useThe result for the USE model (see mtc.run).
  • result.umeThe result for the UME model (see mtc.run).
  • result.consThe result for the consistency model (see mtc.run).
  • For summary: an object of class mtc.anohe.summary. This is a list with the following elements:
  • cons.modelGenerated consistency model.
  • studyEffectsStudy-level effect summaries (multi-arm trials downweighted).
  • pairEffectsPair-wise pooled effect summaries (from the UME model).
  • consEffectsConsistency effect summaries.
  • indEffectsIndirect effect summaries (back-calculated).
  • isquared.compPer-comparison I-squared statistics.
  • isquared.globGlobal I-squared statistics.

encoding

utf8

Details

mtc.anohe returns the MCMC results for all three types of model. To get appropriate summary statistics, call summary() on the results object. The summary can be plotted.

See Also

mtc.run