Algorithmic Parameterization of Mixed Treatment Comparisons

G van Valkenhoef, TP Tervonen, B de Brock, HL Hillege

Research output: Contribution to journalArticleAcademicpeer-review

24 Citations (Scopus)
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Mixed Treatment Comparisons (MTCs) enable the simultaneous meta-analysis (data pooling) of networks of clinical trials comparing ?2 alternative treatments. Inconsistency models are critical in MTC to assess the overall consistency between evidence sources. Only in the absence of considerable inconsistency can the results of an MTC (consistency) model be trusted. However, inconsistency model specification is non-trivial when multi-arm trials are present in the evidence structure. In this paper, we define the parameterization problem for inconsistency models in mathematical terms and provide an algorithm for the generation of inconsistency models. We evaluate running-time of the algorithm by generating models for 15 published evidence structures.
Original languageEnglish
Pages (from-to)1099-1111
Number of pages13
JournalStatistics and Computing
Issue number5
Publication statusPublished - 2012

Research programs

  • EUR ESE 32


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