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RankAggregator (version 0.0.1)

consensusRankingBoot: Rank aggregation of partial rankings with optonal bootstrapping

Description

This funciton calls RankAggregator::consensusRanking to return a best consensus (or median) ranking for a set of (partial) rankings. This function also provides an optional bootstrap resampling procedure to give user-defined confidence intervals and average rank positions with the consensus ranking.

Usage

consensusRankingBoot(
  x,
  bootstrap,
  nboot = 10000,
  conf.int = 0.95,
  prog.upd = TRUE
)

Arguments

x

a data.frame containing columns titled Reviewer, Item, Ranking. On data structure, Reviewer and Item must be character, and Ranking must be numeric. Each row of x identifes the rank position that a single Reviewer awarded a single Item

bootstrap

a logical value indicating whether to bootstrap the rank aggregation procedure.

nboot

a numeric value for bootstrap replicates. Default value is 10000.

conf.int

a numeric value >0 and <1. Default value is 0.95, which sets confidence interval at 95% level.

prog.upd

a logical value indicating whether the user wants progress updates on the bootstrap procedure.

Value

If bootstrap is FALSE, a data.frame is returned, with two columns: Item and Rank.est, where Item is a Factor containing all unique Item's from the input data.frame x, and where Rank.est is the estimated (numeric) rank position based on the consensusRanking() rank aggregation procedure.#' If bootstrap is TRUE, a list is returned, with two elements:

  • $summaryTable is a data.frame with six columns: Item Rank.est, Rank.cilo, Rank.cihi, Rank.median, Rank.mean. Where Item and Rank.est are as described above, Rank.cilo and Rank.cihi are the estimates for the low and high confidence intervals, respectively. Rank.median and Rank.mean both describe the average rank positions.

  • $bootstrapData is an array containing estimated (numeric) rank positions based on the consensusRanking() rank aggregation procedure with resampled data. NA denotes estimated rankings that were discarded due to not containing all Items.

References

Cook, W.D., Golany, B., Penn, M. and Raviv, T., 2007. Creating a consensus ranking of proposals from reviewers partial ordinal rankings. Computers & Operations Research, 34, pp.954-965. Marshall, E.C., Sanderson, C., Spiegelhalter, D.J. and McKee, M., 1998. Reliability of league tables of in vitro fertilisation clinics: retrospective analysis of live birth ratesCommentary: How robust are rankings? The implications of confidence intervals. Bmj, 316, pp.1701-1705.

See Also

Calls the internal function consensusRanking, which calls the other internal functions evaluationMatrix, consensusRanking, extendRanking, lowerBound, upperBound