Function reference • aggreCAT

All functions
`AverageWAgg()`	Aggregation Method: AverageWAgg
`BayesianWAgg()`	Aggregation Method: BayesianWAgg
`confidence_score_evaluation()`	Confidence Score Evaluation
`confidence_score_heatmap()`	Confidence Score Heat Map
`confidence_score_ridgeplot()`	Confidence Score Ridge Plot
`data_comments`	data_comments
`data_confidence_scores`	Confidence Scores generated for 25 papers with 22 aggregation methods
`data_justifications`	Free-text justifications for expert judgements
`data_outcomes`	Replication outcomes for the papers
`data_ratings`	P1_ratings
`data_supp_priors`	A table of prior means, to be fed into the BayPRIORsAgg aggregation method
`data_supp_quiz`	A table of scores on the quiz to assess prior knowledge, to be fed into the QuizWAgg aggregation method
`data_supp_reasons`	Categories of reasons provided by participants for their expert judgements
`DistributionWAgg()`	Aggregation Method: DistributionWAgg
`ExtremisationWAgg()`	Aggregation Method: ExtremisationWAgg
`IntervalWAgg()`	Aggregation Method: IntervalWAgg
`LinearWAgg()`	Aggregation Method: LinearWAgg
`method_placeholder()`	Placeholder function with TA2 output
`postprocess_judgements()`	Post-processing.
`preprocess_judgements()`	Pre-process the data
`ReasoningWAgg()`	Aggregation Method: ReasoningWAgg
`ShiftingWAgg()`	Aggregation Method: ShiftingWAgg
`weight_asym()`	Weighting method: Asymmetry of intervals
`weight_interval()`	Weighting method: Width of intervals
`weight_nIndivInterval()`	Weighting method: Individually scaled interval widths
`weight_outlier()`	Weighting method: Down weighting outliers
`weight_reason()`	Weighting method: Total number of judgement reasons
`weight_reason2()`	Weighting method: Total number and diversity of judgement reasons
`weight_varIndivInterval()`	Weighting method: Variation in individuals’ interval widths

Reference

All functions