Remarkable properties for diagnostics and inference of ranking data modelling
From MaRDI portal
Publication:6126889
DOI10.1111/bmsp.12260MaRDI QIDQ6126889
Cristina Mollica, Luca Tardella
Publication date: 10 April 2024
Published in: British Journal of Mathematical and Statistical Psychology (Search for Journal in Brave)
bootstrapPlackett-Luce modelranking dataheuristic methodsgoodness-of-fit assessmentLuce's choice Axiom
Cites Work
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- A scaled difference chi-square test statistic for moment structure analysis
- Models for paired comparison data: a review with emphasis on dependent data
- Statistical methods for ranking data
- Mixtures of weighted distance-based models for ranking data with applications in political studies
- A mixture of experts model for rank data with applications in election studies
- Probability models on rankings
- Estimating the dimension of a model
- A comparison of truncated and time-weighted Plackett-Luce models for probabilistic forecasting of Formula One results
- Bayesian Plackett-Luce mixture models for partially ranked data
- Posterior predictive \(p\)-values
- Limited information estimation and testing of Thurstonian models for preference data
- Bayesian analysis of order-statistics models for ranking data
- Limited information goodness-of-fit testing in multidimensional contingency tables
- Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling
- Bayesian analysis of ranking data with the extended Plackett-Luce model
- Permutation probabilities for gamma random variables
- NON-NULL RANKING MODELS. I
- A Biometrics Invited Paper. Science, Statistics, and Paired Comparisons
- PLMIX: an R package for modelling and clustering partially ranked data
- Revealing Subgroup Structure in Ranked Data Using a Bayesian WAND
- Expert Elicitation of Adversary Preferences Using Ordinal Judgments
- Multistage Ranking Models
- Post-Processing Posterior PredictivepValues