Antonio Calcagnì

University of Padova

> Research
Speaking
Teaching
Contacts

Ongoing projects

Modeling non-random uncertainty in statistical models
§ Conditional sampling schema for continuous fuzzy numbers
§ Fuzzy topic models for short texts [code]
Analysing post-sampling uncertainty in social survey data
§ Decoupling measurement error information by mixing errors

Selected publications

Research profile: Scopus | zbMATH | ArXiv

A novel CFA+EFA model to detect aberrant respondents
Cao N., Finos L., Lombardi L., Calcagnì A.
Journal of the Royal Statistical Society Series C, 2024
[link] [pdf] [arxiv] [code]

A Bayesian Modeling Approach to Fuzzy Data Analysis
Calcagnì A., Grzegorzewski P.
Proceedings of SMPS, 2024
[link] [pdf]

Post-selection Inference in Multiverse Analysis (PIMA): An Inferential Framework Based on the Sign Flipping Score Test
Girardi P., Vesely A., Lakens D., Altoè G., Pastore M., Calcagnì A., Finos L.
Psychometrika, 2024
[link] [pdf] [arxiv]

Mixture polarization in inter-rater agreement analysis: A Bayesian nonparametric index
Mignemi G., Calcagnì A., Spoto A., Manolopoulou I.
Statistical Methods & Applications, 2024
[link] [pdf] [arxiv]

Estimating latent linear correlations from fuzzy frequency tables
Calcagnì A.
Communications in Mathematics and Statistics, 2022
[link] [pdf] [arxiv] [code]

A probabilistic tree model to analyze fuzzy rating data
Calcagnì A., Lombardi L.
Proocedings of IPMU, 2022
[link] [pdf] [arxiv] [code]

Jointly modeling rating responses and times with fuzzy numbers
Cao N., Calcagnì A.
Mathematics, 2022
[link] [pdf] [arxiv] [code]

A psychometric modeling approach to fuzzy rating data
Calcagnì A., Cao N., Rubaltelli E., Lombardi L.
Fuzzy Sets and Systems, 2022
[link] [pdf] [arxiv] [code]

Modeling random and non-random decision uncertainty in ratings data
Calcagnì A., Lombardi L.
AStA Advances in Statistical Analysis, 2021
[link] [pdf] [arxiv] [code]

A State Space Approach to Dynamic Modeling of Mouse-Tracking Data
Calcagnì A., Lombardi L., D'Alessandro M., Freuli F.
Frontiers in Psychology: Quantitative Psychology and Measurement, 2019
[link] [pdf] [code]

A Maximum Entropy Procedure to Solve Likelihood Equations
Calcagnì A., Finos L., Altoè G., Pastore M.
Entropy, 2019
[link] [pdf] [arxiv] [code]

Multiple mediation analysis for interval-valued data
Calcagnì A., Lombardi L., Avanzi L., Pascali E.
Statistical Papers, 2017
[link] [pdf] [code]

Deriving optimal data-analytic regimes from benchmarking studies
Doove L.L., Wilderjans T.F., Calcagnì A., Van Mechelen I.
Computational Statistics and Data Analysis, 2017
[link] [pdf]

A dimension reduction technique for two-mode non-convex fuzzy data
Calcagnì A., Lombardi L., Pascali E.
Soft Computing, 2016
[link] [pdf] [code]

Generalized cross entropy method for analysing the SERVQUAL model
Ciavolino E., Calcagnì A.
Journal of Applied Statistics, 2015
[link] [pdf]

A fuzzy set theory based computational model to represent the quality of inter-rater agreement
Ciavolino E., Salvatore S., Calcagnì A.
Quality & Quantity, 2014
[link] [pdf]

A generalized maximum entropy (GME) approach for crisp-input/fuzzy-output regression model
Ciavolino E., Calcagnì A.
Quality & Quantity, 2014
[link] [pdf]

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