18 citations · 31 across the 10 of their papers we have counts for
10 papers
Towards a Geometric Characterization of Multiverse Analysis
Giovanni Saraceno, Antonio Calcagnì
Multiverse analysis makes explicit how empirical conclusions depend on alternative, defensible analytical specifications. Standard approaches usually generate the multiverse first…
Non-ignorable fuzziness in granular counts: the case of RNA-seq data
Antonio Calcagnì, Arianna Consiglio, Przemyslaw Grzegorzewski +1
RNA-seq count data are often affected by read-to-gene alignment ambiguity, especially in high-dimensional transcriptomics. This type of ambiguity can be conveniently expressed thro…
Bayesianize Fuzziness in the Statistical Analysis of Fuzzy Data
Antonio Calcagnì, Przemysław Grzegorzewski, Maciej Romaniuk
Fuzzy data, prevalent in social sciences and other fields, capture uncertainties arising from subjective evaluations and measurement imprecision. Despite significant advancements i…
A novel CFA+EFA model to detect aberrant respondents
Niccolò Cao, Livio Finos, Luigi Lombardi +1
Aberrant respondents are common but yet extremely detrimental to the quality of social surveys or questionnaires. Recently, factor mixture models have been employed to identify ind…
Mixture polarization in inter-rater agreement analysis: a Bayesian nonparametric index
Giuseppe Mignemi, Antonio Calcagnì, Andrea Spoto +1
In several observational contexts where different raters evaluate a set of items, it is common to assume that all raters draw their scores from the same underlying distribution. Ho…
Post-selection Inference in Multiverse Analysis (PIMA): an inferential framework based on the sign flipping score test
Paolo Girardi, Anna Vesely, Daniël Lakens +4
When analyzing data researchers make some decisions that are either arbitrary, based on subjective beliefs about the data generating process, or for which equally justifiable alter…
Jointly modeling rating responses and times with fuzzy numbers: An application to psychometric data
Niccolò Cao, Antonio Calcagnì
In several research areas, ratings data and response times have been successfully used to unfold the stage-wise process through which human raters provide their responses to questi…
A probabilistic tree model to analyze fuzzy rating data
Antonio Calcagnì, Luigi Lombardi
In this contribution we provide initial findings to the problem of modeling fuzzy rating responses in a psychometric modeling context. In particular, we study a probabilistic tree…
Estimating latent linear correlations from fuzzy frequency tables
Antonio Calcagnì
This research concerns the estimation of latent linear or polychoric correlations from fuzzy frequency tables. Fuzzy counts are of particular interest to many disciplines including…
A Maximum Entropy Procedure to Solve Likelihood Equations
Antonio Calcagnì, Livio Finos, Gianmarco Altoè +1
In this article we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy approach. Unlike standard procedures that require eq…