activity
20092024
most citedEstimation of latent variable models for ordinal data via fully exponential Laplace approximation

25 citations · 44 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ME2024

The generalized Hausman test for detecting non-normality in the latent variable distribution of the two-parameter IRT model

Lucia Guastadisegni, Silvia Cagnone, Irini Moustaki +1

This paper introduces the generalized Hausman test as a novel method for detecting non-normality of the latent variable distribution of unidimensional Item Response Theory (IRT) mo…

stat.AP2016

Multilevel Models with Stochastic Volatility for Repeated Cross-Sections: an Application to tribal Art Prices

Silvia Cagnone, Simone Giannerini, Lucia Modugno

In this paper we introduce a multilevel specification with stochastic volatility for repeated cross-sectional data. Modelling the time dynamics in repeated cross sections requires…

stat.ME2015

Approximate likelihood inference in generalized linear latent variable models based on integral dimension reduction

Silvia Bianconcini, Silvia Cagnone, Dimitris Rizopoulos

Latent variable models represent a useful tool for the analysis of complex data when the constructs of interest are not observable. A problem related to these models is that the in…

stat.AP2013★ 1 cited

The Analysis of Tribal Art Prices: a Multilevel Model with Autoregressive Components

Lucia Modugno, Silvia Cagnone, Simone Giannerini

In this paper we propose a multilevel model specification with time series components for the analysis of prices of artworks sold at auctions. Since auction data do not constitute…

stat.ME2011★ 25 cited

Estimation of latent variable models for ordinal data via fully exponential Laplace approximation

Silvia Bianconcini, Silvia Cagnone

Latent variable models for ordinal data represent a useful tool in different fields of research in which the constructs of interest are not directly observable. In such models, pro…

stat.ME2010

A factor mixture analysis model for multivariate binary data

Silvia Cagnone, Cinzia Viroli

The paper proposes a latent variable model for binary data coming from an unobserved heterogeneous population. The heterogeneity is taken into account by replacing the traditional…

stat.AP2009★ 18 cited

A general multivariate latent growth model with applications in student careers Data warehouses

Silvia Bianconcini, Silvia Cagnone

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context the analysis of stud…