Silvia Cagnone
University of Bologna
StatisticsOrdinal regressionCovariateMathematical optimizationGoodness of fitEconometricsArtificial intelligencePsychologyAutoregressive modelMultivariate statisticsExpectation–maximization algorithmAdaptive quadratureInferenceApplied mathematicsMathematicsComputer scienceLatent variableMultilevel modelLatent variable modelLatent class modelStructural equation modelingStochastic volatilityOrdinal dataLikelihood function
75Publications
9H-index
287Citations
Publications 73
Newest
#1L. Guastadisegni (UNIBO: University of Bologna)
#2Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
Last. Vassilis G. S. Vasdekis (OPA: Athens University of Economics and Business)H-Index: 13
view all 4 authors...
This paper studies the Type I error, false positive rates, and power of four versions of the Lagrange Multiplier test to detect measurement non-invariance in Item Response Theory (IRT) models for binary data under model misspecification. The tests considered are the Lagrange Multiplier test computed with the Hessian and cross-product approach, the Generalized Lagrange Multiplier test and the Generalized Jackknife Score test. The two model misspecifications are those of local dependence among ite...
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#1Silvia Bianconcini (UNIBO: University of Bologna)H-Index: 9
#2Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
Cognitive functioning is a key indicator of overall individual health. Identifying factors related to cognitive status, especially in later life, is of major importance. We concentrate on the analysis of the temporal evolution of cognitive abilities in the elderly population. We propose to model the individual cognitive functioning as a multidimensional latent process that accounts also for the effects of individual-specific characteristics (gender, age, and years of education). The proposed mod...
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#2Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
Last. Vassilis G. S. Vasdekis (OPA: Athens University of Economics and Business)H-Index: 13
view all 4 authors...
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#1Silvia Bianconcini (UNIBO: University of Bologna)H-Index: 9
#2Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
Source
#1Silvia BianconciniH-Index: 9
#2Silvia CagnoneH-Index: 9
#1Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
#2Cinzia Viroli (UNIBO: University of Bologna)H-Index: 15
Alcohol abuse is a dangerous habit in young people. The National Youth Survey is a longitudinal American study in part devoted to the investigation of alcohol disorder over time. The symptoms of alcohol disorder are measured by binary and ordinal items. In the literature it is well recognized that alcohol abuse can be measured by a latent construct; therefore generalized latent variable models for mixed data represent the ideal framework to analyse these data. However, it might be desirable to c...
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#1Silvia CagnoneH-Index: 9
#2Cinzia ViroliH-Index: 15
#1Silvia Cagnone (UNIBO: University of Bologna)H-Index: 9
#2Francesco Bartolucci (University of Perugia)H-Index: 27
Maximum likelihood estimation of models based on continuous latent variables generally requires to solve integrals that are not analytically tractable. Numerical approximations represent a possible solution to this problem. We propose to use the adaptive Gaussian---Hermite (AGH) numerical quadrature approximation for a particular class of continuous latent variable models for time-series and longitudinal data. These dynamic models are based on time-varying latent variables that follow an autoreg...
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#1Silvia CagnoneH-Index: 9
#2Silvia BianconciniH-Index: 9
textabstractWe propose a new method to perform approximate likelihood inference in latent variable models. Our approach provides an approximation of the integrals involved in the likelihood function through a reduction of their dimension that makes the computation feasible in situations in which classical and adaptive quadrature based methods are not applicable. We derive new theoretical results on the accuracy of the obtained estimators. We show that the proposed approximation outperforms sever...
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