Bartolucci, F. and Pandolfi, S. (2010), Bayesian inference for a class of latent Markov models for categorical longitudinal data, http://arxiv.org/PS_cache/arxiv/pdf/1101/1101.0391v2.pdf

Bartolucci, F., d'Agostino, G., Montanari, G. E. (2010), An investigation of the discriminant power and dimensionality of items used for assessing health condition of elderly people, http://arxiv.org/abs/1008.3268

Pandolfi, S., Bartolucci, F. and Friel, N. (2010), A generalized Multiple-try Metropolis version of the Reversible Jump algorithm, http://arxiv.org/abs/1006.0621.

Bartolucci, F., Farcomeni, A. and Pennoni, F. (2010), An overview of latent Markov models for longitudinal categorical data, http://arxiv.org/abs/1003.2804.

Bartolucci, F. and Nigro, V. (2009), Approximate conditional inference for panel logit models allowing for state dependence and unobserved heterogeneity, arXiv:math/0702774.

Pubblicazioni (Published papers)

lista formato pdf (list in pdf format - citations)

- in press -

1. Bartolucci, F., Montanari, G.E., S. Pandolfi (2011), Dimensionality of the latent structure and item selection via latent class multidimensional IRT models, Psychometrika.

2. Bacci, S., Bartolucci, F. (2010), A multidimensional latent class Rasch model for the assessment of the Health-related Quality of Life, in K. B. Christensen, M. Mesbah, and S. Kreiner (Eds.), Rasch models for Health Sciences.

3. Chiavarini, M., Bartolucci, F., Gili, A., Pieroni, L., Minelli, L. (2010), Effects of Individual and Social Factors on Preterm Birth and Low Birth Weight: an Italian case study, International Journal of Public Health

- 2011 -

4. Bartolucci, F. and Grilli, L. (2011), Modelling partial compliance through copulas in a principal stratification framework, Journal of the American Statistical Association, 106, pp. 469-479.

5. Bartolucci, F., Pennoni, F. and Vittadini, G. (2011), Assessment of school performance through a multilevel latent Markov Rasch model, Journal of Educational and Behavioral Statistics, 36, 491-522. (previous Technical report: arXiv:0909.4961v1).

6. Bartolucci, F. and Pennoni F. (2011), Impact evaluation of job training programs by a latent variable model, In: Ingrassia S., Rocci R., Vichi M. (Editors), New Perspectives in Statistical Modeling and Data Analysis, Springer, pp. 65-73.

- 2010 -

7. Bartolucci, F. and Scrucca, L. (2010), Point Estimation Methods with Applications to Item Response Theory Models, In: B. McGaw, E. Baker and P. P. Peterson (Editors), International Encyclopedia of Education, 3rd Edition, Elsevier, 7, pp. 366-373.

8. Bartolucci, F. and Solis-Trapala, I. (2010), Multidimensional latent Markov models in a developmental study of inhibitory control and attentional flexibility in early childhood, Psychometrika, 75, pp. 725-743.

9. Bartolucci, F. (2010), On the conditional logistic estimator in two-arm experimental studies with non-compliance and before-after binary outcomes, Statistics in Medicine, 29, pp. 1411-1429 (previous tech. Technical report: arXiv:0710.2608).

10. Bartolucci, F. and Nigro, V. (2010), A Dynamic Model for Binary Panel Data with Unobserved Heterogeneity Admitting a root-n Consistent Conditional Estimator, Econometrica, 78, pp. 719-733.

11. Bartolucci, F. and Farcomeni, A. (2010), A Note on the Mixture Transition Distribution and Hidden Markov Models, Journal of Time Series Analysis, 31, pp. 132-138.

- 2009 -

12. Bartolucci, F. and Farcomeni, A. (2009), A multivariate extension of the dynamic logit model for longitudinal data based on a latent Markov heterogeneity structure, Journal of the American Statistical Association, 104, pp. 816-831.

13. Bartolucci, F., Lupparelli, M. and Montanari, G. E. (2009), Latent Markov model for longitudinal binary data: an application to the performance evaluation of nursing homes, Annals of Applied Statistics, 3, pp. 611-636. (previous Technical report: arXiv:0908.2300)

- 2008 -

14. Bartolucci, F. and Lupparelli, M. (2008), Focused information criterion for capture-recapture models for closed populations, Scandinavian Journal of Statistics, 35, pp. 629 - 649.

15. Bartolucci, F., Pennoni, F. and Lupparelli, M. (2008), Likelihood inference for the latent Markov Rasch model, in C. Huber, N. Limnios, M. Mesbah, M. Nikulin (Eds.), Mathematical Methods for Survival Analysis, Reliability and Quality of Life, Wiley, pp. 239-254.

- 2007 -

16. Bartolucci, F. and Pennoni, F. (2007), On the approximation of the quadratic exponential distribution in a latent variable context, Biometrika, 94, pp. 745-754.

17. Bartolucci, F. (2007), A class of multidimensional IRT models for testing unidimensionality and clustering items, Psychometrika, 72, 141-157.

18. Bartolucci, F. and Pennoni, F. (2007), A class of latent Markov models for capture-recapture data allowing for time, heterogeneity and behavior effects, Biometrics, 63, pp. 568-578.

19. Bartolucci, F., Colombi, R. and Forcina, A. (2007), An extended class of marginal link functions for modelling contingency tables by equality and inequality constraints, Statistica Sinica, 17, pp. 691-711.

20. Bartolucci, F. and Nigro, V. (2007), Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data, Computational Statistics and data analisys, 51, pp. 3470-3483.

21. Bartolucci, F. (2007), A penalized version of the empirical likelihood ratio for the population mean, Statistics and Probability Letters, 77, pp. 104-110.

22. Bartolucci, F., Pennoni, F. and Francis, B. (2007), A latent Markov model for detecting patterns of criminal activity, Journal of the Royal Statistical Society, series A, 170, pp. 115–132.

- 2006 -

23. Bartolucci, F. and Forcina, A. (2006), A class of latent marginal models for capture-recapture data with continuous covariates, Journal of the American Statistical Association, 101, pp. 786-794.

24. Bartolucci, F. (2006), Likelihood inference for a class of latent Markov models under linear hypotheses on the transition probabilities, Journal of the Royal Statistical Society, series B, 68, pp. 155-178.

25. Bartolucci, F., Scaccia, L. and Mira, A. (2006), Efficient Bayes factor estimation from the Reversible Jump output, Biometrika, 93, pp. 41-52.

26. Bartolucci, F. and Montanari, G. E. (2006), A new class of unbiased estimators for the variance of the systematic sample mean, Journal of Statistical Planning and Inference, 136, pp. 1512-1525.

- 2005 -

27. Scaccia, L. and Bartolucci, F. (2005), A Hierarchical Mixture Model for Gene Expression Data, New Developments in Classification and Data Analysis, (editors: M. Vichi, P. Monari, S. Mignani and A. Montanari), Springer, pp. 267-274 (Extended version of the paper presented at CLADAG 2003).

28. Bartolucci, F. (2005), Clustering univariate observations via mixtures of unimodal normal mixtures, Journal of Classification, 22, pp. 203-219.

29. Bartolucci, F. and Forcina, A. (2005), Likelihood inference on the underlying structure of IRT models, Psychometrika, 70, p. 31-43.

30. Bartolucci, F. and Scaccia, L. (2005), The use of mixtures for dealing with non-normal regression errors, Computational Statistics and Data Analysis, 48, pp. 821-834 (tables for the homeschedastic case).

- 2004 -

31. Forcina, A. and Bartolucci, F. (2004), Modelling quality of life variables with non-parametric mixtures, Environmetrics, 15, pp. 519-528.

32. Bartolucci, F. and Scaccia, L. (2004), Testing for positive association in contingency tables with fixed margins, Computational statistics and Data Analysis, 47, pp. 195-210.

- 2003 -

33. Bartolucci, F. and De Luca, G. (2003), Likelihood-based inference for asymmetric stochastic volatility models, Computational Statistical and Data Analysis, 42, pp. 445-449.

34. Bartolucci, F., Mira, L. and Scaccia, L. (2003), Answering two biological questions with a latent class model via MCMC applied to capture-recapture data, in Applied Bayesian Statistical Studies in Biology and Medicine, (editors: M. Di Bacco, G. D'Amore and F. Scalfari), Kluwer Academic Publishers, pp. 7-23.

- 2002 -

35. Bartolucci, F. and Forcina, A. (2002), Extended RC association models allowing for order restrictions and marginal modelling, Journal of the American Statistical Association, 97, pp. 1192-1199.

36. Bartolucci, F. and Besag, J. (2002), A recursive algorithm for Markov random fields, Biometrika, 89, pp. 724-730.

37. Bartolucci, F. and De Luca, G. (2002), Estimation of stochastic volatility models, in Computational Methods in Decision-Making, Economics and Finance (editors: E.J. Kontoghiorghes, B. Rustem and S. Siokos Editors), Kluwer Academic Publishers, pp. 541-556.

- 2001 -

38. Bartolucci, F., Forcina, A. and Dardanoni, V. (2001), Positive Quadrant Dependence and Marginal Modelling in two-way tables with ordered margins, Journal of the American Statistical Association, 96, pp. 1497-1505.

39. Bartolucci, F. and Forcina A. (2001), Analysis of capture-recapture data with a Rasch-type model allowing for conditional dependence and multidimensionality, Biometrics, 57, pp. 714-719.

40. Bartolucci, F. and De Luca, G. (2001), Maximum likelihood estimation for a latent variable time series model, Applied Stochastic Models for Business and Industry, 17, pp. 5-17.

41. Bartolucci, F. (2001), Developments of the Markov chain approach within the distribution theory of runs, Computational Statistics and Data Analysis, 36, pp. 107-118.

- 2000 -

42. Bartolucci, F. and Forcina A. (2000), A likelihood ratio test for MTP₂ within binary variables, The Annals of Statistics, 28, pp. 1206-1218.

Seminari (Talks)

Performance evaluation of nursing homes via latent Markov models , Università Milano-Bicocca, 12/10/2010 (slides).

Analysis of binary panel data by static and dynamic logit models , Università di Napoli – Federico II, 03/12/2009 (slides).

Pseudo conditional ML estimation of the dynamic logit model for binary panel data , UPF - Barcelona, 21/01/2009 and University of Leaven 27/04/09 (slides).

Dynamic logit model: pseudo conditional likelihood estimation and latent Markov extension, Luiss Roma, 14/11/2008 (slides).

Likelihood inference for a latent Markov Rasch model, with application to educational assessment, Laboratoire de Statistique Théorique et Appliquée (LSTA), Université Pierre et Marie Curie - Paris VI, 06/03/2006 (slides).

A class of latent marginal models for capture-recapture data with continuous covariates, Dipartimento di Economia Politica e Metodi Quantitativi, Università di Pavia, 21/04/2005 (slides).

Empirical likelihood control charts for the process mean, Department of Applied Statistics and Operational Research, Università Politecnica de Valencia, 26/07/04 (slides).

Analisi di dati cattura-ricattura tramite una versione estesa del modello di Rasch, Rasch Analysis: aspetti teorici e pratici, Università Milano, 28/06/04 (slides).

A Markov Chain Approach to Quality Control, Department of Applied Statistics and Operational Research, Università Politecnica de Valencia, 17/07/03 (slides).

Introduzione all'ottimizzazione stocastica, Scuola estiva di ottimizzazione, Università dell'Insubria, 10/07/03 (slides).

Modelli mistura per l'analisi di dati cattura-ricattura, Istituto di Metodi Quantitativi, Università Bocconi, 05/06/03 (slides).

Analisi di dati categorici con modelli marginali espressi tramite vincoli di uguaglianza e disuguaglianza, Ente per gli studi monetari, bancari e finanziali Luigi Einaudi, Roma, 25/10/02 (slides).

Una classe di modelli a variabile latente per l'analisi di dati di tipo cattura-ricattura, Istituto di Economia, Facoltà di Economia, Università dell’Insubria, Varese, 04/06/02 (slides).

A Likelihood Ratio Test for MTP₂ within Binary Variables, Department of Statistics of Penn State University, USA, 29/06/00 (slides).

Software (Software)

R package to fit Latent Markov models in the basic version (http://arxiv.org/abs/1003.2804), by F. Bartolucci

Software described in the paper “Maximum likelihood estimation of an extended latent Markov model for clustered binary panel data” (Computational Statistics and Data Analysis, 2007), by F. Bartolucci and V. Nigro.

Software described in the paper “A latent Markov model for detecting patterns of criminal activity” (Journal of the Royal Statistical Society – Series A, 2007), by F. Bartolucci, F. Pennoni and B. Francis.

Software described in the paper “A class of multidimensional IRT models for testing unidimensionality and clustering items” (Psychometrika, 2007), by F. Bartolucci.

Software described in the paper “A class of latent marginal models for capture-recapture data with continuous covariates” (Journal of the American Statistical Association, 2006), by F. Bartolucci and A. Forcina.

Software described in the paper “Clustering univariate observations via mixtures of unimodal normal mixtures” (Journal of Classification, in press, 22, pp. 203-219), by F. Bartolucci.

Software described in the paper “The Analysis of Capture-Recapture Data with a Rasch-type Model allowing for Conditional Dependence and Multidimensionality” (Biometrics, 2001), by F. Bartolucci and A. Forcina.

Links

American Statistical Association

Annals of Statistics

Applied Stochastic Models in Business and Industry

Biometrika

Biometrics

Computational Statistics and Data Analysis

Empirical likelihood

Institute of Mathematical Statistics

Institute of Mathematics and Statistics

Journal of Computational and Graphical Statistics

Journal of the American Statistical Association