List of publications (see also my profile in Google Scholar, ISI, RePec)

Francesco Bartolucci

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Technical Reports

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Teaching (DIDATTICA)


1. Bartolucci, F., Farcomeni, A. and Pennoni, F. (2013), Latent Markov Models for Longitudinal Data, Chapman and Hall/CRC press.



1. Gnaldi, M., Bacci, S. & Bartolucci, F. (2015), A multilevel finite mixture item response model to cluster examinees and schools, Advances in Data Analysis and Classification, in press.

2. Bartolucci, F. and Lupparelli, M. (2015), Pairwise likelihood inference for nested hidden Markov chain models for multilevel longitudinal data, Journal of the American Statistical Association, in press.

3. Bartolucci, F., Dardanoni, V. and Peracchi, F. (2015), Ranking scientific journals via latent class models for polytomous item response data, Journal of the Royal Statistical Society, series - A, in press (previous technical report: EIEF 13/13).

4. Bartolucci, F. (2015), A comparison between g-index and h-index based on concentration, Journal of the Association for Information Science and Technology, in press.

5. Bartolucci, F. & Farcomeni, A. (2015), A discrete time event-history approach to informative drop-out in mixed latent Markov models with covariates, Biometrics, in press (previous tecnica report:

6. Bartolucci, F., Montanari, G. E. and Pandolfi, S. (2015), Three-step estimation of latent Markov models with covariates, Computational Statistics and Data Analysis, 83, pp. 287-301 (previous technical report:

7. Bartolucci, F., Belotti, F. & Peracchi, F. (2015), Testing for Time-Invariant Unobserved Heterogeneity in Generalized Linear Models for Panel Data, Journal of Econometrics, 184, pp. 111-123 (previous technical report: EIEF 12/13).

8. Minelli, L., Pigini, C., Chiavarini, M. & Bartolucci, F. (2014), Employment status and perceived health condition: longitudinal data from Italy, BMC Public Health, 14: 946 (previous technical report: MPRA 55788).

9. Bartolucci, F., Farcomeni, A. & Pennoni, F. (2014), Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates (with discussion), Test, 23, pp. 433-486 (previous techincal report: MPRA Paper 39023).

10. Bacci, S., Bartolucci, F. Chiavarini, M., Minelli, L. & Pieroni, L. (2014), Differences in Birthweight Outcomes: A Longitudinal Study Based on Siblings, International Journal of Environmental Research and Publich Health, 11, pp. 6472-6484 (previous tecnical report:

11. Bartolucci, F., Bellio, R., Sartori, N. & Salvan, A. (2014), Modified profile likelihood for fixed-effects panel data models, Econometric Reviews, in press (previous techinal report:

12. Bacci, S., Bartolucci, F. (2014), A Multidimensional Latent Class IRT Model for Non-Ignorable Missing Responses, Structural Equation Modeling A Multidisciplinary Journal, in press (previous techincal report:

13. Bartolucci, F. & Farcomeni, A. (2014), Information matrix for hidden Markov models with covariates, Statistics and Computing, in press.

14. Bartolucci, F. & Pandolfi, S (2014), A new constant memory recursion for hidden Markov models, Journal of Computational Biology, 21, pp. 99-117 (previous tecnical report:

15. Pandolfi, S., Bartolucci, F. & Friel, N. (2014), A generalized Multiple-try Metropolis version of the Reversible Jump algorithm, Computational Statistics and Data Analysis, 72, 298–314 (previous thecnical report:

16. Bartolucci, F., Bacci, S. and Gnaldi, M. (2014), MultiLCIRT: An R package for multidimensional latent class item response models, Computational Statistics and Data Analysis, 71, pp. 971-985 (previous technical report:

17. Bacci, S. & Bartolucci, F. (2014), Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data, Computational Statistics and Data Analysis, 71, pp. 262-272 (previous technical report:

18. Bacci, S., Bartolucci, F., Gnaldi, M. (2014), A class of Multidimensional Latent Class IRT models for ordinalpolytomous item responses, Communication in Statistics - Theory and Methods, 43, pp. 787-800 (previous tecnical report:

19. Bartolucci, F., Bacci, S. & Pennoni, F. (2014), Longitudinal analysis of the self-reported health status by mixture latent autoregressive models, Journal of the Royal Statistical Society - series C, 63, pp. 267-288. (previous technical report:

20. Bartolucci, F. & Farcomeni, A. (2013), Causal inference in paired two-arm experimental studies under non-compliance with application to prognosis of myocardial infarction, Statistics in Medicine, 25, pp. 4348-4366 (previous technical report:

21. Bartolucci, F., Montanari, G.E. & S. Pandolfi (2012), Dimensionality of the latent structure and item selection via latent class multidimensional IRT models, Psychometrika, 77, pp. 782-802.

22. Bartolucci, F., Scaccia, L. & Farcomeni, A. (2012), Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data, Computational Statistics and Data Analysis, 56, pp. 4067-4080. (previous technical report:

23. Bartolucci, F. & Nigro, V. (2012), Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data, Journal of Econometrics, 170, pp. 102-116. (previous technical report arXiv:math/0702774 and

24. Chiavarini, M., Bartolucci, F., Gili, A., Pieroni & L., Minelli, L. (2012), Effects of Individual and Social Factors on Preterm Birth and Low Birth Weight: an Italian case study, International Journal of Public Health, 57, pp. 261-268.

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

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

27. Bartolucci, F. & 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.

28. 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).

29. Bartolucci, F. & 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.

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

31. Bartolucci, F. & 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.

32. Bartolucci, F., Lupparelli, M. & 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)

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

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

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

36. Bartolucci, F. & 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.

37. Bartolucci, F., Colombi, R. & 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.

38. Bartolucci, F. & 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.

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

40. Bartolucci, F., Pennoni, F. & 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.

41. Bartolucci, F. & 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.

42. 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.

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

44. Bartolucci, F. & 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.

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

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

47. Bartolucci, F. & 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).

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

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

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

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

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

53. Bartolucci, F., Forcina, A. & 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.

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

55. Bartolucci, F. & 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.

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

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



1. Bartolucci, F., Bacci, S., Pigini, C. (2014), Comparison between conditional and marginal maximum likelihood estimation for a class of ordinal item response models, QdS - Journal of Methodological and Applied Statistics, in press.

2. Bartolucci, F. (2014), Modeling Longitudinal Data by Latent Markov Models with Application to Educational and Psychological Measurement, in Analysis and Modeling of Complex Data in Behavioural and Social Sciences, D. Vicari, A. Okada, G. Ragozini, C. Weihs (Eds.), Springer, pp. 11-19. (previous tecnical report:

3. Bacci, S. & Bartolucci, F. (2012), 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, pp. 199-222.

4. Bartolucci, F. & 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.

5. Pandolfi, S., Bartolucci, F. & Friel, N. (2010), A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection, Journal of Machine Learning Research Workshop and Conference Proceedings, Volume 9: AISTATS 2010, pp. 581-588.

6. Bartolucci, F. & 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.

7. Bartolucci, F., Pennoni, F. & 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.

8. Scaccia, L. & Bartolucci, F. (2005), A Hierarchical Mixture Model for Gene Expression Data, in 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).

9. Bartolucci, F., Mira, L. & 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.

10. Bartolucci, F. & 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.



1. Bartolucci, F. & Pandolfi, S (2014), Comment on “On the memory complexity of the forward-backward”, Pattern Recognition Letters, 38, pp. 15-19.

2. Bartolucci, F. (2012), On a possible decomposition of the h-index, letter to the Editor of the Journal of the American Society for Information Science and Technology, 63, 2126-212.