Prof. Liberato Camilleri

Prof. Liberato Camilleri

Prof. Liberato Camilleri

 B.Ed.(Hons),M.Sc.,Ph.D.(Lanc.)

Associate Professor

Room 509
Maths & Physics Building
University of Malta
Msida
  +356 2340 3069

Head of Department

Liberato Camilleri graduated from the University of Malta after reading for a first degree in Education and proceeded to read an M.Sc in Mathematics. He obtained a PhD degree in Applied Statistics in 2005 from Lancaster University. He joined the University of Malta as an assistant lecturer in 1998 with the Department of Statistics and Operations Research and was promoted to lecturer and later to senior lecturer.

His research specialization areas are related to statistical modeling, which include generalized linear models, latent class models, item response models, structural equation models, multilevel models and survival models. He has co-authored a number of peer-reviewed publications in journals and conference proceedings with foreign and local researchers in several fields of application including market segmentation, education, neural networks and atmospheric chemistry. He has co-authored three books describing national surveys related to SEBD and Maltese university students. He has contributed in analyzing data and writing national and international reports – PISA Malta report (2009 and 2015), TIMSS Malta report (2011, 2015), PIRLS (2011) Malta report Civic and citizenship education (2010) Malta report, European Survey on Language Competences (2011) Malta report, Short-Term Statistics for Industrial Production and Retail Trade Indices (2015), Prediction of expected TV and Radio Share (2015), Digital and Video Game Usage in Malta (2014), Consent Project (2013) Standardized spelling and reading tests for Maltese students (2011), Food consumption and eating patterns of Maltese adults (2010), Travelling patterns of university students (2009).
  • Latent Class Models
  • Multilevel Models
  • Generalised Linear Models
  • Survival Models

Camilleri, L. & Cefai, C. 2013, "Identifying the factors that influence change in SEBD using Logistic Regression Analysis", World Journal of Education, vol. 3, no. 4, pp. 96-104.

Camilleri, L. & Francalanza, H. 2012, "Segmenting preferences for investment bonds using Latent Class Variable Mixture Models", Journal of Advances in Business-Related Scientific Research, vol. 3, no. 2, pp. 105-119.

Camilleri, L., Cefai, C. & Cooper, P. 2011, "Social, emotional and Behaviour Difficulties in Maltese schools: A Multilevel model. ", Journal of Research in Educational Sciences, vol. 2, no. 1(3), pp. 3-15.

Camilleri, L., Firman, C., Martinelli, V. & Ventura, F. 2010, "Using Multilevel Random Coefficient Models to assess students' spelling abilities", The 2020 European Simulation and Modelling Conference, eds. J. Gerrit, K. Ramaekers & A. Caris, Eurosis, Hasselt, Belgium, October 25 - 27, pp. 449 - 453.

Camilleri, L. 2009, "Bias of Standard Errors in Latent Class Model Applications using Newton-Raphson and EM algorithms", Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 13, no. 5, pp. 537-541.

Camilleri, L. 2009, "Latent Class Mixture models for analyzing Rating Responses", Industrial Simulation Conference 2009, eds. B. Diganta, N. Vahid & D. Lipika, Eurosis, Loughborough; United Kingdom, June 1 - 3, pp. 42 - 46.

Camilleri, L. 2008, "Standard Error estimation for EM applications related to Latent Class models", 1st International North American Simulation Technology Conference, eds. M. Beldjehem, L. Zadeh, R. Yager & M. Gupta, Eurosis, Montreal; Canada, August 13 - 15, pp. 52 - 56.

Camilleri, L. 2007, "Assessing the Performance of Several Information Criteria to Determine the Optimal Number of Segments in a Latent Class Model", The 2007 European Simulation and Modelling Conference, eds. A. Tanguy, C. Bertelle, G. Fortino & J. Sklenar, Eurosis, Malta, October 22 - 24, pp. 191-198.

Camilleri, L. & Portelli, M. 2007, "Segmenting the Heterogeneity of Tourist Preference using a Latent Class Model combined with the EM algorithm", The 6th Aplimat Conference , ed. M. Kovacova, Bratislava University Press, Bratislava; Slovak Republic, Februrary 6 - 9, pp. 343 - 356.

Camilleri, L. & Green, M. 2004, "Statistical models for market segmentation", 19th International Workshop on Statistical Modelling, eds. A. Biggeri, E. Dreassi, C. Lagazio & M. Marchi, Firenze University Press, Firenze; Italy, July 4 - 8, pp. 121 - 125.

  • COU5141 - Advanced Counselling Research Methods
  • EDU5970 - Fundamentals of Educational Research
  • EDU5971 - Applied Educational Research Methods
  • EMC5702 - Research Methods in Comparative Education
  • EMP1004 - Data Management and Processing
  • EMP2014 - Research Methods: Theory and Applications
  • HSC5111 - Research Methods for Health Care Professionals
  • IRL2082 - Research Methods
  • IRL5061 - Methodology and Research Methods in Humanitarian Studies
  • LHM3000 - Research Methods
  • OMS5003 - Essentials of Operational Oceanography
  • OMS5004 - Data Resources in Operational Oceanography
  • RFS5006 - Application Tools and Research Methods
  • SOC2055 - Introduction to SPSS for Sociology Students
  • SOR0210 - Data Treatment and Probability
  • SOR0220 - Elementary Statistical Theory
  • SOR1440 - Principles of Financial Mathematics
  • SOR3211 - Generalized Linear Models
  • SOR3221 - Regression Models
  • SOR3241 - Survival Analysis
  • SWB1002 - Introduction to Research for Social Wellbeing
  • SWB2001 - Research Methods for Social Wellbeing
Research work in progress:
The PIRLS (2016) Malta report
The ICCS (2016) Malta report

Publications in Progress:
Modeling survival times using Frailty models
Modelling Mortality rates using GEE models

Affiliation and Membership:
Associate Editor of the local journal Xjenza.
Member of the editorial board of the International Journal of Emotional Education.

Award
Certificate of Presentation of Medal for Services rendered to the Pharmacy Profession.
(Presented on the occasion of the 2016 Annual Pharmacy Symposium).

Best Paper Award:
Camilleri L., Francalanza H. (2011). Latent Class Analysis for Segmenting Preferences
of Investment Bonds. Proceedings of 2011 ABSRC Conference p.23-35.

Search for staff

Study at UM

https://www.um.edu.mt/_templates/staffprofiles