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Vincent Marmarà

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Vincent Marmara is a Statistician and Researcher by profession. He obtained his first degree in Statistics, Operational Research and Mathematics at the University of Malta.  He later advanced his studies by obtaining Masters of Science in Statistics at Sheffield University, UK.  Currently he is reading his PhD in Mathematics at the University Of Stirling, Scotland.  His PhD study focuses on Epidemiology and he is under the supervision of Dr Adam Kleczkowski (Stirling University).  He was entrusted with numerous research projects both at a national and international level.  He led research groups and analyzed data to a high level scientific extent.  One of his main research projects involved modeling missing data in surveys and in other research areas.  Mr. Marmarà has 7 years experience in the iGaming industry as a Business Intelligence Analyst. At present he is the Chief Regulatory Officer/Deputy CEO of the Malta ‘Lotteries and Gaming Authority. On a part-time basis he lectures at the University of Malta.  Moreover he is the President of the Malta Statistics and Operations Research Organization (MSTOR).


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My main areas of research are Epidemiology, Missing Data, Bayesian Analysis, Sampling Techniques, Time Series and Regression Analysis. 

               Completed dissertation titles:

                           Missing Data in Sampling Surveys (2006)

Abstract: “The main aim of this dissertation is to study the problem of missing data in surveys.  This study will lead us to analyze other issues related to nonresponse.  In fact there are other aims in this dissertation.  One of them is the discussion about the use of the characteristics of the population and sample, mainly demographic issues.  These will be used for the implementation of imputation models.  Imputation will be divided in two types; imputation to cater for respondents who refused to answer more than one question in the questionnaire, but not all of them and imputation to cater for those persons who refused to answer all the questions in the questionnaire.  These analyses will be done with respect to two different kinds of surveys but three surveys for the analysis.  Our main interests relate to be the classification of political tendencies of the nonrespondents.  Another problem studied related to the estimation of income of nonrespondents.  Finally we are going to compare and analyze the results obtained in this dissertation and also, further recommendations for further study.



                           Rural and Urban Ozone (2009)

Abstract: “Ozone gas is a very influential gas in the earth’s atmosphere.  This gas varies in various concentrations for different rural and urban areas.  The level of concentration of ozone is influenced by the type of pollutants present in the atmosphere and other ambient conditions. In fact concentrations in rural areas are higher than in urban areas.   This study investigated the relationship between urban and rural ozone concentrations and quantified the extent to which ambient rural conditions and the concentrations of other pollutants can be used to predict urban ozone concentrations.  The general relationship between various levels of ozone concentrations at urban and neighbouring rural sites was explored using linear mixed-effect modelling and generalized least squares models.  In these models the correlation and variance structures were defined so as to describe the error terms in the models due to dependent data.  Ozone concentrations at finer temporal resolution are more dependent and have coarser resolution as well.  During this study it was found that ozone concentrations coming from a neighbouring urban site make a better predictor to the urban ozone concentrations than ambient rural ozone at some levels of temporal averaging.  Rural ozone was found to be the best predictor to predict urban ozone concentration for weekly average data.  In general the constructed models produced good predictions for the urban ozone concentrations.”


               Other details

I am at present the President of the Malta Statistics and Operations Research Organization (MSTOR) (Welcome to MSTOR).  Our main aims are:

The main aims of MSTOR are to promote unity among all statisticians and statistics students through social and educational activities and to promote the need of high quality research by means of seminars, conferences and other public activities. Other specific aims of the organization are to represent its members on a national and international level, to bridge the gap between academic life and industry and to empower statistics students with further resources complementary with what they are doing in their course.”

Vincent Marmara ( Email:
4BX6, Cottrell Building
Department of Computing Science and Mathematics
University of Stirling Stirling FK9 4LA   SCOTLAND

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