Ritratto di marco.geraci@uniroma1.it

Si invitano gli studenti a registrarsi ai corsi su Google Classroom utilizzando i codici disponibili in questa pagina. Il materiale e gli annunci relativi ai corsi verranno pubblicati esclusivamente su Google Classroom, mentre informazioni di carattere generale verranno pubblicate sul sito del docente (https://web.uniroma1.it/memotef/users/geraci-marco).

 

Students should join courses using the Google Classroom codes available on this page. Materials and announcements about the courses will be posted exclusively on Google Classroom, while general information will be published on the instructor's webpage (https://web.uniroma1.it/memotef/users/geraci-marco).

 

Anno accademico 2022/2023

  • 10596373Statistics for health economics - codice Google Classroom: dhqlqdb
  • 10592625 - Advanced statistics for finance - codice Google Classroom: sdsjueo

Anno accademico 2021/2022

  • 10600044 - Metodi quantitativi (statistica) - codice Google Classroom: kpoxgq7
  • 10596373 - Statistics for health economics - codice Google Classroom: 5vxwwfo

Anno accademico 2020/2021

  • 1051800 - Metodi statistici per l'economia - codice Google Classroom: rssx6k5
  • 10596373 - Statistics for health economics - codice Google Classroom: i7ao6lr
Insegnamento Codice Anno Corso - Frequentare Bacheca
ADVANCED STATISTICS FOR FINANCE 10592625 2022/2023
STATISTICS FOR HEALTH ECONOMICS 10596373 2022/2023
ADVANCED STATISTICS FOR FINANCE 10592625 2022/2023
STATISTICS FOR HEALTH ECONOMICS 10596373 2021/2022
METODI QUANTITATIVI 10600044 2021/2022
STATISTICS FOR HEALTH ECONOMICS 10596373 2020/2021
METODI STATISTICI PER L'ECONOMIA 1051800 2020/2021
METODI STATISTICI PER L'ECONOMIA 1051800 2019/2020
STATISTICS FOR HEALTH ECONOMICS 10592237 2019/2020
METODI STATISTICI PER L'ECONOMIA 1051800 2017/2018

Lunedì, martedì e mercoledì 10:30-11:30 in ufficio o su Zoom. Il giovedì e venerdì 9-17 solo su Zoom. Inviare un'email per richiedere un appuntamento

Mondays, Tuesdays and Wednesdays 10:30-11:30 at my office or on Zoom. Thursdays and Fridays 9-17 on Zoom only. Request appointment via email.

Professor Geraci obtained a Laurea (MSc) magna cum laude in Economics from the University of Sassari (Italy) in 2000 and a PhD in Applied Statistics from the University of Florence (Italy) in 2005. He carried out academic research in several institutions, including the National Council of Research (Italy), the University of Manchester (UK), University College London (UK) and the University of South Carolina (USA), where he currently holds an appointment as Adjunct Professor of Biostatistics. His research interests are in statistical methods and applications for health sciences, quantile inference, random-effects models, multivariate statistics, missing data, statistical computing, programming (R and C/C++), spatial statistics, accelerometer data, epidemiology and pediatrics.

Professor Geraci is involved in a wide range of collaborations in methodological and applied research. He has published peer-reviewed articles in statistics, cancer epidemiology, maternal and child health epidemiology, physical activity, gastroenterology, nuclear medicine and higher education. He also authored four statistical R packages on CRAN. He received funding awards for both methodological and collaborative research projects including a major Center grant (NIH P20) for 11 million dollars as lead of the Statistical and Data Management Core, several methodological grants (e.g., NIH R03 and intramural funding) as principal investigator for thousands of dollars, several collaborative grants (NIH R01 and R03) totalling 10 million dollars as co-investigator and lead statistician.

In 2010, Professor Geraci was awarded Chartered Statistician by the Royal Statistical Society. He obtained the National Scientific Qualification (Abilitazione Scientifica Nazionale) as Full Professor of Statistics in 2017 (settore concorsuale 13/D1) and as Full Professor of Medical Statistics in 2019 (settore concorsuale 06/M1). He was Statistical Editor for the Journal of Child Health Care (SAGE) and Associate Editor for the Journal of Applied Statistics (Taylor & Francis). He is currently Associate Editor for Statistical Methods and Applications (Springer) and Board Member of Significance (Wiley on behalf of the Royal Statistical Society RSS and the American Statistical Association ASA). He is an RSS fellow since 2006 and ASA member since 2015. He performed more than 280 reviews for 51 distinct journals (verified on Publons) including the Journal of the American Statistical Association, Journal of the Royal Statistical Society A, Journal of Statistical Planning and Inference, American Sociological Review, Annals of Applied Statistics, Journal of Statistical Software, Scandinavian Journal of Statistics, Statistical Methods in Medical Research, Statistics and Computing, Statistics in Medicine, as well as journals from the Lancet group. He has been awarded Publons Top 1% Reviewers for multidisciplinary (2017) and cross-field (2019).