Seminar

Marco Geraci

Marco Geraci
(Sapienza University of Rome)
Bio Marco Geraci is Professor of Statistics at the School of Economics, Sapienza University of Rome. He also obtained the habilitation as Professor of Medical Statistics bestowed by the Italian Ministry of Education, University and Research. After attaining a PhD in Applied Statistics from the University of Florence (Italy) in 2005, he carried out his research at the Italian National Council of Research, the University of Manchester, University College London and the University of South Carolina, 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, circular statistics, missing data, statistical computing, programming (R and C/C++), spatial statistics, accelerometer data, epidemiology and pediatrics.

Abstract

In the continuous case, the quantile function is defined as the inverse of the cumulative distribution function (CDF). The asymptotic properties of sample quantiles, including normality, have been established in a variety of settings. In the discrete case, quantiles are not unique, and inference becomes troublesome. A possible way out is offered by mid-quantiles. These are obtained by inverting the mid-CDF, which is closely related to Lancaster’s mid-p-value. Mid-quantiles, which can be seen as a bridge between quantiles of continuous and discrete distributions, provide not only advantages for inference in general but also a sensible interpretation when the distribution is discrete. In this talk, I will introduce regression methods for conditional mid-quantiles (Stat Med Res, 31(5), 2022), along with recent applications to longitudinal data analysis (J Stat Comput Simul, 94(12), 2024) and graphical modelling (arXiv:2309.05084v2).

Schedule

  • Friday 29 November 2024, 11:00-12:00 room seminar 1 @ Povo 0

Details

Material (Restricted access, user: CMQ2024)