Upcoming GRBIO seminars
Organizers: Ferran Reverter and Jordi Cortés
Online. If you want to attend, please, contact grbio@grbio.eu
Development and Evaluation of Metrics for Assessing Synthetic Tabular Data Quality
This presentation introduces synthetic data as a promising solution to enable secure data sharing while addressing concerns around sensitive information. By enhancing privacy, reducing bias, and augmenting datasets, synthetic data has become increasingly valuable across domains. The talk will provide an overview of synthetic data generation methods and the challenges of evaluating their quality, particularly for tabular data. It will highlight existing gaps in validation metrics and discuss future research directions aimed at building a robust methodology for assessing synthetic data. Special attention will be given to the importance of balancing data utility, privacy, and representativeness, with potential applications in the energy sector.
Biosketch
Nora Amama Ben Hassun is a PhD candidate in Statistics and Operations Research at the Polytechnic University of Catalonia, supervised by Dr. Daniel Fernández Martínez and Dr. Jordi Cortés Martínez. She holds a Bachelor's degree in Statistics from the University of Barcelona and the UPC - BarcelonaTech, and a Master's in Statistics and Operations Research from the UPC - BarcelonaTech and the University of Barcelona. Her doctoral research focuses on developing a new methodology for the validation of synthetic data, with applications primarily aimed at the energy sector.
Online. If you want to attend, please, contact grbio@grbio.eu
Advances in the analysis of human perceptions within the CUB framework
Questionnaires are widely used across various research fields to assess latent traits such as perceptions, opinions, and attitudes. These traits are typically measured using rating scales like Likert or Semantic Differential scales, generating ordinal data. Analyzing such data presents unique challenges, for which specialized models have been developed. Among these, the CUB (Combination of discrete Uniform and shifted Binomial random variables) class of models stands out as a prominent approach in the literature. CUB models assume that respondents' ratings result from the interplay of two distinct psychological components: feeling, representing a rational response, and uncertainty, reflecting indecision. This talk provides an introduction to CUB models and presents new theoretical contributions to their development. Additionally, an application of these models to analyze the synesthetic experience of museum visitors is presented, showing their practical relevance in studying human perceptions.
Biosketch
Matteo Ventura is completing his PhD in Statistics at the University of Brescia, Italy. His research focuses on both the methodological and applied aspects of Statistical Sciences. His primary interests lie in mixture models and ordinal data, with applications across various fields, including marketing, tourism, culture, and psychology. Additionally, he is interested in graphical models with applications to social sciences and ecology.
Online. If you want to attend, please, contact grbio@grbio.eu
Addressing bias in statistical inference based on epidemiological registry data
Hospital's registry data is a widely used resource in Nordic countries to estimate parameters of interest in the public health and in epidemiology. This data allows the researcher to have an unbiased representation of the population, since it is collected for all the individuals that visit the hospitals in the country, and it is stored in databases that are available for the researchers. Despite being a powerful tool, this data has some drawbacks that must be considered before making the study.
This presentation aims to expose the delayed-entry problem, that arise when hospital's registers are used for estimating the incidence of a disease, and explain the washout periods methodology, that it is usually used to correct (or partially correct) it. We will present a theoretical framework that helps to understand the delayed-entry problem from a formal point of view and a simulation study to analyze this methodology and understand its limitations.
Biosketch
Dídac Gallego is graduated with a bachelor’s degree in mathematics from the Autonomous University of Barcelona in 2022. In the same year, he began a Master’s program in Statistics and Operations Research (UPC-UB), which he completed in June 2024. Currently, he is working at Accenture
Share: