Miguel Lafuente Blasco

Current positions

I am an Assistant Professor in the Department of Statistical Methods at the University of Zaragoza, and a researcher at Institute for Biocomputation and Physics of Complex Systems (BIFI) .

I am also a member of the Stochastic Models research group recognised by the Government of Aragón (DGA).

I currently co-chair the working group Procesos Estocásticos y sus Aplicaciones (Pres&a) of the Spanish Society of Statistics and Operations Research (SEIO), together with Prof. Gerardo Sanz Sáiz.

Research interests

I hold a PhD in Mathematics and Statistics. My main research line focuses on the probabilistic and statistical properties of record values and record-like observations.

I also collaborate in fields such as gastroenterology, oncology, epidemiology, and the social sciences, using advanced statistical modelling and machine-learning methods.

Miguel Lafuente Blasco

My teaching books

You can download them in Spanish for free.

Análisis de datos con Jamovi. Guía práctica para la investigación científica

This book grew out of teaching and research needs in health-related programs, but the workflow applies to many fields. It is a step-by-step guide built around jamovi, a user-friendly statistical package that is free and open-source.

Estadística descriptiva en investigación social con Excel

A practical introduction to descriptive statistics with real social-science data, explained step by step in Excel. It is aimed mainly at sociology and social work, but it also works well as a first contact with data analysis in other areas.

Tools

Research tools and online calculators I developed.

BodyCompAI

An online calculator for clinicians, plus a batch mode to predict LST (lean soft tissue) for many patients at once.

INCLAD

A tool to assess disability inclusion.

INCLAD

INCLAD Gen

Guided access to INCLAD scales A and B to assess the employment inclusion of people with disabilities in conventional companies, public administrations and special employment centres.

HIBOPCovid

Open-source statistical software implementing a multistate modelling approach to forecast hospital and ICU bed occupancy. It supports back-testing on historical periods and can be adapted to planning questions beyond the original COVID-19 setting.

Contact

Email: miguellb@unizar.es