01/03/2026
The primary aim of the Advanced Statistics Course is to provide theoretical and practical knowledge of advanced data analysis techniques applied to clinical research and the health and social sciences.
Following a methodological introduction to the main analytical frameworks, the course systematically covers: survival analysis and Cox regression models; models for longitudinal and repeated measures data (Linear Mixed Models and Generalized Estimating Equations); latent class and latent profile analyses; Item Response Theory models for the validation of measurement instruments; and dyadic models for the study of interdependence between pairs of individuals.
For each topic, an essential theoretical foundation is provided, followed by practical applications of the techniques presented.
During the 32 hours of training, delivered online in synchronous mode, participants will complete numerous guided exercises using специально prepared datasets and major statistical software packages (SPSS, Stata, Mplus).
The course is intended for participants with a solid background in basic and intermediate statistics.
As a final assessment, each participant will be required to complete a mini applied project consisting of the analysis of a dataset using one or more of the advanced techniques covered during the course, including the production of an APA-formatted results table, an appropriate graph or diagram, and a brief critical interpretation of the results.
The assignment must be submitted within one week of the end of the course.
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