CH0002A - PSYCHOMETRIC AND COMPUTATIONAL TECHNIQUES FOR COGNITIVE AND CLINICAL RESEARCH

By the end of the course, the student will be able to:


Select, design, and evaluate measurement instruments (tests, questionnaires, and tasks) for observing psychological and behavioral constructs.

Design datasets and acquisition procedures for experimental and observational data, including behavioral data and (at an introductory level) neurophysiological data.

Apply data-analysis pipelines to model relationships between variables and test hypotheses (e.g., GLM-like models, mixed-effects models, latent-structure analyses).

Use simulations and resampling strategies to test hypotheses, estimate statistical power/sample size, and evaluate the robustness of analytical pipelines.

Identify, discuss, and mitigate methodological biases (in measurement, sampling, analysis, and reporting), developing a critical approach to analytical choices.

Interpret and communicate scientific results in a rigorous, transparent, and reproducible manner, including appropriate visualizations and clear methodological reporting.

Develop and discuss research projects at the individual, group, and whole-class level, integrating theory, measurement, analysis, and interpretation.

Project-based activities (Project-Based Learning)
During the year, the class will develop a psychometric instrument on a topic chosen by the students. The project will involve defining the construct, developing items, collecting/simulating data, and conducting validation analyses. Depending on the quality of the work, possible scientific dissemination may be considered (e.g., a presentation or submission).
Questions in the written exam will include content related to the development and validation process of the instrument created through the class project.