Analysis of Temporal Biomedical Data

Recommended Prerequisites

Knowledge of descriptive and univariated inferential statistics. Basic programming skills.

Teaching Methods

Lecturing, discussing and resolving practical problems.

Learning Outcomes

* Recognize the multivariate nature and time involvement of most biomedical problems;

* Understand the difference between cross-sectional and longitudinal studies;

* Acquire the fundamentals of statistical techniques for longitudinal studies involving fixed or variable time intervals;

* Perform and interpret results of statistical methods for longitudinal studies with fixed and variable time intervals;

* Acquire the fundamentals of stochastic time series and its decomposition;

* Perform and interpret results of stochastic time series;

* Use software tools to build statistical models involving time applied to biomedical data;

Work Placement(s)

No

Syllabus

* Longitudinal studies: short revision of univariate techniques;

* Analysis of variance: Repeated measures in fixed time intervals (parametric and nonparametric approaches);

* Survival curves: Kaplan-Meier estimator;

* Cox regression;

* Time series: stochastic processes ans decomposition (sazonality, cicle, tendency and randomness);

* Time series application: curve fitting, function approximation, predicting and forecasting, signal estimation, classification;

Head Lecturer(s)

Bárbara Cecília Bessa dos Santos Oliveiros Paiva

Assessment Methods

Assessment
Project: 100.0%

Bibliography

* Análise Estatística, com utilização do SPSS; João Maroco, Edições Silabo;

* Modelling Survival Data in Medical Research (Second ed., 2003). David Collet, Boca Raton: Chapman & Hall/CRC.

* Introductory Time Series with R, Cowpertwait PSP, Metcalfe AV (2009), Springer.