Course Code : | 2024GENEP1 |

Study domain: | Epidemiology |

Academic year: | 2019-2020 |

Semester: | 2nd semester |

Contact hours: | 18 |

Credits: | 9 |

Study load (hours): | 252 |

Contract restrictions: | Faculty decision based on student file |

Language of instruction: | English |

Exam period: | exam in the 2nd semester |

Lecturer(s) | Geert Molenberghs Steven Abrams |

At the start of this course the student should have acquired the following competences:

an active knowledge of

an active knowledge of

- English

Introduction to statistics (or demonstrable equivalent knowledge, to be assessed by the course coordinator)

- At the end of the module the student can demonstrate that he/she Knowledge Goal 1: can define the square root law of sample size and can describe its impact on sample size calculation
- Knowledge Goal 2: can name the general principles of statistical testing
- Knowledge Goal 3: can give the statistical principles of the following techniques: Student’s t-test (one sample; paired and unpaired samples); analysis of variance (one-way and two-way); simple and multiple regression (one sample, two samples, and paired proportions; chi² test for goodness-of-fit, Pearson chi² test, McNemar chi² test)
- Knowledge Goal 4: has the right knowledge relative to situations where these techniques can be used; knows which conditions need to be satisfied so that these techniques will lead to reliable results
- Knowledge Goal 5: can define the concept ‘variance explained’
- Knowledge Goal 6: can recognize the concept of ‘multicolinearity’
- Knowledge Goal 7: can name the basic principles of non-parametric techniques that need to be applied whenever the assumptions of the normal distribution are not tenable
- Knowledge Goal 8: can list the principles of model simplification in regression analysis
- Knowledge Goal 9: can state the basic principles of linear and logistic regression analysis
- Knowledge Goal 10: can state the basic principles of Poisson regression
- Knowledge Goal 11: can state the basic principles of analysis of time-related events, including Cox proportional hazards regression analysis
- Knowledge Goal 12: can state the principles of likelihood theory and maximum likelihood estimation
- Knowledge Goal 13: can list the principles of model validation and regression diagnostics
- Knowledge Goal 14: can present the basic principles of longitudinal data analysis
- Knowledge Goal 15: The procedure of ‘testing’ can be applied using the standard statistical software (SPSS, SAS, R,…)
- Knowledge Goal 16: is able to interpret the results obtained with such techniques in an effort to respond to a research question

The course starts with the basic applications of biostatistics methodology for the analysis of data from medical and public health research. The following topics are given attention: data types, measures of location and spread, population and samples, distributions, confidence intervals, hypothesis testing, comparison of two or more proportions (parametric and non-parametric methods), relationships between two variables (correlation, single linear regression, logistic regression, Poisson regression, time-to-event regression).

This module handles the statistical methods needed to study the association between (various) determinants and the occurrence of a certain event.

Considerable attention is given to multiple linear regression. Likelihood theory and maximum likelihood estimation is introduced, using examples and keeping mathematical derivations to a minimum. Subsequently, the most important regression techniques that are applied in biomedical and related research, are sketched and exemplified. This refers to: logistic regression (including model validation and regression diagnostics), Poisson regression, analysis of event history data, with specific attention for the Cox proportional hazards model. Finally, students are introduced to the analysis of longitudinal data. Attention is given to missing data.

The course has an international dimension.

Class contact teachingLectures Laboratory sessions

Personal workAssignments In group Paper In group

**5.3 Facilities for working students ***

Classroom activities

Individual work

Personal work

Classroom activities

- Lectures: recording available via video link on Blackboard

Individual work

- In group: individual alternative assignment possible

ExaminationOral without written preparation

Continuous assessmentAssignments

Continuous assessment

Hand-outs and web lectures, available at BlackBoard

B. Rosner. Fundamentals of Biostatistics. Seventh Edition. Brooks/Cole Cengage learing. Boston MA USA 2010

ISBN-13: 978-0-538-73349-6

ISBN-10: 0-538-73349-7

http://www.uhasselt.be/fiche?voornaam=geert&naam=molenberghs