Advanced statistical methods

The course is a compulsory course within the Master’s Programme of Applied Biostatistics (M2STA).

The entry requirements of the course include a professional degree/Bachelor's degree of at least 180 credits in health sciences, natural sciences, economics, or engineering, and a course in statistics or quantitative methods of at least 7,5 credits. Further, R programming of at least 2 credits or equivalent, English B/English 6 or equivalent, and Matematik 3b/3c or equivalent are required.

The course introduces selected complex statistical methods that expand the modelling toolbox of the students. Generalized linear (mixed) models are introduced as an overarching framework for regression modelling, and typical procedures for inference and diagnostic are exemplified in a few case studies, including ordinal outcomes and hierarchical data. The course introduces resampling methods for statistical inference (bootstrap and permutation tests) and discusses their application. Further, imputation techniques for handling missing data are discussed, with focus on multiple imputations and the workflow for the associated statistical analysis. Finally, attention is directed to the role that simulation studies play in assessing the properties of statistical methods. The focus is on discussing the steps in planning, conducting, and reporting such studies that are important for ensuring fair evaluation, transparency, reproducibility, and thus sustainable research.

The course is sustainability related.

On successful completion of the course the student will be able to:

Knowledge and understanding

• define the framework of generalized linear (mixed) models and give examples of their use.
• describe the workflow of an analysis involving multiple imputations.
• recognize situations where bootstrap and permutation tests can support inference.

Competence and skills

• adapt and estimate the model, as well as diagnose the fit and interpret the results of generalized linear (mixed) models discussed in the course.
• perform a regression analysis involving multiple imputations of missing data and report the results.
• apply bootstrap and permutations for inference and report the results.

Judgement and approach

• discuss the steps involved in planning, conducting, and reporting a simulation study for assessing statistical methods and how the steps contribute to sustainable research.
• discuss the choice of statistical method in different studies, based on the research question and the type and structure of the data.

The course is a mixture of lectures, seminars and computer sessions.

Language of instruction: English

The course is examined through an individual on-campus written exam (3.5 credits) and active participation in two compulsory seminars (2 credits) and two compulsory computer sessions (2 credits) with accompanying written reports. Completion of non-approved compulsory elements will be offered and is to be carried out according to the teacher's instructions.

If a student who has been failed twice for the same examination element wishes to change examiner before the next examination session, such a request is to be granted unless there are specific reasons to the contrary (Chapter 6 Section 22 HF).

If a student has received a certificate of disability study support from the University of Gothenburg with a recommendation of adapted examination and/or adapted forms of assessment, an examiner may decide, if this is consistent with the course’s intended learning outcomes and provided that no unreasonable resources would be needed, to grant the student adapted examination and/or adapted forms of assessment.

If a course has been discontinued or undergone major changes, the student must be offered at least two examination sessions in addition to ordinary examination sessions. These sessions are to be spread over a period of at least one year but no more than two years after the course has been discontinued/changed. The same applies to placement and internship (VFU) except that this is restricted to only one further examination session.

If a student has been notified that they fulfil the requirements for being a student at Riksidrottsuniversitetet (RIU student), to combine elite sports activities with studies, the examiner is entitled to decide on adaptation of examinations if this is done in accordance with the Local rules regarding RIU students at the University of Gothenburg.

The grading scale comprises: Pass with distinction (VG), Pass (G) and Fail (U). The compulsory computer sessions and seminars are graded Pass (G) and Fail (U), while the individual written exam is graded Pass with Distinction (VG), Pass (G) and Fail (U).

To obtain a Pass grade for the course, a Pass grade is required for the compulsory computer sessions, for the seminars, and for the written exam. To obtain a Pass with Distinction grade for the course, a Pass grade is required for the compulsory components and a Pass with Distinction grade for the individual written exam.

The course evaluation is carried out in the form of an anonymous questionnaire. A compilation of the questionnaire is done by the course coordinator. The results of and possible changes to the course will be shared with students who participated in the evaluation and students who are starting the course.

Each student needs access to a laptop (at least 8 GB RAM recommended) with R and RStudio (or other user interface for R) installed.