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PU5569: UNDERSTANDING AND APPLYING REGRESSION MODELS (2023-2024)

Last modified: 15 Nov 2023 14:46


Course Overview

This course intends to develop a student’s statistical skills and understanding so that they can apply common multivariate regression modelling techniques to a range of health research data. The course will focus on the application, interpretation and communication of common regression models, including general linear models, log-linear models, logistic regression, and survival analysis. It assumes that students will already have completed a first course in statistics and have an understanding of bivariate techniques and basic mathematical skills.

Course Details

Study Type Postgraduate Level 5
Session Second Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr David McLernon
  • Dr Rute Vieira

What courses & programmes must have been taken before this course?

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

Are there a limited number of places available?

No

Course Description

Health research often involves complex data which needs multivariate statistical techniques to answer research questions. This course will introduce you to key concepts in advanced regression modelling which can be applied to a range of data. It will cover some of the theory underlying different regression models and then take a practical approach to teach you how to investigate data in different contexts. You will use the statistical software package (SPSS) to apply different multivariate regression models, including how to check model assumptions, adjust for confounding and assess the model suitability. You will have the opportunity to analyse a variety of data sets and practice communicating the rationale for choice of statistical method and interpretation of results for a scientific audience.


Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

  • 1 Tutorial during University weeks 26 - 35, 39 - 40

More Information about Week Numbers


Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 20
Assessment Weeks 29 Feedback Weeks 30

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Feedback

Students will complete MCQ assessment in MyAberdeen which will cover course materials. Feedback will be obtained via on online session.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandUnderstand and describe the rationale for using multivariate regression models.
FactualEvaluateCheck a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit
ProceduralAnalyseSelect and apply an appropriate regression model and interpret its results.
ProceduralApplyEmploy the statistical package SPSS to analyse data using regression methods
ReflectionCreateCommunicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience.

Project Report/Dissertation

Assessment Type Summative Weighting 40
Assessment Weeks 35 Feedback Weeks 40

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Feedback

Students will submit a final report based on the analysis arising from their project plan in teaching week 10 with final feedback by teaching week 12.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandUnderstand and describe the rationale for using multivariate regression models.
FactualEvaluateCheck a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit
ProceduralAnalyseSelect and apply an appropriate regression model and interpret its results.
ProceduralApplyEmploy the statistical package SPSS to analyse data using regression methods
ReflectionCreateCommunicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience.

Class Test - Multiple Choice Questions

Assessment Type Summative Weighting 40
Assessment Weeks 39 Feedback Weeks 40

Look up Week Numbers

Feedback

Students will complete MCQ assessment in MyAberdeen which will cover course materials. Feedback will be obtained via on online session.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandUnderstand and describe the rationale for using multivariate regression models.
FactualEvaluateCheck a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit
ProceduralAnalyseSelect and apply an appropriate regression model and interpret its results.
ReflectionCreateCommunicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience.

Formative Assessment

Project Plan, Summary or Abstract

Assessment Type Formative Weighting
Assessment Weeks 29 Feedback Weeks 30

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Feedback

Students will submit a brief project plan in teaching week 4 with written feedback by teaching week 5 and optional consultation with tutor.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualUnderstandUnderstand and describe the rationale for using multivariate regression models.

Resit Assessments

Exam

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

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Feedback

Feedback will be released with grade and will provide additional written commentary to facilitate ongoing learning 

Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
FactualEvaluateCheck a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit
ProceduralApplyEmploy the statistical package SPSS to analyse data using regression methods
ConceptualUnderstandUnderstand and describe the rationale for using multivariate regression models.
ReflectionCreateCommunicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience.
ProceduralAnalyseSelect and apply an appropriate regression model and interpret its results.

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