Last modified: 08 Nov 2023 14:16
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.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Session | Second Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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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.
| Assessment Type | Summative | Weighting | 40 | |
|---|---|---|---|---|
| Assessment Weeks | 39 | Feedback Weeks | 40 | |
| Feedback |
Students will complete MCQ assessment in MyAberdeen which will cover course materials. Feedback will be obtained via on online session. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand and describe the rationale for using multivariate regression models. |
| Factual | Evaluate | Check a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit |
| Procedural | Analyse | Select and apply an appropriate regression model and interpret its results. |
| Reflection | Create | Communicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience. |
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | 29 | Feedback Weeks | 30 | |
| Feedback |
Students will complete MCQ assessment in MyAberdeen which will cover course materials. Feedback will be obtained via on online session. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand and describe the rationale for using multivariate regression models. |
| Factual | Evaluate | Check a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit |
| Procedural | Analyse | Select and apply an appropriate regression model and interpret its results. |
| Procedural | Apply | Employ the statistical package SPSS to analyse data using regression methods |
| Reflection | Create | Communicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience. |
| Assessment Type | Summative | Weighting | 40 | |
|---|---|---|---|---|
| Assessment Weeks | 35 | Feedback Weeks | 40 | |
| 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. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand and describe the rationale for using multivariate regression models. |
| Factual | Evaluate | Check a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit |
| Procedural | Analyse | Select and apply an appropriate regression model and interpret its results. |
| Procedural | Apply | Employ the statistical package SPSS to analyse data using regression methods |
| Reflection | Create | Communicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience. |
| Assessment Type | Formative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | 29 | Feedback Weeks | 30 | |
| Feedback |
Students will submit a brief project plan in teaching week 4 with written feedback by teaching week 5 and optional consultation with tutor. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Understand and describe the rationale for using multivariate regression models. |
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Feedback will be released with grade and will provide additional written commentary to facilitate ongoing learning |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Reflection | Create | Communicate the process and results of regression models using written, tabular and graphical displays as appropriate for a scientific audience. |
| Conceptual | Understand | Understand and describe the rationale for using multivariate regression models. |
| Procedural | Apply | Employ the statistical package SPSS to analyse data using regression methods |
| Factual | Evaluate | Check a model’s assumptions, adjust for confounding and use strategies to assess a model’s suitability and fit |
| Procedural | Analyse | Select and apply an appropriate regression model and interpret its results. |
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