Postgraduate Course: Further Statistical Modelling (PUHR11041)
Course Outline
| School |
School of Clinical Sciences and Community Health |
College |
College of Medicine and Veterinary Medicine |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 11 (Postgraduate) |
Credits |
10 |
| Home subject area |
Public Health Research |
Other subject area |
None |
| Course website |
None |
|
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| Course description |
This course describes the principles of statistical methods suited to modeling continuous and survival data, and considers how these should be interpreted appropriately. |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
None
|
| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2010/11 Block 4 (Sem 2), Available to all students (SV1)
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WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| No Classes have been defined for this Course |
| First Class |
First class information not currently available |
Summary of Intended Learning Outcomes
To introduce students to statistical methods for modelling continuous and survival data, and to provide training and experience in applying these appropriately using statistical software and then to interpret findings. Builds on the general modelling principles established in the Statistical Modelling prerequisite course.
Statistics, linear regression, Poisson regression, survival analysis, Cox model
Demonstrate an understanding of the application and interpretation of linear models such as Analysis of Variance, and multiple regression models.
Show familiarity with the Poisson distribution and Poisson regression and in particular with their application to the calculation of standardised rates.
Recognise the need for specialised techniques for survival data, and demonstrate an understanding of the application and interpretation of Kaplan-Meier methods and Cox proportional hazards models in this situation.
Select and apply methods suitable for measurement validation.
Show knowledge of and ability to use suitable generic principles of statistical modelling, for exploring interactions and confounding, selecting variables and choosing appropriate explanatory variable formats.
Undertake modelling appropriately using statistical software.
Methods to be covered include:
&·multiple regression and analysis of variance and interpretation of results;
&·confounding and interactions in continuous data;
&·intra-class correlations and Bland-Altman plots for measurement data;
&·Poisson regression;
&·Kaplan-Meier plots and log-rank tests;
&·Cox proportional hazards model.
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Assessment Information
| Assignment comprising of a data analysis project and report. |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Niall Anderson
Tel: (0131 6)50 3212
Email: Niall.Anderson@ed.ac.uk |
Course secretary |
Ms Margaret Luttrell
Tel:
Email: Maggie.Luttrell@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:37 am
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