THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : Deanery of Molecular, Genetic and Population Health Sciences : Public Health Research

Postgraduate Course: Statistical Modelling (PUHR11040)

Course Outline
SchoolDeanery of Molecular, Genetic and Population Health Sciences CollegeCollege of Medicine and Veterinary Medicine
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course describes the main principles of statistical modelling and introduces three types of model commonly used in epidemiological studies: linear regression, logistic regression and survival analysis.
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Introduction to Statistics (PUHR11050) AND Further Statistics (PUHR11051)
Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2020/21, Available to all students (SV1) Quota:  None
Course Start Block 3 (Sem 2)
Course Start Date 11/01/2021
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 10, Revision Session Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 76 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Data analysis project (100%)
Feedback Not entered
No Exam Information
Learning Outcomes
Show knowledge of and ability to select and interpret results of suitable analytical approaches to statistical modelling.

Show knowledge of approaches to exploring interactions and confounding. Understand the principles of good practice in model building and validation.

Demonstrate an understanding of the interpretation of linear regression, logistic regression and survival analyses.

Undertake logistic regression analyses appropriately using statistical software.

Topics to be covered include:
¿Simple and multifactorial linear models, including ANOVA models
¿binary logistic regression
¿Kaplan-Meier plots and log-rank tests
¿Cox proportional hazards model
¿methods for assessing appropriate formats for including explanatory variables
¿variable selection methods
¿diagnostic methods
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsStatistics,statistical methods,R,SPSS,modelling,regression,linear,logistic,survival analysis
Contacts
Course organiserDr Niall Anderson
Tel: (0131 6)50 3212
Email: Niall.Anderson@ed.ac.uk
Course secretaryMs Charlotte Munden
Tel: (0131 6)50 3227
Email: cmunden2@ed.ac.uk
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