WASP - Advanced Logistic Regression
The Wolfson Research Institute for Health and Wellbeing (WRIHW) of Durham University is offering an advanced course on Applied Logistic Regression. The course will build on our previous course on Basic Statistics with specific focus on multiple logistic regressions and analysis of correlated binary data. We will discuss how to estimate odds ratio for categorical and continuous predictors, and also how to transform odds ratio into probabilities. For the correlated data, we will discuss how to perform robust analysis for panel and clustered data using different correlation structures including exchangeable correlation, auto-regression and unstructured correlation structures. The case studies will be analysed using both the graphical user interface and syntax of Statistical Package for the Social Sciences (SPSS).
This course requires knowledge of basic statistics and regression analysis. It is a participant oriented course, where statistical concepts will be explained using practical examples. Participants will have lots of opportunity to try out data analysis under the supervision of the course leaders. Participants can also bring their own project data for the practical sessions.
The course will run on 29-30th June 2015 at the Durham campus including tea-coffee and lunch for participants. Student/staff at Durham University are all welcome to participate.
Timings and Agenda
|Timings||29 June||30 June|
|9.30am - 10.00am||Registration/Coffee||Registration/Coffee|
|10.00am - 12.00pm||Multiple Logistic Regression with categorical indicators||Correlated data analysis|
|12.00pm - 1.00pm||Lunch||Lunch|
|1.00pm - 2.40pm||Multiple Logistic Regression with continuous indicators||Correlated data analysis|
|2.40pm - 3pm||Break||Break|
|3.00pm - 4.00pm||Practical||Practical|
Registration is essential as places are limited to 20. To book your place, please click here to take you to the online booking form. Places will be allocated in order of receipt. Please ensure you have permission from your Supervisor/Line Manager to attend this two-day course.
Contact email@example.com for more information about this event.