Introduction to Longitudinal Analysis Using Stata
Please book your place on-line below:
£340.00: Imperial College only.
£620.00: External rate.
- Thur 17 & Fri 18 January 2019
- Thur 01 & Fri 02 August 2019
Time and Location
Location: Imperial College London (exact details will follow once your booking has been confirmed)
Please book your course on-line by clicking on your chosen date above. Any problems with booking, please contact Krupa Shukla on +44 (0)20 7594 1754 or email@example.com
This is a 2 day practical PC-based workshop on Statistical Methods Applied to longitudinal data. In longitudinal studies observations on individuals are measured repeatedly through time. This type of design allows the user to estimate the marginal effect of factors/covariates of interest, as well as to assess changes over time. Longitudinal data require special statistical methods, as observations made on each subject cannot be assumed to be independent, making traditional regression methods inappropriate.
The methodology for analyzing longitudinal data takes the correlation between measurements over time into account.
In this course we will present some of the approaches used in longitudinal data analysis, through work examples covering exploratory analysis, modeling and interpretation of the results.
Course Outline (2018/19)
- Features and Merits Longitudinal Data
- Longitudinal analysis considerations
- Data layout for Stata Mixed
- Exploring Longitudinal data
Models for the Mean Response
- Profile Analysis: Specifying the Covariance Structure, Model Fit and Model Comparison
- Parametric Curves
Random Coefficients Approach
- Random Intercept Model
- Random Intercept and Random Slope Model
- An application to a continuous response
- An application to a binary response
Entry Requirements: To attend this course you should be familiar with the Stata software, possess a good working knowledge of Multiple Linear Regression and ANCOVA. You should also be able to demonstrate a good understanding of concepts such as “Main effects”, ”Interaction Effects” , “Test of Hypotheses” and “Statistical significance”.
Tutor: Dr Fabiana Gordon
This course has been approved by the Royal College of Physicians for 12 CPD credits.
If you are not able to attend on the day, please contact firstname.lastname@example.org as soon as you can.