‘Advanced Statistical Modelling’ will provide an introduction to some advanced statistical modelling methods commonly used in epidemiological and public health research. This involves looking at different models used in this field of research: multilevel models, principal component models, factor models, and path models. Multilevel models allow the study of influences on health that operate at different levels, such as the study of association characteristics and health of individuals. Principal components models are used to form new linear composite variables of original variables. Factor models are used to develop scales which measure latent or unobservable constructs. Moreover, an introduction to structural equation models (SEMs) which allow the testing of complex models involving hypothesised pathways between risk factors and disease will be given. Finally, students will be introduced to the statistical methods for dealing with missing data.

After taking this module, you should be familiar with some advanced statistical methods commonly used in epidemiological and public health research. More specifically, for each model covered in the course you should be able to:


	Describe the statistical method and understand when it is appropriate to apply the method;
	
	
	Understand how to interpret results from analyses using each method;
	
	
	Describe methods to check main assumptions underlying the method;
	
	
	Interpret the results of statistical analyses reported in the health literature;
	
	
	Perform statistical analyses using STATA, and;
	
	
	Interpret findings from statistical analyses, and present these findings in a clear, concise, and logical manner.
	
The module may is attended by many students from the MSc/Dip Social Epidemiology, and by other postgraduate students from the Faculty of Population Health Sciences. Spaces on this module are limited to 50.

You will attend lectures (60-90 minutes) followed by computer-based practical sessions (90-120 minutes) for which the statistical package STATA will be used. There may be two or three additional non-practical sessions to review practical work. Teaching materials for this module will be placed on Moodle, providing online access to lecture notes and practical assignments.