Advanced Statistical Modelling

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Conduct and interpret advanced statistical modelling techniques in generalised linear models, including log-linear models.
• Apply multilevel models to real data (e.g. hierarchical and longitudinal data) and to ensure assumptions of the models are satisfied.
• Interpret and draw conclusions from the statistical analyses performed.
• Recognise the basic statistical theory underpinning multilevel models, e.g. identify when a multilevel model is appropriate.
• Use statistical software to perform multilevel statistical analysis.

• Revision of Generalised Linear Model
• Log-linear model
• Hierarchical data structures
• Multilevel models:

oRandom intercepts and random slopes

oContextual variables

oCross-level interactions

oHeterogeneous variance structures

oBinary, counts, and continuous responses.

• Model building:

oEstimation

oTesting

oDiagnostic checking (specification issues and residual analysis)

oModel selection

Teaching and learning methods

Teaching is delivered through lectures, computer workshops, and tutorials.

Resources & Reading list

Textbooks

Agresti, A. (2013). (2013). Categorical Data Analysis. . Wiley .

Bryk, A.S. and Raudenbush, S.W (1992, 2002 ). Hierarchical Linear Models: Applications and Data Analysis Methods.. Newbury Park, CA : Sage .

Singer, Judith D., Willett, John B (2003). Applied Longitudinal Data Analysis: Modelling Change andEvent Occurrence.. New York : Oxford University Press.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Repeat Information

Repeat type: Internal & External