Analysis of Complex Survey Data

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Have a solid foundation in the conceptual issues associated with statistical modelling using complex survey data
• Have practical skills in the use of STATA to fit both linear and logistic regression models and to perform tests for independence of tabular data, while accounting for survey weights, stratification and clustering
• Be able to apply methods for statistical analysis based on complex survey data

• Survey design and sample weights
• Descriptive design-based inference
• Analytical inference and further inference topics
• Regression modelling with complex survey data
• Parametric models and pseudo-maximum likelihood
• Logistic regression with complex survey data
• Hypothesis testing and model selection in complex surveys
• Goodness-of-fit tests
• Tests for two-way tables in complex surveys

Teaching and learning methods

The module comprises a series of classroom lectures intertwined with individual study and computer lab sessions where students are expected to put in practice the topics presented in class.

Resources & Reading list

General Resources

Background textbooks. Skinner, C.J., Holt, D. and Smith, T.M.F. (eds.) (1989). Analysis of Complex Surveys. Chichester: John Wiley. Chambers, R.L. and Skinner, C.J. (eds.) (2003). Analysis of Survey Data. Chichester: John Wiley. Heeringa, S.G., West, C.T. and Berglund, P.A. (2010) Applied Survey Data Analysis. Boca Raton: CRC Press.

Software requirements. STATA You will require access to the computer lab and to STATA software, which is available on the University’s computer workstations.

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.