Complex Survey Data Analysis

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Estimate model parameters and assess the estimation errors, taking into account of the sampling feature (weighting, stratification and clustering), using STATA
• Understand the principle of finite-population inference, including understanding the most common modelling approaches.
• Use basic weighting and imputation approaches for nonresponse adjustment.

Effects of finite-population sampling on standard statistical analysis methods

Introduction to statistical inference framework

Linear regression based on complex survey data

Testing and model selection

Logistic and log-linear models

Dealing with missing observations

Teaching and learning methods

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

Resources & Reading list

Textbooks

Chambers, R.L. and Skinner, C.J. (eds.) (2003). Analysis of Survey Data.. Chichester: John Wiley.

Skinner, C.J., Holt, D. and Smith, T.M.F. (eds.) (1989). Analysis of Complex Surveys. Chichester: John Wiley.

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 Information

Repeat type: Internal & External