Further Survey Estimation

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• evaluate the uncertainty associated with an estimation method.
• understand the differences between design-based and model-based approaches to sample survey estimation;
• assess the advantages and disadvantages of an estimator with respective to the underlying model assumptions and the sampling design;
• apply the estimation methods in common use of survey sampling;

• Historical overview.
• Design-based survey estimation.
• Conceptual problems of design-based inference.
• Model-assisted survey estimation (post-stratification, ratio estimation, regression estimation).
• Model-based survey estimation.
• Variance estimation.

Teaching and learning methods

A variety of methods will be used including lectures and workshops/tutorials, mixed in a 5 day course designed for students on release from the workplace. Students are also expected to read wider than the lecture material as part of their individual study, and to critically appraise different approaches.

Resources & Reading list

Journal Articles

Deville,J.-C. and Sarndal,C.-E (1992). Calibration Estimators in Survey Sampling.. Journal of the American Statistical Association, 87, 376-382.

Textbooks

Cochran, W.G (1977). Sampling Techniques. New York: Wiley.

Valliant, R., Dorfman, A.H. and Royall, R.M. (2000). Finite Population Sampling and Inference. New York: Wiley.

Chambers, R.L. and Clark, R.G. (2012). An Introduction to Model-Based Survey Sampling with Application. Oxford: OUP.

Sarndal, C.-E., Swensson, B. and Wretman, J (1992). Model Assisted Survey Sampling. New York: Springer-Verlag.

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