The aim of this module is to develop students' understanding of the nature of studies to monitor and evaluate intervention programmes, using examples from Government and other related areas. There is a particular focus on the contribution of statistical methods in both the design and analysis of such studies.
Pre-requisite: STAT6083 or STAT6095 or STAT6117
Aims and Objectives
Having successfully completed this module you will be able to:
- Understand and be able to apply broad principles to guide the choice between alternative statistical designs that can accommodate the evaluation of an intervention
- Understand and be able to articulate the important role monitoring plays, both as a policy tool in its own right and as an aid to evaluation.
Alternative experimental and quasi-experimental designs for evaluation programmes and the principles underlying the choice between these designs
- Data sources and research methods
- Performance monitoring
- Theoretical framework
- Randomized controlled trials
General statistical methods that can be used in the analysis of data devised from such designs, in particular for the estimation of programme effects, allowing for potential confounding factors
- Regression adjustment and other analysis methods
- Propensity score matching
- Econometric methods of analysis
Learning and Teaching
|Total study time||100|
Resources & Reading list
Laboratory space and equipment required. Computing Laboratory with access to Excel, including Data Analysis Toolkit, and R
The Magenta Book: Guidance Notes for Policy Evaluation and Analysis, background paper 7 ‘ Why do social experiments? Experiments and quasi-experiments forevaluating government policies and programmes’.
Ravallion M (2001). The Mystery of the Vanishing Benefits: An Introduction to Impact Evaluation. World Bank Economic Review, 15(1), pp. 115-40.
J.D. Angrist and J.-S. Pischke (2009). Mostly Harmless Econometrics: an Empiricist's Companion. Oxford: Princeton University Press.
J.D. Angrist and J.-S. Pischke (2015). Mastering Metrics: the Path from cause to Effect. Oxford: Princeton University Press.
This is how we’ll formally assess what you have learned in this module.
This is how we’ll assess you if you don’t meet the criteria to pass this module.
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 type: Internal & External