This topic shows students how to conduct a sensitivity analysis, the process where the results of a model are recalculated under a series of varying assumptions and predictions. It is often referred to informally as ‘what-if’ analysis (Graham).
Topic Learning Outcome: Students will understand the uses of sensitivity analysis, and will be developing a working knowledge of how to identify useful assumptions and predictions to include in sensitivity analyses and conduct these types of analyses themselves.
Core Concepts associated with this Topic: Diagnostic Procedures; Logic Model.
Harvard University: API-208 Program Evaluation: Estimating Program Effectiveness with Empirical Analysis
Rosenbaum, P.R. (2005), "Sensitivity Analysis in Observational Studies," Encyclopedia of Statistics in Behavioral Science, vol. 4, 1809-1814.
Imbens, G.W. (2003), "Sensitivity to Exogeneity Assumptions in Program Evaluation," American Economic Review (Papers & Proceedings), vol. 93(2), 126-132.
Rosenbaum, P.R. (2002), Observational Studies. New York: Springer-Verlag. Chapter 4.
Rosenbaum, P.R. and D.B. Rubin (1983), "Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome," Journal of the Royal Statistical Society. Series B, vol. 45(2), 212-218.
Sample Assessment Questions:
1.) What is sensitivity analysis? Why is this an important topic for students of public administration to study?
2.) What is a logic model? Draw a mock logic model for any public policy/program of your choice.
Page created by Sean Goertzen and Ben Eisen on 21 May 2015.