Date of this Version
Journal of the American Statistical Association
Outside the field of statistics, the literature on observational studies offers advice about research designs or strategies for judging whether or not an association is causal, such as multiple operationalism or a dose-response relationship. These useful suggestions are typically informal and qualitative. A quantitative measure, design sensitivity, is proposed for measuring the contribution such strategies are then evaluated in terms of their contribution to design sensitivity. A related method for computing the power of a sensitivity analysis is also developed.
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on 01 Jan 2012, available online: http://wwww.tandfonline.com/10.1198/016214506000001455.
autoregressive models, Bayesian forecasting, call center, cubic smoothing spline, inhomogeneous Poisson process, Markov chain Monte Carlo, multiplicative model, sequential Monte Carlo, state-space model
Brown, L. D. (2007). Design Sensitivity in Observational Studies. Journal of the American Statistical Association, 102 (480), 1185-1198. Retrieved from https://repository.upenn.edu/statistics_papers/506
Date Posted: 27 November 2017