Brown, Lawrence D2023-05-232023-05-232007-01-012016-07-14https://repository.upenn.edu/handle/20.500.14332/47900Outside 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 modelsBayesian forecastingcall centercubic smoothing splineinhomogeneous Poisson processMarkov chain Monte Carlomultiplicative modelsequential Monte Carlostate-space modelStatistics and ProbabilityArticle