Methodology in Practice: Statistical Misspecification Testing

Deborah G. Mayo · Aris Spanos

120 citations0/0 files storedPhilosophy of Science

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Philosophy and History of Science Philosophy, Science, and History Statistical Methods and Bayesian Inference

Abstract

The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle ‘practical’ problems of model validation, and conversely, a methodology of statistical model validation can shed light on a number of issues of interest to philosophers of science.

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References

1996Error and the Growth of Experimental Knowledge 1994How to Tell When Simpler, More Unified, or LessAd HocTheories will Provide More Accurate Predictions 1998Causality in Crisis? Statistical Methods and the Search for Causal Knowledge in the Social Sciences 1991Novel Evidence and Severe Tests

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