# Theoretical objections to hypothesis testing [duplicate]

We've all seen how $p$-values can be misinterpreted to draw false inferences. However, I'm interested in learning more about theoretical/mathematical/philosophical objections to the hypothesis-testing-paradigm, ie. I'd like to learn why someone would prefer (say) a likelihood ratio over a hypothesis test.

I've read some articles by Andrew Gelman on this topic, but I'm trying to find more literature. Any help would be greatly appreciated.

• Couple of books that you might be interested in "What if there were no significance tests?", edited by Harlow, Mulaik and Steiger, and "The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives" by Ziliak and McCloskey. – Jeremy Miles Mar 26 '13 at 15:14
• This is just my own opinion, but too many people confuse statistical hypotheses with scientific ones. Even if you have "rejected the null hypothesis" that some statistical parameter = 0, it doesn't necessarily mean you've even asked a scientific question (from a philosophical, epistemological point of view). – D L Dahly Mar 26 '13 at 19:04
• – Michael Bishop Mar 26 '13 at 19:57

Try also the phrase +bayesian significance testing fisher in Google Scholar and I guarantee you will find at least dozen good references (and some interesting info too).