Back to required readings:

On Likelihoodism:

• Fitelson, Likelihoodism, Bayesianism, and Relational Confirmation

• D. Steel, Bayesian Confirmation Theory and the Likelihood Principle

• Fitelson, The Plurality of Bayesian Measures of Confirmation and the Problem of Measure Sensitivity (on Bayesian confirmation)

• Eells and Fitelson, Measuring Confirmation and Evidence (on Bayesian confirmation)
• Royall, The First Principle (Chapter 1 of Statistical Evidence: A Likelihood Paradigm) (Likelihoodism - more technical treatment)
  
  

On Frequentism

• S. Goodman and R. Royall, Evidence and Scientific Research

• S. Goodman, Toward Evidence-Based Medical Statistics I – the P-value Fallacy

• S. Goodman, Toward Evidence-Based Medical Statistics 2 – the Bayes Factor

• Royall, Neyman-Pearson theory (Chap 2 of Statistical Evidence)

• Royall, Fisherian theory (Chap 3 of Statistical Evidence)

• Neyman and Pearson, On the problem of the most efficient tests of statistical hypotheses (the original foundational paper)

• The New Math of Clinical Trials (the Bayesian doctor)

      

   On Stopping Rules:

• Steel, A Bayesian way to make stopping rules matter

• Mayo Why you cannot be just a little bit Bayesian (Chap 10 of Error and the Growth of Experimental Knowledge)

• Backe, The Likelihood Principle and the reliability of experiments 

• Kadane et al. When several bayesians agree that there will be no reasoning to a forgone conclusion (very technical facts about stopping rules)