Statistical Inference as Severe Testing How to Get Beyond the Statistics Wars 1st Edition by Deborah Mayo ISBN 1107664640 9781107664647

Excursion 1: How to Tell What’s True about Statistical Inference

Tour I: Beyond Probabilism and Performance

• 1.1 Severity Requirement: Bad Evidence, No Test (BENT)
• 1.2 Probabilism, Performance, and Probativeness
• 1.3 The Current State of Play in Statistical Foundations: A View From a Hot-Air Balloon

Tour II: Error Probing Tools versus Logics of Evidence

• 1.4 The Law of Likelihood and Error Statistics
• 1.5 Trying and Trying Again: The Likelihood Principle

Excursion 2: Taboos of Induction and Falsification

Tour I: Induction and Confirmation

• 2.1 The Traditional Problem of Induction
• 2.2 Is Probability a Good Measure of Confirmation?

Tour II: Falsification, Pseudoscience, Induction

• 2.3 Popper, Severity, and Methodological Probability
• 2.4 Novelty and Severity
• 2.5 Fallacies of Rejection and an Animal Called NHST
• 2.6 The Reproducibility Revolution (Crisis) in Psychology
• 2.7 How to Solve the Problem of Induction Now

Excursion 3: Statistical Tests and Scientific Inference

Tour I: Ingenious and Severe Tests

• 3.1 Statistical Inference and Sexy Science: The 1919 Eclipse Test
• 3.2 N-P Tests: An Episode in Anglo-Polish Collaboration
• 3.3 How to Do All N-P Tests Do (and More) While a Member of the Fisherian Tribe

Tour II: It’s the Methods, Stupid

• 3.4 Some Howlers and Chestnuts of Statistical Tests
• 3.5 P-values Aren’t Error Probabilities Because Fisher Rejected Neyman’s Performance Philosophy
• 3.6 Hocus-Pocus: P-values Are Not Error Probabilities, Are Not Even Frequentist!

Tour III: Capability and Severity: Deeper Concepts

• 3.7 Severity, Capability, and Confidence Intervals (CIs)
• 3.8 The Probability Our Results Are Statistical Fluctuations: Higgs’ Discovery

Excursion 4: Objectivity and Auditing

Tour I: The Myth of “The Myth of Objectivity”

• 4.1 Dirty Hands: Statistical Inference Is Sullied with Discretionary Choices
• 4.2 Embrace Your Subjectivity

Tour II: Rejection Fallacies: Who’s Exaggerating What?

• 4.3 Significant Results with Overly Sensitive Tests: Large n Problem
• 4.4 Do P-Values Exaggerate the Evidence?
• 4.5 Who’s Exaggerating? How to Evaluate Reforms Based on Bayes Factor Standards

Tour III: Auditing: Biasing Selection Effects and Randomization

• 4.6 Error Control is Necessary for Severity Control
• 4.7 Randomization

Tour IV: More Auditing: Objectivity and Model Checking

• 4.8 All Models Are False
• 4.9 For Model-Checking, They Come Back to Significance Tests
• 4.10 Bootstrap Resampling: My Sample Is a Mirror of the Universe
• 4.11 Misspecification (M-S) Testing in the Error Statistical Account

Excursion 5: Power and Severity

Tour I: Power: Pre-data and Post-data

• 5.1 Power Howlers, Trade-offs, and Benchmarks
• 5.2 Cruise Severity Drill: How Tail Areas (Appear to) Exaggerate the Evidence
• 5.3 Insignificant Results: Power Analysis and Severity
• 5.4 Severity Interpretation of Tests: Severity Curves

Tour II: How Not to Corrupt Power

• 5.5 Power Taboos, Retrospective Power, and Shpower
• 5.6 Positive Predictive Value: Fine for Luggage

Tour III: Deconstructing the N-P versus Fisher Debates

• 5.7 Statistical Theatre: “Les Miserables Citations”
• 5.8 Neyman’s Performance and Fisher’s Fiducial Probability

Excursion 6: (Probabilist) Foundations Lost, (Probative) Foundations Found

Tour I: What Ever Happened to Bayesian Foundations?

• 6.1 Bayesian Ways: From Classical to Default
• 6.2 What Are Bayesian Priors? A Gallimaufry
• 6.3 Unification or Schizophrenia: Bayesian Family Feuds
• 6.4 What Happened to Updating by Bayes’ Rule?

Tour II: Pragmatic and Error Statistical Bayesians

• 6.5 Pragmatic Bayesians
• 6.6 Error Statistical Bayesians: Falsificationist Bayesians
• 6.7 Farewell Keepsake