# Alphabet Soup

@article{Hubbard2004AlphabetS, title={Alphabet Soup}, author={Raymond Hubbard}, journal={Theory \& Psychology}, year={2004}, volume={14}, pages={295 - 327} }

Confusion over the reporting and interpretation of results of commonly employed classical statistical tests is recorded in a sample of 1,645 papers from 12 psychology journals for the period 1990 through 2002. The confusion arises because researchers mistakenly believe that their interpretation is guided by a single unified theory of statistical inference. But this is not so: classical statistical testing is a nameless amalgamation of the rival and often contradictory approaches developed by…

## 84 Citations

### Tests of Statistical Significance Made Sound

- PsychologyEducational and psychological measurement
- 2017

It is suggested that to correct for the deficiencies of the hybrid, psychology avail itself of two important and more recent viewpoints on ToSS, namely the neo-Fisherian and the error-statistical perspectives.

### The statistical theories of Fisher and of Neyman and Pearson: A methodological perspective

- Psychology
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Most of the debates around statistical testing suffer from a failure to identify clearly the features specific to the theories invented by Fisher and by Neyman and Pearson. These features are…

### Null hypothesis significance tests. A mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations

- EducationScientometrics
- 2014

The theoretical origins of NHST are introduced to the scientometric community, which is mostly absent from standard statistical textbooks, and some of the most prevalent problems relating to the practice are discussed and traced back to the mix-up of the two different theoretical origins.

### Blinding Us to the Obvious? The Effect of Statistical Training on the Evaluation of Evidence

- PsychologyManag. Sci.
- 2016

Dichotomization of evidence is reduced though still present when researchers are asked to make decisions based on the evidence, particularly when the decision outcome is personally consequential.

### Why P Values Are Not a Useful Measure of Evidence in Statistical Significance Testing

- Psychology
- 2008

Reporting p values from statistical significance tests is common in psychology's empirical literature. Sir Ronald Fisher saw the p value as playing a useful role in knowledge development by acting as…

### Détente: A Practical Understanding of P values and Bayesian Posterior Probabilities

- PsychologyClinical pharmacology and therapeutics
- 2020

The fundamental differences in NHST and Bayesian approaches are explained and how they can co‐exist harmoniously to guide clinical trial design and inference is demonstrated.

### “Repeated sampling from the same population?” A critique of Neyman and Pearson’s responses to Fisher

- PsychologyEuropean Journal for Philosophy of Science
- 2020

Fisher ( 1945a , 1945b , 1955 , 1956 , 1960 ) criticised the Neyman-Pearson approach to hypothesis testing by arguing that it relies on the assumption of “repeated sampling from the same population.”…

### Design sensitivity and statistical power in acceptability judgment experiments

- Psychology
- 2017

The goals of the current study are to provide a fuller picture of the status of acceptability judgment data in syntax, and to provide detailed information that syntacticians can use to design and evaluate the sensitivity of acceptable judgment experiments in their own research.

### Significance tests as sorcery: Science is empirical—significance tests are not

- Education
- 2012

Since the 1930s, many of our top methodologists have argued that significance tests are not conducive to science. Bakan (1966) believed that “everyone knows this” and that we slavishly lean on the…

### Before p < 0.05 to Beyond p < 0.05: Using History to Contextualize p-Values and Significance Testing

- SociologyThe American statistician
- 2019

History enables students, practitioners, and statisticians to treat the discipline as an ongoing endeavor, crafted by fallible humans, and provides a deeper understanding of the subject and its consequences for science and society.

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