Statistical Methods in Psychology Journals¶
Wilkinson, L. (1999). Statistical Methods in Psychology Journals: Guidelines and Explanations. American Psychologist, 54(8), 594-604.
Cited by¶
6 citations across 6 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Confidence Intervals
- Additional canonical references in this cluster: , ,
This sourceAPA Task Force guidelines urging reporting of effect sizes and confidence intervals alongside (or instead of) significance tests. WebSearch-verified (Am Psychologist 54(8):594-604).
- Additional canonical references in this cluster: , ,
- Effect Size
- Contemporary psychology distinguishes standardized d (for cross-study meta-analysis) and unstandardized raw differences (for interpretability within a study), with reporting guidance favoring both
Supported in partVerified against the work's full text
The Task Force says always report effect sizes and prefer unstandardized ones when units are meaningful, noting effect sizes serve meta-analysis; it does not assign d to cross-study use.
“If the units of measurement are meaningful on a practical level (e.g., number of cigarettes smoked per day), then we usually prefer an unstandardized measure (regression coefficient or mean difference)”
- Contemporary psychology distinguishes standardized d (for cross-study meta-analysis) and unstandardized raw differences (for interpretability within a study), with reporting guidance favoring both
- Hypothesis Testing (Null vs. Alternative)
- Cross-domain transfer is productive: hypothesis-testing methodology from agriculture to clinical trials to A/B testing; multiplicity-adjustment methods from genomics to social-science panel studies; pre-registration practices from clinical trials to psychology to economics; equivalence testing from bioequivalence regulatory work to psychology replication studies
This sourceWilkinson APA task force statistical methods effect-size reporting confidence intervals significance testing.
- Cross-domain transfer is productive: hypothesis-testing methodology from agriculture to clinical trials to A/B testing; multiplicity-adjustment methods from genomics to social-science panel studies; pre-registration practices from clinical trials to psychology to economics; equivalence testing from bioequivalence regulatory work to psychology replication studies
- Statistical Power
This sourceWilkinson APA task force statistical methods effect-size reporting confidence intervals significance testing.
- Statistical Significance (p-Value)
- Was the analysis pre-specified or selected post-hoc
This sourceWilkinson APA task force statistical methods effect-size reporting confidence intervals significance testing.
Supported in partVerified against the work's full text
The APA task force guidelines distinguish a priori hypothesis testing from exploratory work and warn of post hoc rationalization, supporting the relevance of asking whether an analysis was pre-specified.
“Reviewers should require writers to articulate their expectations well enough to reduce the likelihood of post hoc rationaliza- tions.”
- Was the analysis pre-specified or selected post-hoc
- Type I & Type II Errors
This sourceWilkinson APA task force statistical methods effect-size reporting confidence intervals significance testing.
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