Related Experiment Video
Updated: Mar 7, 2026
05:07
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
Published on: November 7, 2025
470
Directional replicability: When can the factor of two be omitted.
Vera Djordjilović1, Tamar Sofer2,3,4, Jonathan M Dreyfuss5
1Department of Economics, Ca' Foscari University of Venice, Venice, Italy.
Statistics & Probability Letters
|March 6, 2026
Summary
This study simplifies directional replicability assessment. We found a condition where a common multiple testing correction for p-values can be omitted, streamlining the analysis of consistent research findings.
Area of Science:
- Statistics
- Meta-analysis
- Scientific reproducibility
Background:
- Directional replicability assesses if an effect appears consistently across studies.
- Current methods combine one-sided p-values and apply a multiplicative correction for multiple testing when effect direction is not pre-specified.
Purpose of the Study:
- To investigate the necessity of the multiplicative correction in directional replicability analysis.
- To identify conditions under which this correction can be omitted.
Main Methods:
- Analysis of one-sided p-values from independent studies.
- Derivation of a sufficient and necessary condition for omitting the multiplicative correction.
Main Results:
- The multiplicative correction for combining one-sided p-values is not always required.
- A specific condition has been identified that allows for the safe omission of this correction.
Conclusions:
- The proposed condition simplifies the assessment of directional replicability.
- This simplification can lead to more efficient and straightforward analysis of consistent research findings across multiple studies.
Related Concept Videos
01:17Two-Way ANOVA
3.5K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.5K
02:01Factorial Design
14.9K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
14.9K
01:18One-Way ANOVA
13.9K
One-way ANOVA analyzes more than three samples categorized by one factor. For example, it can compare the average mileage of sports bikes. Here, the data is categorized by one factor - the company. However, one-way ANOVA cannot be used to simultaneously compare the sample mean of three or more samples categorized by two factors. An example of two factors would be sports bikes from different companies driven in different terrains, such as a desert or snowy landscape. Here, two-way ANOVA is used...
13.9K
01:21Friedman Two-way Analysis of Variance by Ranks
527
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
527
01:19F Distribution
10.8K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
10.8K
01:26The Dot Product
285
Measuring how one directional quantity affects another along a specific path involves comparing their orientation and strength. When two such quantities are represented using direction and amount, a numerical result is computed to show how much one acts along the path of the other. This result comes from a rule combining both inputs' horizontal and vertical parts and adding the results.This calculation gives a single value that grows larger when both inputs point in similar directions and...
285