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Open AccessJournal ArticleDOI

Equivalence Testing for Psychological Research: A Tutorial

Daniel Lakens, +2 more
- Vol. 1, Iss: 2, pp 259-269
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TLDR
Two One-Sided Tests (TOSTs) as discussed by the authors were used to test both for the presence of an effect and for the absence of a effect in a test set.
Abstract
Psychologists must be able to test both for the presence of an effect and for the absence of an effect. In addition to testing against zero, researchers can use the two one-sided tests (TOST) proce...

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Journal ArticleDOI

Evaluating Effect Size in Psychological Research: Sense and Nonsense:

TL;DR: The most common mistakes being to describe effect sizes in ways that are uninformative (e.g., using arbitrary standards) or misleading as mentioned in this paper, i.e., squa...
Journal ArticleDOI

Indices of Effect Existence and Significance in the Bayesian Framework.

TL;DR: This study describes and compares several Bayesian indices, provide intuitive visual representation of their “behavior” in relationship with common sources of variance such as sample size, magnitude of effects and also frequentist significance, and contributes to the development of an intuitive understanding of the values that researchers report, critical for the standardization of scientific reporting.
Journal ArticleDOI

How Many Participants Do We Have to Include in Properly Powered Experiments? A Tutorial of Power Analysis with Reference Tables.

TL;DR: In this article, the authors describe reference numbers needed for the designs most often used by psychologists, including single-variable between-groups and repeated-measures designs with two and three levels, two-factor designs involving two repeated measures and one repeated measure, and split-plot design.
Posted ContentDOI

Sample Size Justification

Daniel Lakens
TL;DR: In this paper, six approaches are discussed to justify the sample size in a quantitative empirical study: collecting data from (an) almost) the entire population, choosing a sample size based on resource constraints, performing an a-priori power analysis, planning for a desired accuracy, using heuristics, or explicitly acknowledging the absence of a justification.
Journal ArticleDOI

Teenagers, screens and social media: a narrative review of reviews and key studies

TL;DR: The research field needs to refocus on improving transparency, interpreting effect sizes and changing measurement, and show a greater appreciation for the individual differences that will inherently shape each adolescent’s reaction to digital technologies.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Book

Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Book

ggplot2: Elegant Graphics for Data Analysis

TL;DR: This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics.
Journal ArticleDOI

Interpretation of changes in health-related quality of life the remarkable universality of half a standard deviation

TL;DR: In most circumstances, the threshold of discrimination for changes in health-related quality of life for chronic diseases appears to be approximately half a SD, which research in psychology has shown is approximately 1 part in 7.
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Estimating the reproducibility of psychological science

Alexander A. Aarts, +290 more
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