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Effect sizes and confidence intervals

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posted on 12.03.2021, 06:12 by Geoffrey Cumming, Fiona Fidler
This is an Accepted Manuscript of a book chapter published by Routledge in "The Reviewer's Guide to Quantitative Methods in the Social Sciences", 2nd edition, on 19 November 2018, available online: https://www.routledge.com/The-Reviewers-Guide-to-Quantitative-Methods-in-the-Social-Sciences/Hancock-Stapleton-Mueller/p/book/9781138800137

Chapter abstract: An effect size is simply an amount of something of interest. It can be as simple as a mean, a percentage increase, or a correlation; or it may be a regression weight, a standardized measure of a difference, or the percentage of variance accounted for. Most research questions in the social sciences are best answered by finding estimated effect sizes, meaning point estimates of the true effect sizes in the population. Grissom and Kim (2012) provided a comprehensive discussion of effect sizes, and ways to calculate effect size estimates. Our discussion mainly focuses on experimental designs, but much of the discussion is relevant also to other types of research.

History

Publication Date

19/11/2018

Book Title

The reviewer’s guide to quantitative methods in the social sciences

Editors

Hancock GR Stapleton LM Mueller RO

Publisher

Routledge

Place of publication

London

Edition

2

Pagination

14p. (p. 72-85)

ISBN-13

9781138800137

Rights Statement

The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.

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