Calculating and graphing within-subject confidence intervals for ANOVA

Baguley, T. ORCID: 0000-0002-0477-2492, 2012. Calculating and graphing within-subject confidence intervals for ANOVA. Behavior Research Methods, 44 (1), pp. 158-175. ISSN 1554-351X

[img]
Preview
Text
205093_8162 Baguley preprint.pdf

Download (1MB) | Preview

Abstract

The psychological and statistical literature contains several proposals for calculating and plotting confidence intervals for within-subject (repeated measures) ANOVA designs. A key distinction is between intervals supporting inference about patterns of means (and differences between pairs of means in particular) and those supporting individual means. It is argued that the former are best accomplished by adapting intervals proposed by Cousineau (2005) and Morey (2008) so that non-overlapping confidence intervals for individual means correspond to a confidence for their difference that does not include zero. The latter can be accomplished by fitting a multilevel model. In situations where both types of inference are of interest, the use of a two-tiered CI is recommended. Free open-source, cross-platform software for these interval estimates and plots (and for some common alternatives) is provided in the form of R functions for one-way within-subject and twoway mixed ANOVA designs. These functions provide an easy to use solution to the difficult problem of calculating and displaying within-subject confidence intervals.

Item Type: Journal article
Description: The original publication is available at www.springerlink.com
Publication Title: Behavior Research Methods
Creators: Baguley, T.
Publisher: Springer
Date: 2012
Volume: 44
Number: 1
ISSN: 1554-351X
Identifiers:
NumberType
10.3758/s13428-011-0123-7DOI
Divisions: Schools > School of Social Sciences
Depositing User: EPrints Services
Date Added: 09 Oct 2015 10:11
Last Modified: 09 Jun 2017 13:21
URI: http://irep.ntu.ac.uk/id/eprint/9061

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year