Literature DB >> 26062165

A standardized mean difference effect size for single case designs.

Larry V Hedges1, James E Pustejovsky1, William R Shadish2.   

Abstract

Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on the need for effect sizes for summarizing and meta-analyzing findings from the designs; although many effect size measures have been proposed, there is little consensus regarding their use. This article proposes a new effect size measure for single case research that is directly comparable with the standardized mean difference (Cohen's d) often used in between-subjects designs. Techniques are provided for estimating the new effect size, as well as its variance, from balanced or unbalanced treatment reversal designs. The proposed estimation methods are further evaluated using a simulation study and then demonstrated in two applications.
Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Keywords:  autocorrelation; effect size; hierarchical linear model; single case designs

Year:  2012        PMID: 26062165     DOI: 10.1002/jrsm.1052

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN: 1759-2879            Impact factor:   5.273


  28 in total

1.  Optimizing behavioral health interventions with single-case designs: from development to dissemination.

Authors:  Jesse Dallery; Bethany R Raiff
Journal:  Transl Behav Med       Date:  2014-09       Impact factor: 3.046

2.  Single-Case Design, Analysis, and Quality Assessment for Intervention Research.

Authors:  Michele A Lobo; Mariola Moeyaert; Andrea Baraldi Cunha; Iryna Babik
Journal:  J Neurol Phys Ther       Date:  2017-07       Impact factor: 3.649

3.  Treatment Burst Data Points and Single Case Design Studies: A Bayesian N-of-1 Analysis for Estimating Treatment Effect Size.

Authors:  Lucy Barnard-Brak; David M Richman; Laci Watkins
Journal:  Perspect Behav Sci       Date:  2020-05-26

4.  Time-Varying Effect Sizes for Quadratic Growth Models in Multilevel and Latent Growth Modeling.

Authors:  Alan Feingold
Journal:  Struct Equ Modeling       Date:  2018-12-20       Impact factor: 6.125

5.  Confidence interval estimation for standardized effect sizes in multilevel and latent growth modeling.

Authors:  Alan Feingold
Journal:  J Consult Clin Psychol       Date:  2014-09-01

6.  Mediation analysis with binary outcomes: Direct and indirect effects of pro-alcohol influences on alcohol use disorders.

Authors:  Alan Feingold; David P MacKinnon; Deborah M Capaldi
Journal:  Addict Behav       Date:  2018-12-15       Impact factor: 3.913

Review 7.  A systematic review of meta-analyses of psychosocial treatment for attention-deficit/hyperactivity disorder.

Authors:  Gregory A Fabiano; Nicole K Schatz; Ariel M Aloe; Anil Chacko; Andrea Chronis-Tuscano
Journal:  Clin Child Fam Psychol Rev       Date:  2015-03

8.  Mindfulness-Based Exposure Strategies as a Transdiagnostic Mechanism of Change: An Exploratory Alternating Treatment Design.

Authors:  C Alex Brake; Shannon Sauer-Zavala; James F Boswell; Matthew W Gallagher; Todd J Farchione; David H Barlow
Journal:  Behav Ther       Date:  2015-11-07

9.  Training behavioural therapists in presession pairing skills to evaluate the impact on children's life skill acquisition rates.

Authors:  Laura Gormley; Heidi Penrose; Maeve Bracken; Brittany Barron
Journal:  Int J Dev Disabil       Date:  2020-10-27

10.  Comparing Visual and Statistical Analysis in Single-Case Studies Using Published Studies.

Authors:  Magadalena Harrington; Wayne F Velicer
Journal:  Multivariate Behav Res       Date:  2015       Impact factor: 5.923

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.