Literature DB >> 27831527

An Improved Rank Correlation Effect Size Statistic for Single-Case Designs: Baseline Corrected Tau.

Kevin R Tarlow1.   

Abstract

Measuring treatment effects when an individual's pretreatment performance is improving poses a challenge for single-case experimental designs. It may be difficult to determine whether improvement is due to the treatment or due to the preexisting baseline trend. Tau- U is a popular single-case effect size statistic that purports to control for baseline trend. However, despite its strengths, Tau- U has substantial limitations: Its values are inflated and not bound between -1 and +1, it cannot be visually graphed, and its relatively weak method of trend control leads to unacceptable levels of Type I error wherein ineffective treatments appear effective. An improved effect size statistic based on rank correlation and robust regression, Baseline Corrected Tau, is proposed and field-tested with both published and simulated single-case time series. A web-based calculator for Baseline Corrected Tau is also introduced for use by single-case investigators.

Keywords:  clinical outcomes assessment; effect size; measurement; single case; treatment effectiveness

Mesh:

Year:  2016        PMID: 27831527     DOI: 10.1177/0145445516676750

Source DB:  PubMed          Journal:  Behav Modif        ISSN: 0145-4455


  9 in total

1.  Extending the Parent-Delivered Early Start Denver Model to Young Children with Fragile X Syndrome.

Authors:  Laurie A Vismara; Carolyn E B McCormick; Rebecca Shields; David Hessl
Journal:  J Autism Dev Disord       Date:  2019-03

2.  A Priori Justification for Effect Measures in Single-Case Experimental Designs.

Authors:  Rumen Manolov; Mariola Moeyaert; Joelle E Fingerhut
Journal:  Perspect Behav Sci       Date:  2021-03-25

3.  Introduction to the Special Section: Translating Advanced Quantitative Techniques for Single-Case Experimental Design Data.

Authors:  Lucy Barnard-Brak; David M Richman; Laci Watkins
Journal:  Perspect Behav Sci       Date:  2022-02-08

4.  The Power to Explain Variability in Intervention Effectiveness in Single-Case Research Using Hierarchical Linear Modeling.

Authors:  Mariola Moeyaert; Panpan Yang; Xinyun Xu
Journal:  Perspect Behav Sci       Date:  2021-09-01

5.  Single case designs for early phase behavioral translational research in health psychology.

Authors:  Leonard H Epstein; Warren K Bickel; Susan M Czajkowski; Rocco A Paluch; Mariola Moeyaert; Karina W Davidson
Journal:  Health Psychol       Date:  2021-08-09       Impact factor: 4.267

6.  Examination of the Effectiveness and Acceptability of a Play-Based Sibling Intervention for Children with Autism: A Single-Case Research Design.

Authors:  Lindsay B Glugatch; Wendy Machalicek
Journal:  Educ Treat Children       Date:  2021-08-16

7.  Deep-Breathing Biofeedback Trainability in a Virtual-Reality Action Game: A Single-Case Design Study With Police Trainers.

Authors:  Abele Michela; Jacobien M van Peer; Jan C Brammer; Anique Nies; Marieke M J W van Rooij; Robert Oostenveld; Wendy Dorrestijn; Annika S Smit; Karin Roelofs; Floris Klumpers; Isabela Granic
Journal:  Front Psychol       Date:  2022-02-10

8.  Hybrid Telepractice Delivery of Enhanced Milieu Teaching: Effects on Caregiver Implementation and Child Communication.

Authors:  Emily D Quinn; Ann P Kaiser; Jennifer Ledford
Journal:  J Speech Lang Hear Res       Date:  2021-07-21       Impact factor: 2.674

9.  Causal Mediation Analysis in Single Case Experimental Designs: Introduction to the Special Issue.

Authors:  Milica Miočević; Mariola Moeyaert; Axel Mayer; Amanda K Montoya
Journal:  Eval Health Prof       Date:  2022-02-03       Impact factor: 2.651

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.