Literature DB >> 30972557

MultiSCED: A tool for (meta-)analyzing single-case experimental data with multilevel modeling.

Lies Declercq1, Wilfried Cools2, S Natasha Beretvas3, Mariola Moeyaert4, John M Ferron5, Wim Van den Noortgate2.   

Abstract

The MultiSCED web application has been developed to assist applied researchers in behavioral sciences to apply multilevel modeling to quantitatively summarize single-case experimental design (SCED) studies through a user-friendly point-and-click interface embedded within R. In this paper, we offer a brief introduction to the application, explaining how to define and estimate the relevant multilevel models and how to interpret the results numerically and graphically. The use of the application is illustrated through a re-analysis of an existing meta-analytic dataset. By guiding applied researchers through MultiSCED, we aim to make use of the multilevel modeling technique for combining SCED data across cases and across studies more comprehensible and accessible.

Entities:  

Keywords:  Multilevel analysis; R; SCED; Shiny; Single-case experimental design

Mesh:

Year:  2020        PMID: 30972557     DOI: 10.3758/s13428-019-01216-2

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  17 in total

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Authors:  Rumen Manolov; Lucien Rochat
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3.  The Three-Level Synthesis of Standardized Single-Subject Experimental Data: A Monte Carlo Simulation Study.

Authors:  Mariola Moeyaert; Maaike Ugille; John M Ferron; S Natasha Beretvas; Wim Van den Noortgate
Journal:  Multivariate Behav Res       Date:  2013-09       Impact factor: 5.923

4.  Quantifying differences between conditions in single-case designs: Possible analysis and meta-analysis.

Authors:  Rumen Manolov; Antonio Solanas
Journal:  Dev Neurorehabil       Date:  2016-01-25       Impact factor: 2.308

5.  A comparison of mean phase difference and generalized least squares for analyzing single-case data.

Authors:  Rumen Manolov; Antonio Solanas
Journal:  J Sch Psychol       Date:  2013-01-18

6.  Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

Authors:  Eun Kyeng Baek; John M Ferron
Journal:  Behav Res Methods       Date:  2013-03

7.  How Can Single-Case Data Be Analyzed? Software Resources, Tutorial, and Reflections on Analysis.

Authors:  Rumen Manolov; Mariola Moeyaert
Journal:  Behav Modif       Date:  2016-09-21

8.  Evaluating significance in linear mixed-effects models in R.

Authors:  Steven G Luke
Journal:  Behav Res Methods       Date:  2017-08

9.  Estimating individual treatment effects from multiple-baseline data: a Monte Carlo study of multilevel-modeling approaches.

Authors:  John M Ferron; Jennie L Farmer; Corina M Owens
Journal:  Behav Res Methods       Date:  2010-11

10.  Making treatment effect inferences from multiple-baseline data: the utility of multilevel modeling approaches.

Authors:  John M Ferron; Bethany A Bell; Melinda R Hess; Gianna Rendina-Gobioff; Susan T Hibbard
Journal:  Behav Res Methods       Date:  2009-05
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  7 in total

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4.  Individual Patterns and Temporal Trajectories of Changes in Fear and Pain during Exposure In Vivo: A Multiple Single-Case Experimental Design in Patients with Chronic Pain.

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5.  Development, evaluation and implementation of a digital behavioural health treatment for chronic pain: study protocol of the multiphase DAHLIA project.

Authors:  Sara Laureen Bartels; Sophie I Johnsson; Katja Boersma; Ida Flink; Lance M McCracken; Suzanne Petersson; Hannah L Christie; Inna Feldman; Laura E Simons; Patrick Onghena; Johan W S Vlaeyen; Rikard K Wicksell
Journal:  BMJ Open       Date:  2022-04-15       Impact factor: 3.006

6.  A proposal for the assessment of replication of effects in single-case experimental designs.

Authors:  Rumen Manolov; René Tanious; Belén Fernández-Castilla
Journal:  J Appl Behav Anal       Date:  2022-04-25

7.  Graded exposure treatment for adolescents with chronic pain (GET Living): Protocol for a randomized controlled trial enhanced with single case experimental design.

Authors:  Laura E Simons; Lauren E Harrison; Shannon F O'Brien; Marissa S Heirich; Nele Loecher; Derek B Boothroyd; Johan W S Vlaeyen; Rikard K Wicksell; Deborah Schofield; Korey K Hood; Michael Orendurff; Salinda Chan; Sam Lyons
Journal:  Contemp Clin Trials Commun       Date:  2019-09-10
  7 in total

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