Project Activities
The research entailed several studies designed to address major complications encountered when synthesizing results from SSED research. The first set of studies was designed for synthesizing results from SSED studies with outcomes in the same metric. The initial study focused on the basic three-level model for the meta-analysis of SSED studies with the same outcome. A series of additional studies targeted complications encountered in the synthesis of SSED studies' results, including: autocorrelation; count data outcomes; designs with multiple outcomes and/or settings; models with nonlinear growth trajectories; and the use of bootstrapping estimation techniques. The second set of studies assessed synthesis of standardized raw data and effect sizes necessary for meta-analyzing results from SSED studies employing outcomes on different metrics. For each multilevel model extension being investigated, real SSED data was analyzed and a simulation study conducted testing estimation of the relevant model under realistic conditions.
Four types of dissemination products were used to share the results with the wider educational community. These included research presentations and publications, workshops, a freely available SSED modeling manual (providing programs in SAS, R, and MLwiN to estimate the multilevel model and its extensions), and information on the principal investigators' web sites.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
Book chapter
Rindskopf, D., and Ferron, J. (2014). Using Multilevel Models to Analyze Single-Case Design Data. In T.R. Kratochwill, and J.R. Levin (Eds.), Single-Case Intervention Research: Methodological and Data-Analysis Advances. American Psychological Association.
Journal article, monograph, or newsletter
Baek, E., Beretvas, S. N., Van den Noortgate, W., & Ferron, J. M. (2020). Brief research report: Bayesian versus REML estimations with noninformative priors in multilevel single-case data. The Journal of Experimental Education, 88(4), 698-710.
Baek, E.K., Moeyaert, M., Petit-Bois, M., Beretvas, S.N., Van Den Noortgate, W., and Ferron, J.M. (2014). The Use of Multilevel Analysis for Integrating Single-Case Experimental Design Results Within a Study and Across Studies. Neuropsychological Rehabilitation, 24(3-4), 590-606.
Baek, E.K., Petit-Bois, M., Van Den Noortgate, W., Beretvas, S.N., and Ferron, J.M. (2016). Using Visual Analysis to Evaluate and Refine Multilevel Models of Single-Case Studies. The Journal of Special Education, 50(1), 18-26.
Declercq, L., Jamshidi, L., Fernandez Castilla, B., Moeyaert, M., Beretvas, S. N., Ferron, J. M., & Van den Noortgate, W. (2022). Multilevel meta-analysis of individual participant data of single-case experimental designs: One-stage versus two-stage methods. Multivariate Behavioral Research, 57(2-3), 298-317.
Ferron, J. M., Moeyaert, M., Van Den Noortgate, W., and Beretvas, S. N. (2014). Estimating Causal Effects From Multiple-Baseline Studies: Implications for Design and Analysis. Psychological Methods, 19(4), 493.
Hembry, I., Bunuan, R., Beretvas, S. N., Ferron, J. M., and Van Den Noortgate, W. (2015). Estimation of a Nonlinear Intervention Phase Trajectory for Multiple-Baseline Design Data. The Journal of Experimental Education, 83(4), 514-546.
Moeyaert, M., Rindskopf, D., Onghena, P., and Van Den Noortgate, W. (2017). Multilevel Modeling of Single-Case Data: A Comparison of Maximum Likelihood and Bayesian Estimation. Psychological Methods, 22(4): 760-778.
Moeyaert, M., Ugille, M., Ferron, J.M., Onghena, P., Heyvaert, M., Beretvas, S.N., and Van Den Noortgate, W. (2015). Estimating Intervention Effects Across Different Types of Single-Subject Experimental Designs: Empirical Illustration. School Psychology Quarterly, 30(1), 50.
Moeyaert, M., Ugille, M., Ferron, J.M., Beretvas, S.N., and Van Den Noortgate, W. (2016). The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study. The Journal of Experimental Education, 84(3), 473-509.
Moeyaert, M., Ugille, M., Ferron, J. M., Beretvas, S. N., and Van Den Noortgate, W. (2014). The Influence of the Design Matrix on Treatment Effect Estimates in the Quantitative Analyses of Single-Subject Experimental Design Research. Behavior Modification, 38(5), 665-704.
Moeyaert, M., Ugille, M., Ferron, J., Beretvas, S., and Van Den Noortgate, W. (2013). Modeling External Events in the Three-Level Analysis of Multiple-Baseline Across-Participants Designs: A Simulation Study. Behavior Research Methods, 45(2): 547-559.
Moeyaert, M., Ugille, M., Ferron, J., Beretvas, S., and Van Den Noortgate, W. (2014). Three-Level Analysis of Single-Case Experimental Data: Empirical Validation. Journal of Experimental Education, 82(1): 1-21.
Moeyaert, M., Ugille, M., Ferron, J.M., Beretvas, S.N., and Van Den Noortgate, W. (2013). The Three-Level Synthesis of Standardized Single-Subject Experimental Data: A Monte Carlo Simulation Study. Multivariate Behavioral Research, 48(5), 719-748.
Petit-Bois, M., Baek, E.K., Van Den Noortgate, W., Beretvas, S.N., and Ferron, J.M. (2016). The Consequences of Modeling Autocorrelation When Synthesizing Single-Case Studies Using a Three-Level Model. Behavior Research Methods, 48(2), 803-812.
Rindskopf, D., & Ferron, J. (2014). Using Multilevel Models To Analyze Single-Case Design Data. Single-Case Intervention Research: Methodological And Statistical Advances, 221-246.
Ugille, M., Moeyaert, M., Beretvas, N., Ferron, J., and Van den Noorgate, W. (2012). Multilevel Meta-Analysis of Single-Subject Experimental Designs: A Simulation Study. Behavior Research Methods, 44(4): 1244-1254.
Ugille, M., Moeyaert, M., Beretvas, N., Ferron, J., and Van den Noorgate, W. (2014). Bias Corrections for Standardized Effect Size Estimates Used With Single-Subject Experimental Designs. Journal of Experimental Education, 82(3): 358-374.
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