Three-level analysis of single-case experimental data: Empirical validation

Journal of Experimental Education

Volumn 82, Issue 1, 2014, Pages 1-21

  Moeyaert, Mariola ^a   Ugille, Maaike ^a   Ferron, John M ^b   Beretvas, S Natasha ^c   Den Noortgate, Wim Van ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b UNIVERSITY OF SOUTH FLORIDA   (United States)

^c UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Monte Carlo simulation study; single case study; three level analysis

Indexed keywords

EID: 84887815617     PISSN: 00220973     EISSN: 19400683     Source Type: Journal    
DOI: 10.1080/00220973.2012.745470     Document Type: Article

References (46)

1. Alen, E., Grietens, H., and, Van den Noorgate, W. 2009. Meta-analysis of single-case studies: An illustration for the treatment of anxiety disorders Leuven, Belgium. Unpublished master's thesis, Katholieke Universiteit Leuven
2. Barlow, D. H., and, Hersen, M. 1984. Single-case experimental designs: Strategies for studying behavior change (2nd ed.), New York, NY: Pergamon Press.
3. Beretvas, S. N., and, Chung, H. 2008. A review of single-subject experimental design meta-analyses: Methodological issues and practice. Evidence-Based Communication and Assessment and Intervention, 2: 129-141.
4. Center, B. A., Skiba, R. J., and, Casey, A. A methodology for the quantitative synthesis of intra-subject design research. Journal of Special Education, 19, 1985-1986, 387-400.
5. Cohen, J. 1988. Statistical power analysis for the behavioural sciences, Mahwah, NJ: Erlbaum.
6. Denis, J., Van den Noortgate, W., and, Maes, B. 2011. Self-injurious behavior in people with profound intellectual disabilities: A meta-analysis of single-case studies. Research in Developmental Disabilities, 32: 911-923.
7. Fai, A. H.-T., and, Cornelius, P. L. 1996. Approximate F-tests of multiple degree of freedom hypotheses in generalized least squares analyses of unbalanced split-plot experiments. Journal of Statistical Computation & Simulation, 54: 363-378.
8. Farmer, J., Owens, C. M., Ferron, J. M., and, Allsopp, D. 2010, May. A review of social science single-case meta-analyses. Paper presented at the annual meeting of the American Education Research Association, Denver, CO.
9. Ferron, J. M., and, Onghena, P. 1996. The power of randomization tests for single-case phase designs. Journal of Experimental Education, 64: 231-239.
10. Ferron, J. M., and, Sentovich, C. 2002. Statistical power of randomization tests used with multiple-baseline designs. Journal of Experimental Education, 70: 165-178.
11. Ferron, J. M., Bell, B. A., Hess, M. F., Rendina-Gobioff, G., and, Hibbard, S. T. 2009. Making treatment effect inferences from multiple-baseline data: The utility of multilevel modeling approaches. Behavior Research Methods, 41: 372-384.
12. Ferron, J. M., Farmer, J. L., and, Owens, C. M. 2010. Estimating individual treatment effects from multiple-baseline data: A Monte Carlo study of multilvel-modeling approaches. Behavior Research Methods, 42: 930-943.
13. Fouladi, R. T., and, Shieh, Y. 2004. A comparison of two general approaches to mixed model longitudinal analyses under small sample size conditions. Communications in Statistics: Simulation and Computation, 33: 807-824.
14. Giesbrecht, F. G., and, Burns, J. C. 1985. Two-stage analysis based on a mixed model: Large sample asymptotic theory and small-sample simulation results. Biometrics, 41: 477-486.
15. Gomez, E., Schaalje, G. B., and, Fellingham, G. W. 2005. Performance of the Kenward-Roger method when the covariance structure is selected using AIC and BIC. Communication in Statistics: Simulation and Computation, 34: 377-392. (Pubitemid 40836071)
16. Huitema, B. E., and, McKean, J. W. 1994. Two biased-reduced autocorrelation estimators: rF1 and rF2. Perceptual and Motor Skills, 78: 323-330.
17. Kackar, R. N., and, Harville, D. A. 1984. Approximations for standard errors of estimators of fixed and random effects in mixed linear models. Journal of the American Statistical Association, 79: 853-862.
18. Kazdin, A. E., and, Kopel, S. A. 1975. On resolving ambiguities of the multiple-baseline design: Problems and recommendations. Behavior Therapy, 6: 601-608.
19. Kennedy, M. M. 1979. Generalizing from single case studies. Evaluation Quarterly, 3: 661-678.
20. Kokina, A., and, Kern, L. 2010. Social story interventions for students with autism spectrum disorders: a meta-analysis. Journal of Autism and Developmental Disorders, 40: 812-826.
21. Kowalchuk, R. K., Keselman, H. J., Algina, J., and, Wolfinger, R. D. 2004. The analysis of repeated measurements with mixed-model adjusted F tests. Educational and Psychological Measurement, 64: 224-242. (Pubitemid 38430612)
22. Kratochwill, T., Alden, K., Demuth, D., Dawson, D., Paicucci, C., Arntson, P., and,. Levin, J. 1974. A futher consideration in the application of an analysis of variance model for the intrasubject replication design. Journal of Applied Behavior Analysis, 7: 629-633.
23. Kromrey, J. D., and, Foster-Johnson, L. 1996. Determining the efficacy of intervention: The use of effect sizes for data analysis in single-subject research. Journal of Experimental Education, 65: 73-93.
24. Kwok, O., West, S. G., and, Green, S. B. 2007. The impact of misspecifying the within-subject covariance structure in multiwave longitudinal multilevel models: A Monte Carlo study. Multivariate Behavioral Research, 42: 557-592.
25. Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., and, Schabenberger, O. 2006. SAS© system for mixed models (2nd ed.), Cary, NC: SAS Institute Inc.
26. McKnight, S. D., McKean, J. W., and, Huitema, B. E. 2000. A double bootstrap method to analyze linear models with autoregressive error terms. Psychological Methods, 5: 87-101.
27. McLean, R. A., and, Sanders, W. L. 1988. Approximating degrees of freedom for standard errors in mixed linear models. Proceedings of the statistical computing section,. (pp. 50-59). New Orleans, LA: American Statistical Association.
28. Moeyaert, M., Ugille, M., Ferron, J. M., Beretvas, S. N, and, Van den Noortgate, W. in press. The three-level synthesis of standardized single-subject experimental data: A Monte Carlo simulation study, Multivariate Behavioral Research.
29. Morgan, D. L., and, Morgan, R. K. 2001. Single-participant research design: Bringing science to managed care. American Psychologist, 56: 119-127. (Pubitemid 33624314)
30. Murphy, D. L., and, Pituch, K. A. 2009. The performance of multilevel growth curve models under an autoregressive moving average process. The Journal of Experimental Education, 77: 255-282.
31. Nugent, W. R. 1996. Integrating single-case and group-comparison designs for evaluation research. Journal of Applied Behavioral Science, 32: 209-226. (Pubitemid 126071353)
32. Onghena, P., and, Edgington, E. S. 2005. Customization of pain treatments: Single-case design and analysis. Clinical Journal of Pain, 21: 56-68. (Pubitemid 40019113)
33. Owens, C. M., and, Ferron, J. M. 2012. " Synthesizing single-case studies: A Monte Carlo examination of a three-level meta-analytic model ". In Behavior Research Methods Vol. 44, 795-805. doi: 10.3758/S13428-011-0180-y
34. Raudenbush, S. W., and, Bryk, A. S. 2002. Hierarchical linear models: Applications and data analysis methods (2nd ed., Vol. 1, London, UK: Sage.
35. Satterthwaite, F. E. 1941. Synthesis of variance. Psychometrika, 6: 309-316. doi: 10.1007/BF02288586
36. Shadish, W. R., Cook, T. D., and, Campbell, D. T. 2002. Experimental and quasi-experimental designs for generalized causal inference, Boston, MA: Houghton-Mifflin.
37. Shadish, W. R., and, Rindskopf, D. M. 2007. " Methods for evidence-based practice: Quantitative synthesis of single-subject designs ". In Informing federal policies on evaluation method: Building the evidence base for method choice in government sponsored evaluation, Edited by: Julnes, G. and Rog, D. J. 95-109. San Francisco, CA: Jossey-Bass.
38. Shadish, W. R., and, Sullivan, K. J. 2011. Characteristics of single-case designs used to assess intervention effects in 2008. Behavior Research Methods, 43: 971-980.
39. Shogren, K. A., Fagella-Luby, M. N., Bae, J. S., and, Wehmeyer, M. L. 2004. The effect of choice-making as an intervention for problem behavior. Journal of Positive Behavior Interventions, 6: 228-237. (Pubitemid 39374522)
40. Snijders, T. A. B., and, Bosker, R. J. 1993. Standard errors and sample sizes for two-level research. Journal of Educational and Behavioral Statistics, 18: 237-259.
41. Swanson, H. L., and, Sachse-Lee, C. 2000. A meta-analysis of single-subject-design intervention research for students with LD. Journal of learning disabilities, 33: 114-136.
42. Tate, R. L., McDonald, S., Perdices, M., Togher, L., Schultz, R., and, Savage, S. 2008. Rating the methodological quality of single-subject designs and n-of-1 trials: Introducing the Single-Case Experimental Design (SCED) Scale. Neuropsychological Rehabilitation, 18: 385-401. (Pubitemid 351896818)
43. Van den Noortgate, W, and, Onghena, P. 2003a. Combining single-case experimental data using hierarchical linear models. School Psychology Quarterly, 18: 325-346. (Pubitemid 37342081)
44. Van den Noortgate, W, and, Onghena, P. 2003b. Hierarchical linear models for the quantitative integration of effect sizes in single-case research. Behavior Research Methods, Instruments, & Computers, 35: 1-10. (Pubitemid 37545044)
45. Van den Noortgate, W, and, Onghena, P. 2008. A multilevel meta-analysis of single-subject experimental design studies. Evidence-Based Communication Assessment and Intervention, 2: 142-151.
46. Wang, S., Cui, Y., and, Parrila, R. 2011. Examining the effectiveness of peer-mediated and video-modeling social skills interventions for children with autism spectrum disorders: a meta-analysis in single-case research using HLM. Research in Autism Spectrum Disorders, 5: 562-569.