Comparing "visual" effect size indices for single-case designs

Methodology

Volumn 6, Issue 2, 2010, Pages 49-58

  Manolov, Rumen ^a   Solanas, Antonio ^a   Leiva, David ^a  

^a UNIVERSITY OF BARCELONA   (Spain)

Author keywords

AB designs; Autocorrelation; Effect size; Single case

Indexed keywords

EID: 77950335061     PISSN: 16141881     EISSN: 16142241     Source Type: Journal    
DOI: 10.1027/1614-2241/a000006     Document Type: Article

References (50)

1. Allison, D. B., Faith, M. S., & Franklin, R. (1995). Antecedent exercise in the treatment of disruptive behavior: A review and meta-analysis. Clinical Psychology: Science and Practice, 2, 279-303.
2. Allison, D. B., & Gorman, B. S. (1993). Calculating effect sizes for meta-analysis: The case of the single case. Behaviour Research and Therapy, 31, 621-631.
3. Bellini, S., Peters, J. K., Benner, L., & Hopf, A. (2007). A meta-analysis of school-based social skills interventions for children with autism spectrum disorders. Remedial and Special Education, 28, 153-162.
4. Borrego, J. Jr., Anhalt, K., Terao, S. Y., Vargas, E. C., & Urquiza, A. J. (2006). Parent-child interaction therapy with a Spanish-speaking family. Cognitive and Behavioral Practice, 13, 121-133.
5. Busk, P. L., & Marascuilo, L. A. (1988). Autocorrelation in single-subject research: A counterargument to the myth of no autocorrelation. Behavioral Assessment, 10, 229-242.
6. Busse, R. T., Kratochwill, T. R., & Elliott, S. N. (1995). Meta-analysis for single-case consultation outcomes: Applications to research and practice. Journal of School Psychology, 33, 269-285.
7. Campbell, J. M. (2004). Statistical comparison of four effect sizes for single-subject designs. Behavior Modification, 28, 234-246.
8. Center, B. A., Skiba, R. J., & Casey, A. (1985-1986). A methodology for the quantitative synthesis of intra-subject
9. design research. The Journal of Special Education, 19, 387-400.
10. Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.
11. Cohen, J (1994). The earth is round (p <.05). American Psychologist, 49, 997-1003.
12. Crosbie, J. (1987). The inability of the binomial test to control Type I error with single-subject data. Behavioral Assessment, 9, 141-150.
13. Faith, M. S., Allison, D. B., & Gorman, D. B. (1997). Meta-analysis of single-case research. In R. D. Franklin, D. B. Allison, & B. S. Gorman (Eds.), Design and analysis of single-case research (pp. 245-277). Mahwah, NJ: Erlbaum.
14. Friedman, H. (1982). Simplified determinations of statistical power, magnitude of effect and research sample sizes. Educational and Psychological Measurement, 42, 521-526.
15. Gorman, B. S., & Allison, D. B. (1997). Statistical alternatives for single-case designs. In R. D. Franklin, D. B. Allison, & B. S. Gorman (Eds.), Design and analysis of single-case research (pp. 159-214). Mahwah, NJ: Erlbaum.
16. Gorsuch, R. L. (1983). Three methods for analyzing limited time-series (N of 1) data. Behavioral Assessment, 5, 141-154.
17. Greenwood, K. M., & Matyas, T. A. (1990). Problems with application of interrupted time series analysis for brief single-subject data. Behavioral Assessment, 12, 355-370.
18. Huitema, B. E. (1985). Autocorrelation in behavior analysis: A myth. Behavioral Assessment, 7, 107-118.
19. Huitema, B. E., & McKean, J. W. (1991). Autocorrelation estimation and inference with small samples. Psychological Bulletin, 110, 291-304.
20. Huitema, B. E., & McKean, J. W. (2000). Design specification issues in time-series intervention models. Educational and Psychological Measurement, 60, 38-58.
21. Huitema, B. E., & McKean, J. W. (2007). An improved portmanteau test for autocorrelated errors in interrupted time-series regression models. Behavior Research Methods, 39, 343-349.
22. Huitema, B. E., McKean, J. W., & McKnight, S. (1999). Autocorrelation effects on least-squares intervention analysis of short time series. Educational and Psychological Measurement, 59, p767-786.
23. Jones, R. R., Weinrott, M. R., & Vaught, R. S. (1978). Effects of serial dependence on the agreement between visual and statistical inference. Journal of Applied Behavior Analysis, 11, 277-283.
24. Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56, 746-759.
25. Kromrey, J. D., & 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.
26. Ma, H. H. (2006). An alternative method for quantitative synthesis of single-subject research: Percentage of data points exceeding the median. Behavior Modification, 30, 598-617.
27. Manolov, R., & Solanas, A. (2008). Comparing N = 1 effect size indices in presence of autocorrelation. Behavior Modification, 32, 860-875.
28. Mathur, S. R., Kavale, K. A., Quinn, M. M., Forness, S. R., & Rutherford, R. B. Jr. (1998). Social skills interventions with students with emotional and behavioral problems: A quantitative synthesis of single-subject research. Behavioral Disorders, 23, 193-201.
29. Matyas, T. A., & Greenwood, K. M. (1990). Visual analysis for single-case time series: Effects of variability, serial dependence, and magnitude of intervention effects. Journal of Applied Behavior Analysis, 23, 341-351.
30. Matyas, T. A., & Greenwood, K. M. (1991). Problems in the estimation of autocorrelation in brief time series and some implications for behavioral data. Behavioral Assessment, 13, 137-157.
31. Matyas, T. A., & Greenwood, K. M. (1997). Serial dependency in single-case time series. In R. D. Franklin, D. B. Allison, & B. S. Gorman (Eds.), Design and analysis of single-case research (pp. 215-243). Mahwah, NJ: Erlbaum.
32. Parker, R. I. (2006). Increased reliability for single-case research results: Is bootstrap the answer? Behavior Therapy, 37, 326-338.
33. Parker, R. I., & Brossart, D. F. (2003). Evaluating single-case research data: A comparison of seven statistical methods. Behavior Therapy, 34, 189-211.
34. Parker, R. I., Cryer, J., & Byrns, G. (2006). Controlling baseline trend in single-case research. School Psychology Quarterly, 21, 418-443.
35. Parker, R. I., & Hagan-Burke, S. (2007a). Median-based overlap analysis for single case data: A second study. Behavior Modification, 31, 919-936.
36. Parker, R. I., & Hagan-Burke, S. (2007b). Useful effect size interpretations for single case research. Behavior Therapy, 38, 95-105.
37. Parker, R. I., Hagan-Burke, S., & Vannest, K. (2007). Percentage of all non-overlapping data: An alternative to PND. Journal of Special Education, 40, 194-204.
38. Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276-1284.
39. Scruggs, T. E., & Mastropieri, M. A. (1994). The utility of the PND statistic: A reply to Allison and Gorman. Behaviour Research and Therapy, 32, 879-883.
40. Scruggs, T. E., & Mastropieri, M. A. (1998). Summarizing single-subject research: Issues and applications. Behavior Modification, 22, 221-242.
41. Scruggs, T. E., Mastropieri, M. A., & Casto, G. (1987). The quantitative synthesis of single-subject research: Methodology and validation. Remedial and Special Education, 8, 24-33.
42. Scruggs, T. E., Mastropieri, M. A., Forness, S. R., & Kavale, K. A. (1988). Early language intervention: A quantitative synthesis of single-subject research. The Journal of Special Education, 20, 259-283.
43. Sharpley, C. F., & Alavosius, M. P. (1988). Autocorrelation in behavior data: An alternative perspective. Behavior Assessment, 10, 243-251.
44. Sierra, V., Solanas, A., & Quera, V. (2005). Randomization tests for systematic single-case designs are not always appropriate. The Journal of Experimental Education, 73, 140-160.
45. Skiba, R. J., Casey, A., & Center, B. A. (1986). Nonaversive procedures in the classroom behavior problems. The Journal of Special Education, 19, 459-481.
46. Suen, H. K. (1987). On the epistemology of autocorrelation in applied behavior analysis. Behavioral Assessment, 9, 113-124.
47. Suen, H. K., & Ary, D. (1987). Autocorrelation in behavior analysis: Myth or reality? Behavioral Assessment, 9, 130-150.
48. Toothaker, L. E., Banz, M., Noble, C., Camp, J., & Davis, D. (1983). N = 1 designs: The failure of ANOVA-based tests. Journal of Educational Statistics, 4, 289-309.
49. White, D. M., Rusch, F. R., Kazdin, A. E., & Hartmann, D. P. (1989). Applications of meta-analysis in individual subject research. Behavioral Assessment, 11, 281-296.
50. Wilkinson, L., & The Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 694-704.