Research Report The Statistical Analysis of Single-Subject Data: A Comparative Examination Background and Purpose. The purposes of this study were to examine whether the use of three dzfferent statistical methodsfor analyzing single-subject data led to similar results and to identtfi components of graphed data that influ- ence agreement (or disagreement) among the statistical procedures. Metbocls. Forty-twographs containing single-subject data were examined. Twenty-onewere AB charts of hypothetical data. The other 21 graphs appeared in Journal of Ap- plied Behavioral Analysis, Physical Therapy, Journal of the Association for Persons With Severe Handicaps, and Journal of Behavior Therapy and Experimental Psy- chiatry. Three dzfferent statistical tests-the C statistic, the two-standard deviation band method, and the split-middle method of trend estimation-were used to analyze the 42 graphs. Results. A relatively low degree of agreement (38%) was found among the three statistical tests. The highest rate of agreementfor any two statistical procedures (71%) wasfound for the two-standard deviation band method and the C statistic. A logistic regression analysis revealed that overlap in single-subject graphed data was the best predictor of disagreement among the three statistical tests (P =.49, P <. 03). Conclusbn and Discussion. The results indicate that interpretation of data from single-subject research designs is directly influenced by the method of data analysis selected Variation exists across both visual and statistical method- of data reduction. The advantages and disadvan- tages of statistical and visual analysis are described. [Nourbakhsh MR, Ottenbacher KJ B e statistical analysis of single-subject data: a comparative examination. Pbys Ther. 1994;74: 768-7761 Key Words: N=1 research, Research design, Statistical methods, Visual analysis. Researchers in physical therapy and rehabilitation have recently advocated and used single-subject research de- signs to examine the efficacy of inter- vention-3 Single-subject designs represent alternatives to traditional group-comparison procedures used in the evaluation of clinical interven- tions. The traditional method of data analysis used in single-subject designs is visual inspection.4 Kazdin defines visual analysis as "reaching a judg- ment about the reliability or consist- ency of intervention effects by visually examining graphed data."5(~2321 Par- sonson and BaeP have described MR Nourbakhsh, PhD, PT, is currently engaged in postdoctoral study in 'kdelaide, Australia. He was a graduate student in the Therapeutic Science Program. University of Wisconsin-Madison, when this study was completed. KJ Ottenbacher, PhD. OTR, is Professor and Associate Dean, School of Health Related Professions, State University of New York at Buffalo, 435 Stockton Kimball Tower, Main Street Campus, Buffalo, NY 14214 (USA). Address all correspondence to Dr Ottenbacher. This article was suhntirred June 29, 1993, and was accepted arch 15, 1994. Mohammed Reza Nourbakhsh Kenneth J Ottenbacher several advantages of visual analysis in single-subject research. One advan- tage they identified is the insensitivity of visual analysis to weak treatment effects. Insensitivity to small or weak treatment effects is an advantage ac- cording to Parsonson and Baer be- cause it helps ensure that only large treatment effects with obvious clinical significance will be allowed into the research literature. A frequent criticism of visual analysis in single-subject designs is that there are no formal decision rules available to researchers or clinicians to inter- pret the data.7~8 Some investigators"ll 80 / 768 Physical Therapy/Volume 74, Number 8/August 1994