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Summary: Single designs

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  • Summary: Single designs

    Thanks to all of those who replied to my post with suggested journal
    articles, many happy nights were spent wading through statistical

    I have summarised the useful papers on single subject designs and
    have added a few of my thoughts on the subject.

    I believe that performing standard tests for normality, variance and
    dependence will help guide the researcher to the appropriate test.

    The debate surrounding repeated measures is somewhat of a moot
    point. If the data fits the assumptions and the most logical test is
    chosen, then the analysis will be valid. Furthermore, those with
    advanced statistical knowledge or access to a statistician could
    consider a mixed modelling approach (see the referenced website).

    Analysing multiple individuals in a single subject design, can overcome
    limitations regards generalising results.

    There is little research on regression techniques and single subject
    design, most articles deal with tests for comparison. Although, if the
    ratio of predictor variables to criterion measures is low, bootstrapping
    may be a useful tool when only within subject variability is encountered.

    Nick Flyger
    Assistant Lecturer and Masters Candidate
    Otago University School of Physical Education
    Dunedin, New Zealand
    03 4799117

    Backman, C. L., & Harris, S. R. (1999). Case studies, single-
    subject research and N of 1 randomized trials. American Journal
    of Physical Medicine and Rehabilitation, 78(2), 170-176.

    Backman, C. L., & Harris, S. R. (1999). Case studies, single-
    subject research, and N of 1 randomized trials. American journal
    of physical medicine and rehabilitation, 78(2), 170-176.

    Bates, B. T. (1996). Single-subject methodology: an alternative
    approach. Medicine & Science in Sports & Exercise., 28(5), 631-

    Bates, B. T., James, C. R., & Dufek, J. S. (2004). Single Subject
    Analysis. In N. Stergiou (Ed.), Innovative analysis of human
    movement. Champaign, Ill: Human Kinetics.

    Boneau, C. A. (1960). The effects of violations of assumptions
    underlying the t-test. Psychological Bulletin, 57, 49-64.

    Dufek, J. S., Bates, B. T., Stergiou, N., & James, C. R. (1995).
    Interactive effects between group and single-subject response
    patterns. Human Movement Science, 14(3), 301-323.

    Gagnon, F. A., Susak, L. E., Phillips, N., Wing, P. C., & Tsang, I.
    K. Y. (1993). Study designs for microgravity human physiology
    experiments. Aviation, Space, and Environmental Medicine, 64,

    Hopkins, W. G. (2004). A new view of statistics. Retrieved
    19/10/2004, 2004, from

    Horne, G. P., Yang, M. C. K., & Ware, W. B. (1982). Time series
    analysis for single-subject designs. Psychological Bulletin, 91(1),

    James, C. R., & Bates, B. T. (1997). Experimental and statistical
    design issues in human movement research. Measurement in
    Physical Education and Exercise Science, 1(1), 55-69.

    Johannessen, T., Fosstvedt, D., & Petersen, H. (1990). Statistical
    aspects of controlled single subject trials. Family Practice, 7(4),

    Kenny, D. A., & Judd, C. M. (1986). Consequences of violating
    the independence assumption in analysis of variance. Psychological
    Bulletin, 99(3), 422-431.

    Mullineaux, D. R., Bartlett, R. M., & Bennett, S. (2001). Research
    design and statistics in biomechanics and motor control. Journal of
    Sports Sciences, 19, 739-760.

    Phillips, J. P. N. (1983). Serially correlated errors in some single-
    subject designs. British Journal of Mathematical and Statistical
    Psychology, 36, 269-280.

    Reboussin, D. M., & Morgan, T. M. (1996). Statistical
    considerations in the use and analysis of single-subject designs.
    Medicine & Science in Sports & Exercise., 28(5), 639-644.

    Rochon. (1990). A statistical model for the "N-of-1" study.
    Journal of Clinical Epidemiology, 43(5), 499-508.

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