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  • Directional Statistics

    I would like to respond to Dr. Ghanna's previous question regarding the best
    way to analyze circadian rhythms. I believe the best method is using
    directional (aka circular)statistics, which is an area or statistics
    concerned with data that is arranged around a circle, such as a compass or
    clock. I have been reading two such texts:

    Circular Statistics in Biology - Batschelet, 1981, Academic Press
    Directional Statistics, Mardia and Jupp, 2000, Wiley

    The former is more didactic and the second more theoretical.

    I have three further questions associated with this topic.

    1) Commonly in the biomechanics literature, statistical comparison of joint
    angles (i.e. circular data) is performed using conventional linear
    statistics such as ANOVA. Has anyone examined whether the assumption of
    linear normal distribution is appropriate in this case. I assume that a
    circular normal (i.e. Von Mises) distribution would be better, but how much
    of a difference is there? I know that ANOVA can be fairly robust with
    non-(linear)normally distributed data. One limiting factor that I can see
    with using the circular inferential stats is that the statistical models do
    not seem to be as well developed as the general linear models. Consequently,
    I have not seen in these textbooks ways to deal with repeated measures, or
    mixed factorial (crossed and nested) designs.

    2) Has anyone developed their own Matlab toolbox of directional statistics
    functions that they would be willing to share. If not, I may have just
    volunteered myself.

    3) Does anyone know of any Statistics list servers where I could cross list
    this posting, in order to get responses from the experts.


    Patrick Sparto, Ph.D., PT
    University of Pittsburgh
    Department of Physical Therapy
    and Otolaryngology
    psparto@pitt.edu

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