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    Statistical methods for analysing discrete and categorical data recorded in performance analysis.

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    Authors
    Nevill, Alan M.
    Atkinson, Greg
    Hughes, Mike D.
    Cooper, Stephen-Mark
    Issue Date
    2002
    
    Metadata
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    Abstract
    In this paper, we identify appropriate statistical methods for analysing categorical differences in discrete variables or 'performance indicators' resulting from performance analysis. The random mechanisms associated with discrete events do not follow a normal distribution; that is, the normal distribution is a continuous not a discrete probability distribution. We propose appropriate statistical methods based on two key discrete probability distributions, the Poisson and binomial distributions. Two approaches are proposed and compared using examples from notational analysis. The first approach is based on the classic chi-square test of significance (both the goodness-of-fit test and the test of independence). The second approach adopts a more contemporary method based on log-linear and logit models fitted using the statistical software GLIM. Provided relatively simple one-way and two-way comparisons in categorical data are required, both of these approaches result in very similar conclusions. However, as soon as more complex models or higher-order comparisons are required, the approach based on log-linear and logit models is shown to be more effective. Indeed, when investigating those factors and categorical differences associated with binomial or binary response variables, such as the proportion of winners when attempting decisive shots in squash or the proportion of goals scored from all shots in association football, logit models become the only realistic method available. By applying log-linear and logit models to discrete events resulting from notational analysis, greater insight into the underlying mechanisms associated with sport performance can be achieved.
    Citation
    Journal of Sports Sciences, 20(10): 829-44
    Publisher
    Taylor & Francis
    URI
    http://hdl.handle.net/2436/19654
    DOI
    10.1080/026404102320675666
    PubMed ID
    12363298
    Additional Links
    http://www.ingentaconnect.com/content/tandf/rjsp/2002/00000020/00000010/art00008
    Type
    Journal article
    Language
    en
    Description
    Metadata only
    ISSN
    0264-0414
    ae974a485f413a2113503eed53cd6c53
    10.1080/026404102320675666
    Scopus Count
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    Faculty of Education, Health and Wellbeing

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