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    Publishing Nutrition Research: A Review of Multivariate Techniques-Part 3: Data Reduction Methods

    Access Status
    Fulltext not available
    Authors
    Gleason, P.
    Boushey, Carol
    Harris, J.
    Zoellner, J.
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Gleason, P. and Boushey, C. and Harris, J. and Zoellner, J. 2014. Publishing Nutrition Research: A Review of Multivariate Techniques-Part 3: Data Reduction Methods. Journal of the Academy of Nutrition and Dietetics. 115 (7): pp. 1072-1082.
    Source Title
    Journal of the Academy of Nutrition and Dietetics
    DOI
    10.1016/j.jand.2015.03.011
    ISSN
    2212-2672
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/51292
    Collection
    • Curtin Research Publications
    Abstract

    This is the ninth in a series of monographs on research design and analysis, and the third in a set of these monographs devoted to multivariate methods. The purpose of this article is to provide an overview of data reduction methods, including principal components analysis, factor analysis, reduced rank regression, and cluster analysis. In the field of nutrition, data reduction methods can be used for three general purposes: for descriptive analysis in which large sets of variables are efficiently summarized, to create variables to be used in subsequent analysis and hypothesis testing, and in questionnaire development. The article describes the situations in which these data reduction methods can be most useful, briefly describes how the underlying statistical analyses are performed, and summarizes how the results of these data reduction methods should be interpreted.

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