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    Exploratory factor analysis in behavior genetics research: Factor recovery with small sample sizes

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    preacher_maccallum_2002.pdf (79.5Kb)
    Issue Date
    2002
    Author
    Preacher, Kristopher J.
    MacCallum, Robert C.
    Type
    Article
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    Abstract
    Results of a Monte Carlo study of exploratory factor analysis demonstrate that in studies characterized by low sample sizes the population factor structure can be adequately recovered if communalities are high, model error is low, and few factors are retained. These are conditions likely to be encountered in behavior genetics research involving mean scores obtained from sets of inbred strains. Such studies are often characterized by a large number of measured variables relative to the number of strains used, highly reliable data, and high levels of communality. This combination of characteristics has special consequences for conducting factor analysis and interpreting results. Given that limitations on sample size are often unavoidable, it is recommended that researchers limit the number of expected factors as much as possible.
    URI
    http://hdl.handle.net/1808/1494
    Collections
    • Psychology Scholarly Works [298]
    Citation
    Behavior Genetics, 32, 153-161.

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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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