A primer for using and understanding weights with national datasets

    Authors

    D. L. Hahs-Vaughn

    Comments

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    Abbreviated Journal Title

    J. Exp. Educ.

    Keywords

    AM; design effects; design effects adjusted weights; normalized weights; raw weights; unadjusted weights; SPSS; MODELS; INFERENCE; Education & Educational Research; Psychology, Educational

    Abstract

    Using data from the National Study of Postsecondary Faculty and the Early Childhood Longitudinal Study-Kindergarten Class of 1998-99, the author provides guidelines for incorporating weights and design effects in single-level analysis using Windows-based SPSS and AM software. Examples of analyses that do and do not employ weights and design effects are also provided to illuminate the differential results of key parameter estimates and standard errors using varying degrees of using or not using the weighting and design effect continuum. The author gives recommendations on the most appropriate weighting options, with specific reference to employing a strategy to accommodate both oversampled groups and cluster sampling (i.e., using weights and design effects) that leads to the most accurate parameter estimates and the decreased potential of committing a Type I error. However, using a design effect adjusted weight in SPSS may produce underestimated standard errors when compared with accurate estimates produced by specialized software such as AM.

    Journal Title

    Journal of Experimental Education

    Volume

    73

    Issue/Number

    3

    Publication Date

    1-1-2005

    Document Type

    Article

    Language

    English

    First Page

    221

    Last Page

    248

    WOS Identifier

    WOS:000230407200003

    ISSN

    0022-0973

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