A Comparison of Techniques for Handling and Assessing the Influence of Mobility on Student Achievement

Lindsey J Wolff Smith, S. Natasha Beretvas

    Research output: Research - peer-reviewArticle

    Abstract

    Conventional multilevel modeling works well with purely hierarchical data; however, pure hierarchies rarely exist in real datasets. Applied researchers employ ad hoc procedures to create purely hierarchical data. For example, applied educational researchers either delete mobile participants' data from the analysis or identify the student only with the last school attended while including an explanatory variable indicating whether a student is mobile. This simulation study compared the parameter and standard error estimates of these two ad hoc procedures for handling and assessing the influence of mobility on outcomes with results based on use of the multiple membership random effects model. Substantial bias was found for some parameters when multiple membership data structures were ignored.

    LanguageEnglish (US)
    Pages3-23
    Number of pages21
    JournalJournal of Experimental Education
    Volume85
    Issue number1
    DOIs
    StatePublished - Jan 2 2017

    Fingerprint

    Research Personnel
    Students
    Handling (Psychology)
    student
    Datasets
    simulation
    trend
    school

    Keywords

    • Achievement
    • at-risk students
    • evaluation
    • HLM
    • multiple membership
    • simulation studies

    ASJC Scopus subject areas

    • Education
    • Developmental and Educational Psychology

    Cite this

    A Comparison of Techniques for Handling and Assessing the Influence of Mobility on Student Achievement. / Smith, Lindsey J Wolff; Beretvas, S. Natasha.

    In: Journal of Experimental Education, Vol. 85, No. 1, 02.01.2017, p. 3-23.

    Research output: Research - peer-reviewArticle

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