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    Power of Alternative Fit Indices for Multiple Group Longitudinal Tests of Measurement Invariance

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    Short_ku_0099D_13319_DATA_1.pdf (9.633Mb)
    Issue Date
    2014-05-31
    Author
    Short, Stephen David
    Publisher
    University of Kansas
    Format
    116 pages
    Type
    Dissertation
    Degree Level
    Ph.D.
    Discipline
    Psychology
    Rights
    This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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    Abstract
    Measurement invariance testing with confirmatory factor analysis has a long history in social science research, and more recently has increased use and popularity. The current paper begins by reviewing the steps for measurement invariance testing via multiple group confirmatory factor analysis, and synthesizing previous research recommendations for model testing, including the chi-square difference test, and examining change in model fit indices. Previous research on measurement invariance testing has examined change in alternative fit indices such as the CFI, TLI, RMSEA, and SRMR, but these studies had not examined power to detect invariance when more than two groups exist and multiple time points are present. The present study implemented a Monte Carlo simulation to examine the power of change in alternative fit indices to detect two types of measurement invariance, weak and strong, across a variety of manipulated study conditions including sample size, sample size ratio, lack of invariance, location of noninvariance, magnitude of noninvariance, and type of mixed study design.
    URI
    http://hdl.handle.net/1808/14570
    Collections
    • Dissertations [4474]
    • Psychology Dissertations and Theses [459]

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    785-864-8983

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    Lawrence, KS 66045
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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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