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Psychometric analysis using Stata

Listed author(s):
  • Chuck Huber

    (StataCorp LP)

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    In this talk, I will provide an overview of Stata features that are typically used for the analysis of psychometric and educational testing data. Traditional multivariate tools such as canonical correlation, MANOVA, multivariate regression, Cronbach’s alpha, exploratory and confirmatory factor analysis, cluster analysis, and discriminant analysis will be discussed as well as more modern techniques based on latent trait models such as the Rasch model, multidimensional scaling, and correspondence analysis. Multilevel mixed-effects models for continuous, binary, and count outcomes will be described in the context of both ecological systems theory and longitudinal data analysis. Structural equation modeling will also be mentioned but not discussed in detail.

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    Paper provided by Stata Users Group in its series SAN12 Stata Conference with number 4.

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    Date of creation: 01 Aug 2012
    Handle: RePEc:boc:scon12:4
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