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ITA 2.0: A Program for Classical and Inductive Item Tree Analysis

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  • Schrepp, Martin

Abstract

Item Tree Analysis (ITA) is an explorative method of data analysis which can be used to establish a hierarchical structure on a set of dichotomous items from a questionnaire or test. There are currently two different algorithms available to perform an ITA. We describe a computer program called ITA 2.0 which implements both of these algorithms. In addition we show with a concrete data set how the program can be used for the analysis of questionnaire data.

Suggested Citation

  • Schrepp, Martin, 2006. "ITA 2.0: A Program for Classical and Inductive Item Tree Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i10).
    • Handle: RePEc:jss:jstsof:v:016:i10
    DOI: http://hdl.handle.net/10.18637/jss.v016.i10
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    References listed on IDEAS

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    1. Schrepp, Martin, 1999. "On the empirical construction of implications between bi-valued test items," Mathematical Social Sciences, Elsevier, vol. 38(3), pages 361-375, November.
    2. Janssens, Rudi, 1999. "A Boolean approach to the measurement of group processes and attitudes: The concept of integration as an example," Mathematical Social Sciences, Elsevier, vol. 38(3), pages 275-293, November.
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    Cited by:

    1. Ünlü, Ali & Schrepp, Martin, 2015. "Untangling comparison bias in inductive item tree analysis based on representative random quasi-orders," Mathematical Social Sciences, Elsevier, vol. 76(C), pages 31-43.

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