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CFA and Its Derivatives

  • Mark Stemmler
Chapter
  • 900 Downloads
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

This chapter introduces several derivatives of CFA that can be used for different purposes. First, there is Prediction CFA (P-CFA). This version of CFA is comparable to multiple regression. One variable is defines as the dependent variable or criterion, which is usually measured with a certain time lag with regard to the other independent variables or predictors. Second, there is Interaction Structure Analysis (ISA). ISA uses an extended definition of interactions, which cannot be analyzed with log-linear modeling. Instead of searching for singular types or antitypes, one can search for biprediction types by looking for regional instead of local contingency. Finally, two-sample CFA is introduced as a very useful statistical tool similar to t-tests for independent samples. This derivative of CFA searches for types which differentiate the two samples under investigation, so called discrimination types.

Keywords

Behavior Problem Order Interaction Kindergarten Teacher Classroom Behavior Extended Definition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mark Stemmler
    • 1
  1. 1.Institute of PsychologyFriedrich-Alexander University of Erlangen-Nuremberg (FAU)ErlangenGermany

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