Konfigurale auswertung von daten aus pratest-posttest kontrollgruppen designs

Translated title of the contribution: Configural analysis of data from pretest-posttest control group designs

Mark Kurt Stemmler, F. Masendorf

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

For treatment evaluation in multivariate pretest-posttest designs, methods of Configural Frequency Analysis (CFA) are recommended. Specifically, three CFA methods are proposed: (1) Prediction CFA, (2) Interaction CFA, and (3) Generalized Unary Hypothesis Analysis (GUHA) CFA. These methods share in common that they define treatment response-relations via so-called types, that is local or regional associations among the factors of a treatment- response cross-classification. Unit of analysis for these CFA approaches are difference scores between the first and second observation. Numerical examples use data from an experiment on the effects of training methods on calculation and reasoning in learning disabled school children.

Translated title of the contributionConfigural analysis of data from pretest-posttest control group designs
Original languageGerman
Pages (from-to)267-276
Number of pages10
JournalZeitschrift fur Klinische Psychologie, Psychiatrie und Psychotherapie
Volume46
Issue number3
StatePublished - Jan 1 1998

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Psychology(all)
  • Biological Psychiatry

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