The relational evaluation procedure (REP) is seen by proponents of relational frame theory (RFT) as a useful means by which to assess and train relational responding.
The Implicit Relational Assessment Procedure (IRAP) has been used to assess the probability of arbitrarily applicable relational responding or as an indirect measure of implicit attitudes.
Two implicit measures, the Implicit Relational Assessment Procedure (IRAP) and the Implicit Association Test (IAT), were compared to assess attitudes towards women and science-based versus liberal arts college subjects.
Over the past 10 years, the theory has served to generate the development of a measure, known as the Implicit Relational Assessment Procedure, which was designed initially to provide a metric of the strength or persistence of relational responding.
The Implicit Relational Assessment Procedure (IRAP), a non-relative measure, was compared with the IAT which allowed us to probe this difference further among STEM and non-STEM students.
Tutors trained in applied behaviour analysis (n = 16) and mainstream school teachers (n = 16) were exposed to an Implicit Relational Assessment Procedure (IRAP) designed to assess implicit attitudes towards individuals with autism versus normally developing individuals.
The Implicit Relational Assessment Procedure (IRAP) was utilized as a means of interpreting disgust in terms of the six domains of Obsessive-Compulsive Disorder as defined by the Obsessive Compulsive Cognitions Working Group; excessive responsibility, overestimation of threat, perfectionism, intolerance for uncertainty, over importance of thoughts and need to control thoughts.
Computing grey relational coefficients using GRA procedure to obtain the required (output) data for DEA-based GRA models.
This research has been organized to proceed along the following stages (Fig. 1): 1. Computing grey relational coefficients using GRA procedure to obtain the required (output) data for DEA-based GRA models.
In the present MODRO procedure, grey relational analysis (GRA), coupled with principal component analysis (PCA), was used as a multicriteria decision making model for converting multiple conflicting objectives into one unified cost function.
