A Quantitative Model of Consensus Measurement

Cultural consensus theory (CCT) as a formal mathematical/statistical model can effectively handle statistical issues related to opinion aggregation, in which individual competencies are weighted to estimate the consensus answers for questions. This book work extended and customized the CCT model to a cross-cultural situation with respondents from two cultures. Respondents were experts with expertise in school psychology, and share much common knowledge on understanding respect. A proposed cross-cultural consensus model (CCCM) was analyzed with Markov Chain Monte Carlo method. This method gives marginal posterior density estimates for parameters, namely, competency and consensus in the study of understanding respect. Then by comparing competency and consensus answers between cultures, we were able to infer the cultural differences. It was documented that the CCCM model provided new perspectives on experts' opinion aggregation and cross-cultural comparison. This book is valuable reference for educators in schools, researchers who are interested in cross-cultural issues of understanding respect, and methodologists who study opinion aggregation.

Autorentext

Dr. Lun Mo, is an Educational Cognitive Psychologist and a Statistician. His special interests are in placing modern educational measurement model in a larger statistical framework, and applying cognitive learning theory to educational practices.