A method for measuring consensus within groups: An index of disagreement via conditional probability
| Autor: | Marjorie Darrah, James J. Nolan, Mushtaq Abdal Rahem, Lei Wang, Yoshio Akiyama |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Information Systems and Management
Index (economics) 05 social sciences 050301 education Scale (descriptive set theory) 02 engineering and technology Function (mathematics) Variance (accounting) Conditional probability distribution Measure (mathematics) Computer Science Applications Theoretical Computer Science Likert scale Artificial Intelligence Control and Systems Engineering Statistics 0202 electrical engineering electronic engineering information engineering Econometrics Range (statistics) 020201 artificial intelligence & image processing 0503 education Software Mathematics |
| Zdroj: | Information Sciences. 345:116-128 |
| ISSN: | 0020-0255 |
| DOI: | 10.1016/j.ins.2016.01.052 |
| Popis: | This paper presents a new index of disagreement (or measure of consensus) for comparison of data collected using Likert items. This new index, which assesses the level of disagreement among group members, exploits the conditional distribution of the variance for a given mean. The variance is often used as a measure of disagreement, with high variance seen as a high disagreement in a group. However, since the range of the variance is a function of the mean, this implies that for a mean close to the end points of the scale, the range of the variance is relatively small and for a mean at the center of the scale the range of the variance is larger. The index of disagreement introduced in this paper takes into account both the mean and the variance and provides a way to compare two groups that is more meaningful than just considering the variance or other measures of disagreement or consensus that only depend on the variance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect