In this chapter, we are going to present a number of techniques for detecting cohesive groups in networks such as cliques, clustering coefficient, triadic analysis, structural holes, brokerage, transitivity, hierarchical clustering, and blockmodels. All of which are based on how nodes in a network...
Testing the Work Environment Hypothesis of Bullying on a Group Level of Analysis: Psychosocial Factors as Precursors of Observed Workplace Bullying While this hypothesis is founded on an organisational and group level of analysis, it has, to our knowledge, only been reported on an individual level...
In the analysis of the video data, students' discourse functions during the game were analysed with content analytic methods for studying the nature of their interaction. An effort was made to analyse the data on both group and individual levels, and therefore the participants' prior social ties...
Testing the Work Environment Hypothesis of Bullying on a Group Level of Analysis: Psychosocial Factors as Precursors of Observed Workplace Bullying The present paper scrutinises the work environment hypothesis of bullying by examining relationships between psychosocial factors at work and bullying with......
Group-level analysis of neuropsychological quantitative evaluations Table 3 gives the quantitative means of the raw scores and z-scores for picture naming, Rey figure copy, digit span forward and backward, verbal fluencies, Trail Making Test (B-A), Stroop (conflict), and Bells’ test. Preoperati...
Medical Data Analysis Meets Artificial Intelligence (AI) and Internet of Medical Things (IoMT) This document discusses the integration of artificial intelligence (AI) and the Internet of Medical Things (IoMT) in the analysis and processing of medical... M Diwakar,P Singh,V Ravi - 《Bioengineering...
Using data from 31 software development groups, we examined the influence of the group's cohesiveness, total experience in software development and capability on the group's performance level. The influence of cohesiveness and capability was found to be strong and significant while the influence of ...
Results show significant differences in cortical excitability for 4/5 subjects using a split middle line analysis on plots of individual subject data. Group level statistics (ANOVA), however, did not detect any significant findings. The consideration of single subject statistics for TMS excitability ...
Research on in-group identification typically focuses on differences in individuals’ identification at the individual level of analysis. We take a multilevel approach, examining the emergence of group influence on identification in newly formed groups. In three studies, multilevel confirmatory factor ana...
On the basis of job analysis results, the validity of using measures of general cognitive ability, job-specific skills, and personality traits jointly at both the individual level and the group level to predict the performance of 79 four... GA Neuman,J Wright - 《Journal of Applied Psychology...