Reliability Estimates for Multilevel Designs in Group Research

Items that capture group members’ outcomes from small group processes (e.g., satisfaction, cohesion) are often nonindependent. A primary assumption of most measurement models is that the data are independent; applying such models to group-outcome data measured at the individual level of analysis is...

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Bibliographic Details
Published in:Small group research 2012-08, Vol.43 (4), p.443-467
Main Authors: Bonito, Joseph A., Ruppel, Erin K., Keyton, Joann
Format: Article
Language:English
Subjects:
Biological and medical sciences
Fundamental and applied biological sciences. Psychology
Group dynamics
Methodology. Experimentation
Monte Carlo simulation
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics. Statistics. Methodology
Reliability
Research methodology
Satisfaction
Social Cohesion
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Summary:Items that capture group members’ outcomes from small group processes (e.g., satisfaction, cohesion) are often nonindependent. A primary assumption of most measurement models is that the data are independent; applying such models to group-outcome data measured at the individual level of analysis is thus likely to produce inaccurate estimates. A solution to the measurement of nonindependent data involves the use of multilevel modeling to estimate variances at item, individual, and group levels of analysis. Examples from several different statistics programs are provided, and Monte Carlo simulations are used to evaluate the effects of group size and number of items on reliability estimates.
ISSN:1046-4964
1552-8278
DOI:10.1177/1046496412437614