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ERIC Number: EJ1099054
Record Type: Journal
Publication Date: 2016-Jun
Pages: 25
Abstractor: As Provided
ISSN: ISSN-0013-1644
Robust Coefficients Alpha and Omega and Confidence Intervals with Outlying Observations and Missing Data: Methods and Software
Zhang, Zhiyong; Yuan, Ke-Hai
Educational and Psychological Measurement, v76 n3 p387-411 Jun 2016
Cronbach's coefficient alpha is a widely used reliability measure in social, behavioral, and education sciences. It is reported in nearly every study that involves measuring a construct through multiple items. With non-tau-equivalent items, McDonald's omega has been used as a popular alternative to alpha in the literature. Traditional estimation methods for alpha and omega often implicitly assume that data are complete and normally distributed. This study proposes robust procedures to estimate both alpha and omega as well as corresponding standard errors and confidence intervals from samples that may contain potential outlying observations and missing values. The influence of outlying observations and missing data on the estimates of alpha and omega is investigated through two simulation studies. Results show that the newly developed robust method yields substantially improved alpha and omega estimates as well as better coverage rates of confidence intervals than the conventional nonrobust method. An R package coefficient alpha is developed and demonstrated to obtain robust estimates of alpha and omega.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: Department of Education (ED)
Authoring Institution: N/A
Grant or Contract Numbers: R305D140037