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Simultaneous estimation of Cronbach’s alpha coefficients
Authors:Supranee Lisawadi  S Ejaz Ahmed  Orawan Reangsephet  Muhammad Kashif Ali Shah
Institution:1. Faculty of Science and Technology, Department of Mathematics and Statistics, Thammasat University, Khlong Luang, Thailand;2. Department of Mathematics and Statistics, Brock University, St. Catharines, Ontario, Canada
Abstract:The simultaneous estimation of Cronbachs alpha coefficients from q populations under the compound symmetry assumption is considered. In a multi-sample scenario, it is suspected that all the Cronbachs alpha coefficients are identical. Consequently, the inclusion of non-sample information (NSI) on the homogeneity of Cronbachs alpha coefficients in the estimation process may improve precision. We propose improved estimators based on the linear shrinkage, preliminary test, and the Steins type shrinkage strategies, to incorporate available NSI into the estimation. Their asymptotic properties are derived and discussed using the concepts of bias and risk. Extensive Monte-Carlo simulations were conducted to investigate the performance of the estimators.
Keywords:Asymptotic properties  Cronbach’s alpha  linear shrinkage  Monte-Carlo  preliminary test  Stein-type shrinkage
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