Abstract
Having quality instruments is essential in ensuring data integrity. Indiscriminately application and over-dependency on Cronbach alpha index for multiple measured items (ordinal scale) and usage of SPSS software, which produce spurious estimation, have been a subject of technical debates in the literature. This debate toes the path of fulfilling stringent underlying assumptions of Cronbach alpha, such as uni-dimensionality, tau-equivalent, etc. However, modern approaches like ordinal alpha, Omega coefficient, GLB, Guttman Lambda, and Revelle Beta have been suggested with precise estimates and confidence intervals via R programming language. Thus, this paper examined the performance of alternative approaches to Cronbach alpha and documented practical step by step of establishing it. Non-experimental design of scale development research was adopted, and a multi-stage sampling procedure was used to sample N = 883 subjects that participated in the study. Findings showed that the instrument is multidimensional, in which Cronbach alpha is not apt for its estimation. Also, other forms of reliability methods produced better and more precise estimates, though their performance differs among themselves. The authors concluded that estimation of Cronbach Alpha using SPSS when the instrument is ordinal is absolutely not sufficient. Therefore, it is recommended that researchers explore and shift their paradigm from traditional reliability estimates through SPSS to modern approaches using an R programming language.