Userfriendlyscience Package of R Programming Language: A Veritable Tool
for Reliability Estimate of Non-cognitive Scale
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.