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The Likert Scale Analysis Using Parametric Based Structural Equation Modeling (Sem)

Authors: Asyraf Afthanorhan;

The Likert Scale Analysis Using Parametric Based Structural Equation Modeling (Sem)

Abstract

The Likert scale is commonly used in survey research using primary and secondary data to measure the respondent attitude by asking insofar to which they agree or disagree with a particular questions. In generals, Likert scale would be preferred in the questionnaire development stage to ascertain the researchers conducting their research needed. However, the researchers nowadays are abuse to understand the nature of measurement scale in data analysis and thus causes the finding obtained are meaningless. This article is aimed to compare the performance of two categories of measurement scales which are 5 point and 10 points of Likert scales using the same sample size and research subject that would pave the way to understand the real different between both of these ranges using Structural Equation Modeling (SEM). Moreover, this study also interested to clarify briefly between two types of measurement scale namely ordinal and interval data. The findings reveal that 10 points of Likert scale is more efficient than 5 points of Likert scale in operating of measurement model.

Keywords

Likert Scale, Structural Equation Modeling (SEM), Ordinal, Interval, Parametric 1

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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