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    Home/Original/inverse
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    Inverse View

    It is not the case that Ordinal scales like Likert-type instruments, as Jamieson (2004) argues, preserve rank information sufficient for linguistic gradient distinctions without normalization artifacts.

    ?Set your confidence on the premises below to see your aggregate.

    Reasons For

    1 perspective
    Reason for
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    • 1.Respondents often treat Likert items as quasi-interval; analyzing them as purely ordinal discards information about psychological distance patterns.
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    • 2.Linguistic gradients are subjective and culturally variable; ordinal rank alone cannot validate that 'agree' represents equivalent psychological meaning across respondents.
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    • 3.Many parametric tests show robustness to ordinal violations in practice; rejecting them entirely may sacrifice statistical power without proportional validity gains.
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    Reasons Against

    1 perspective
    Reason against
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    • 1.Likert scales capture meaningful order relations (strongly disagree < disagree < neutral < agree < strongly agree) without assuming equal intervals.
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    • 2.Linguistic labels inherently convey gradations; forcing ordinal data into parametric assumptions introduces spurious precision artifacts.
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    • 3.Rank-based analyses (Spearman correlation, Mann-Whitney U) on ordinal data are statistically valid and avoid normalization distortions entirely.
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