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An Algorithm for Converting Ordinal Scale Measurement Data to Interval/Ratio Scale

机译:一种将有序尺度测量数据转换为间隔/比率尺度的算法

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摘要

The extensive use of survey instruments in the social sciences has long created debate and concern about validity of outcomes, especially among instruments that gather ordinal-level data. Ordinal-level survey measurement of concepts that could be measured at the interval or ratio level produce errors because respondents are forced to truncate or round off their responses to fit a given ordinal scale. This article presents a Markov chain Monte Carlo modeling technique that converts ordinal measurements to interval/ ratio. Simulated data demonstrate the robustness of this technique, and implications of this technique are discussed.
机译:长期以来,社会科学中调查手段的广泛使用引起了人们对结果有效性的争论和关注,特别是在收集序数数据的手段中。可能在区间或比率级别上测量的概念的按序级别的调查度量会产生错误,因为被调查者被迫截断或四舍五入以适应给定序数规模。本文介绍了一种马尔可夫链蒙特卡洛建模技术,该技术可将有序测量值转换为间隔/比率。仿真数据证明了该技术的鲁棒性,并讨论了该技术的含义。

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