Modeling Likert scale outcomes with trend-proportional odds with and without cluster data.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Ana W Capuano, Jeffrey D Dawson, Marizen R Ramirez, Robert S Wilson, Lisa L Barnes, R William Fields
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引用次数: 7

Abstract

Likert scales are commonly used in epidemiological studies employing surveys. In this tutorial we demonstrate how the proportional odds model and the trend odds model can be applied simultaneously to data measured in Likert scales, allowing for random cluster effects. We use two datasets as examples: an epidemiological study on aging and cognition among community-dwelling Black persons, and a clustered large survey data from 28,882 students in 81 middle schools. The first example models the Likert outcome from the question: "People act as if they think you are dishonest". The trend-proportional odds model indicates that Black men have higher odds than Black women of reporting being perceived dishonest. The second example models the Likert outcome from the question: "How often have you been beaten up at school?". The trend-proportional odds model indicates that children with disability have a higher odds of severe violence than other children. For both examples, the cumulative odds ratio increases by more than 60% at the higher Likert levels.

Abstract Image

建模李克特量表结果与趋势比例的优势,有无集群数据。
李克特量表通常用于采用调查的流行病学研究。在本教程中,我们将演示如何将比例赔率模型和趋势赔率模型同时应用于李克特尺度中测量的数据,从而允许随机聚类效应。本文以两组数据为例:一组是社区黑人老龄化与认知的流行病学研究,另一组是来自81所中学28,882名学生的聚类大型调查数据。第一个例子模拟了这个问题的李克特结果:“人们表现得好像他们认为你不诚实”。趋势比例赔率模型表明,黑人男性比黑人女性报告被认为不诚实的几率更高。第二个例子模拟了李克特结果的问题:“你在学校多久被打一次?”趋势比例几率模型表明,残疾儿童遭受严重暴力的几率高于其他儿童。对于这两个例子,在较高的李克特水平下,累积优势比增加了60%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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