Journal article
Modeling Likert Scale Outcomes With Trend-Proportional Odds With and Without Cluster Data
Methodology, Vol.12(2), pp.33-43
2016
DOI: 10.1027/1614-2241/a000106
PMCID: PMC10426790
PMID: 37583928
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 as 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.
Details
- Title: Subtitle
- Modeling Likert Scale Outcomes With Trend-Proportional Odds With and Without Cluster Data
- Creators
- Ana W Capuano - Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USAJeffrey D Dawson - Department of Biostatistics, Iowa City, IA, USAMarizen R Ramirez - Department of Occupational and Environmental Health, Iowa City, IA, USARobert S Wilson - Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USALisa L Barnes - Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USAR. William Field - Department of Occupational and Environmental Health, Iowa City, IA, USA
- Resource Type
- Journal article
- Publication Details
- Methodology, Vol.12(2), pp.33-43
- DOI
- 10.1027/1614-2241/a000106
- PMID
- 37583928
- PMCID
- PMC10426790
- NLM abbreviation
- Methodology (Gott)
- ISSN
- 1614-1881
- eISSN
- 1614-2241
- Publisher
- Hogrefe Publishing
- Alternative title
- Original Article
- Language
- English
- Date published
- 2016
- Academic Unit
- Public Health Administration; Occupational and Environmental Health; Epidemiology; Biostatistics; Public Policy Center (Archive)
- Record Identifier
- 9983997475002771
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