A novel approach to latent class modelling: identifying the various types of body mass index individuals
© 2020 Royal Statistical Society Given the increasing prevalence of adult obesity, furthering understanding of the determinants of measures such as the body mass index (BMI) remains high on the policy agenda. We contribute to existing literature on modelling the BMI by proposing an extension to...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
WILEY
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/81791 |
| _version_ | 1848764419296722944 |
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| author | Brown, S. Greene, William Harris, Mark |
| author_facet | Brown, S. Greene, William Harris, Mark |
| author_sort | Brown, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2020 Royal Statistical Society
Given the increasing prevalence of adult obesity, furthering understanding of the determinants of measures such as the body mass index (BMI) remains high on the policy agenda. We contribute to existing literature on modelling the BMI by proposing an extension to latent class modelling, which serves to unveil a more detailed picture of the determinants of BMI. Interest here lies in latent class analysis with a regression model and predictor variables explaining class membership, a regression model and predictor variables explaining the outcome variable within BMI classes and instances where the BMI classes are naturally ordered and labelled by expected values within class. A simple and generic way of parameterizing both the class probabilities and the statistical representation of behaviours within each class is proposed, that simultaneously preserves the ranking according to class-specific expected values and yields a parsimonious representation of the class probabilities. Based on a wide range of metrics, the newly proposed approach is found to dominate the prevailing approach and, moreover, results are often quite different across the two. |
| first_indexed | 2025-11-14T11:19:03Z |
| format | Journal Article |
| id | curtin-20.500.11937-81791 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:19:03Z |
| publishDate | 2020 |
| publisher | WILEY |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-817912021-03-15T07:01:12Z A novel approach to latent class modelling: identifying the various types of body mass index individuals Brown, S. Greene, William Harris, Mark Social Sciences Science & Technology Physical Sciences Social Sciences, Mathematical Methods Statistics & Probability Mathematical Methods In Social Sciences Mathematics Body mass index Expected values Latent class models Obesity Ordered probability models HEALTH-CARE OBESITY SELECTION STANDARD AKAIKE TRENDS IMPACT ADULT TESTS ORDER © 2020 Royal Statistical Society Given the increasing prevalence of adult obesity, furthering understanding of the determinants of measures such as the body mass index (BMI) remains high on the policy agenda. We contribute to existing literature on modelling the BMI by proposing an extension to latent class modelling, which serves to unveil a more detailed picture of the determinants of BMI. Interest here lies in latent class analysis with a regression model and predictor variables explaining class membership, a regression model and predictor variables explaining the outcome variable within BMI classes and instances where the BMI classes are naturally ordered and labelled by expected values within class. A simple and generic way of parameterizing both the class probabilities and the statistical representation of behaviours within each class is proposed, that simultaneously preserves the ranking according to class-specific expected values and yields a parsimonious representation of the class probabilities. Based on a wide range of metrics, the newly proposed approach is found to dominate the prevailing approach and, moreover, results are often quite different across the two. 2020 Journal Article http://hdl.handle.net/20.500.11937/81791 10.1111/rssa.12552 English WILEY fulltext |
| spellingShingle | Social Sciences Science & Technology Physical Sciences Social Sciences, Mathematical Methods Statistics & Probability Mathematical Methods In Social Sciences Mathematics Body mass index Expected values Latent class models Obesity Ordered probability models HEALTH-CARE OBESITY SELECTION STANDARD AKAIKE TRENDS IMPACT ADULT TESTS ORDER Brown, S. Greene, William Harris, Mark A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title | A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title_full | A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title_fullStr | A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title_full_unstemmed | A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title_short | A novel approach to latent class modelling: identifying the various types of body mass index individuals |
| title_sort | novel approach to latent class modelling: identifying the various types of body mass index individuals |
| topic | Social Sciences Science & Technology Physical Sciences Social Sciences, Mathematical Methods Statistics & Probability Mathematical Methods In Social Sciences Mathematics Body mass index Expected values Latent class models Obesity Ordered probability models HEALTH-CARE OBESITY SELECTION STANDARD AKAIKE TRENDS IMPACT ADULT TESTS ORDER |
| url | http://hdl.handle.net/20.500.11937/81791 |