Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014
We develop an age-period-cohort model for repeated cross-section data with individual covariates, which identifies the non-linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a p...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
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Wiley
2021
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| _version_ | 1797053879110598656 |
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| author | Fannon, Z Monden, C Nielsen, B |
| author_facet | Fannon, Z Monden, C Nielsen, B |
| author_sort | Fannon, Z |
| collection | OXFORD |
| description | We develop an age-period-cohort model for repeated cross-section data with individual covariates, which identifies the non-linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a parametrization with freely varying parameters that separates the identified non-linear effects and the unidentifiable linear effects. We develop a test of the parametrization against a more general ‘time-saturated’ model. The method is applied to analyse the obesity epidemic in England using survey data. The main non-linear effects we find in English obesity data are age-related among women and cohort-related among men. |
| first_indexed | 2024-03-06T18:49:43Z |
| format | Journal article |
| id | oxford-uuid:0fcf75c5-ff98-488c-b182-8219c3a3b2c6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:49:43Z |
| publishDate | 2021 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:0fcf75c5-ff98-488c-b182-8219c3a3b2c62022-03-26T09:53:08ZModelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0fcf75c5-ff98-488c-b182-8219c3a3b2c6EnglishSymplectic ElementsWiley2021Fannon, ZMonden, CNielsen, BWe develop an age-period-cohort model for repeated cross-section data with individual covariates, which identifies the non-linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a parametrization with freely varying parameters that separates the identified non-linear effects and the unidentifiable linear effects. We develop a test of the parametrization against a more general ‘time-saturated’ model. The method is applied to analyse the obesity epidemic in England using survey data. The main non-linear effects we find in English obesity data are age-related among women and cohort-related among men. |
| spellingShingle | Fannon, Z Monden, C Nielsen, B Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title | Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title_full | Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title_fullStr | Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title_full_unstemmed | Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title_short | Modelling non-linear age-period-cohort effects and covariates, with an application to English obesity 2001–2014 |
| title_sort | modelling non linear age period cohort effects and covariates with an application to english obesity 2001 2014 |
| work_keys_str_mv | AT fannonz modellingnonlinearageperiodcohorteffectsandcovariateswithanapplicationtoenglishobesity20012014 AT mondenc modellingnonlinearageperiodcohorteffectsandcovariateswithanapplicationtoenglishobesity20012014 AT nielsenb modellingnonlinearageperiodcohorteffectsandcovariateswithanapplicationtoenglishobesity20012014 |