Statistical Modelling of Breastfeeding Data
This thesis addresses some key methodological problems in statistical modelling of breastfeeding data. Meta-analysis techniques were used to analyse aggregated breastfeeding data. Generalised linear mixed model and an extended Cox model were used with time-varying exposures to analyse longitudinal a...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
Curtin University
2018
|
| Online Access: | http://hdl.handle.net/20.500.11937/75646 |
| _version_ | 1848763524953669632 |
|---|---|
| author | Zhao, Jian |
| author_facet | Zhao, Jian |
| author_sort | Zhao, Jian |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This thesis addresses some key methodological problems in statistical modelling of breastfeeding data. Meta-analysis techniques were used to analyse aggregated breastfeeding data. Generalised linear mixed model and an extended Cox model were used with time-varying exposures to analyse longitudinal and time-to-event breastfeeding data, respectively. Shared frailty models were applied to correlated breastfeeding duration data controlling for heterogeneity. A novel two-part mixed-effects model was proposed for modelling clustered time-to-event breastfeeding data with clumping at zero. |
| first_indexed | 2025-11-14T11:04:50Z |
| format | Thesis |
| id | curtin-20.500.11937-75646 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:04:50Z |
| publishDate | 2018 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-756462019-06-07T02:58:25Z Statistical Modelling of Breastfeeding Data Zhao, Jian This thesis addresses some key methodological problems in statistical modelling of breastfeeding data. Meta-analysis techniques were used to analyse aggregated breastfeeding data. Generalised linear mixed model and an extended Cox model were used with time-varying exposures to analyse longitudinal and time-to-event breastfeeding data, respectively. Shared frailty models were applied to correlated breastfeeding duration data controlling for heterogeneity. A novel two-part mixed-effects model was proposed for modelling clustered time-to-event breastfeeding data with clumping at zero. 2018 Thesis http://hdl.handle.net/20.500.11937/75646 Curtin University fulltext |
| spellingShingle | Zhao, Jian Statistical Modelling of Breastfeeding Data |
| title | Statistical Modelling of Breastfeeding Data |
| title_full | Statistical Modelling of Breastfeeding Data |
| title_fullStr | Statistical Modelling of Breastfeeding Data |
| title_full_unstemmed | Statistical Modelling of Breastfeeding Data |
| title_short | Statistical Modelling of Breastfeeding Data |
| title_sort | statistical modelling of breastfeeding data |
| url | http://hdl.handle.net/20.500.11937/75646 |