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...

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Bibliographic Details
Main Author: Zhao, Jian
Format: Thesis
Published: Curtin University 2018
Online Access:http://hdl.handle.net/20.500.11937/75646
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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