Prof Michele Haynes - Institute for Learning Sciences & Teacher Education (Faculty of Education and Arts)

Fully accredited supervisor - Can supervise as principal supervisor

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Michele Haynes is professor of data analytics for education and social research in the Learning Sciences Institute Australia. She is an experienced statistician with expertise in estimation of complex models for social applications using longitudinal data from multiple sources including national panel surveys and government administrative data. Michele's research interests include improvement of statistical techniques for investigating trajectories in education and social outcomes for young individuals, identifying the drivers of change and how these vary for disadvantaged groups. Michele has influenced methodological development through various roles including Chair of the Social Statistics Section of the Statistical Society of Australia, Associate Editor for the Journal of the Royal Statistical Society Series A (Statistics in Society), Statistical Advisor for the International Journal of Disability, Development and Education, and through the delivery of professional training in longitudinal data analysis to government personnel. Michele has attracted considerable research funding through grants including an ARC Discovery project that has developed an online survey tool for gathering data from Indigenous people to better understand their experiences and perceptions of architectural health settings, and a recently awarded ARC Linkage grant for a project to study community-based STEM professional learning for teachers of middle years. She has also led numerous projects in partnership with government agencies. Most recently, Michele has been successful with an Education Horizon grant in 2019-2020 with colleagues Joy Cumming, Melanie Spallek and Yoon-Suk Hwang, for a project on "Factors that impact on long-term achievement and retention for students with ASD in Queensland government schools: Evidence from administrative data."

Contact

Phone :0738616168 (Brisbane)
Email :Michele.Haynes@acu.edu.au
URIs : Staff Directory ProfilePersonal Website

Research Interests

Statistics ; Education trajectories ; life course research ; Data analytics for education ; Data for policy ; Big data analysis ; Models for longitudinal data ; Transition to work ;

Methods Expertise

Statistical modelling ; Longitudinal data analysis ; Data analytics ; Survey Research ; Bayesian estimation ;

Research Projects

Selected Publications

2019

Aboriginal and Torres Strait Islander preferences for healthcare settings: effective use of design images in survey research., in Australian Health Review (in press)

Misspecification of multimodal random effect distributions in logistic mixed models for panel survey data., in Journal of the Royal Statistical Society - Series A (Statistics in Society), 182(1) 305-321.

2017

Parents' interest in their child's education and children's outcomes in adolescence and adulthood: Does gender matter?, in International Journal of Educational Research, 85: 131-147.

2016

The family life course and health: partnership and fertility histories and physical health trajectories in later life, in Demography, 53(3):777-804

Engaging parents in schools and building parent-school partnerships: The role of school and parent organisation leadership, in International Journal of Educational Research, 79: 128-141.

2015

Time on housework and selection into and out of relationships in Australia: a multiprocess multilevel approach, in Longitudinal and Life Course Studies, 6(3):245-263.

2014

Holistic housing pathways for Australian families through the childbearing years, in Longitudinal and Life Course Studies, 5:205-226

2012

Individual and environmental characteristics associated with cognitive development in Down syndrome: a longitudinal study, in Journal of Applied Research in Intellectual Disabilities, 25:396-413

2006

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants, in Journal of the Royal Statistical Society - Series A (Statistics in Society), 169(1): 97-114

Other information

I have supervised 19 PhD candidates to completion with 13 completing since 2012.