Dr Peter Rankin

Research Fellow

Queensland Brain Institute


Peter is a Research Fellow in Applied Statistics at the Science of Learning Research Centre, Queensland Brain Institute. His research focuses on understanding the mechanisms that enable or limit children’s life chances. He plays a crucial role in designing well-structured studies, analysing data, and interpreting results to provide valid and reliable conclusions on how to improve children's opportunities and outcomes.

As an applied statistician, Peter collaborates with an inter-disciplinary team to integrate statistical analyses with qualitative research and contextual knowledge. He brings expertise in identifying and analysing key factors and variables that influence children's life chances. Further, he develops research methodologies, including sampling strategies, data collection methods, and statistical analyses of small- and large-scale data, to understand the complex interplay of factors that contribute to children's opportunities and outcomes. He distills the link between experiences and children’s life chances using an array of statistical methods, including longitudinal and multilevel modelling, measurement and psychometrics, causal inference, data science, structural equation modelling, and data visualization. Additionally, he has expertise in uncovering the mediating and moderating factors that influence the relationship between early life experiences and later life chances. By leveraging expertise in statistical analysis and research methodology, Peter’s work provides evidence-based insights into the mechanisms that shape children's life chances. This evidence informs research, policy, and interventions aimed at improving children's opportunities and outcomes.

Research Interests

  • Enabling children’s life chances
    Parents, caregivers, and educators are the closest influence on children in the crucial early years of development. What can parents, caregivers, and educators do to enable children to succeed?
  • Gene environment interaction
    Identical twins share striking similarities in personality, yet profound or traumatic experiences can change a person’s personality entirely. How do genes and the environment interact to determine outcomes? What implications does this have for enabling children’s life chances?
  • Individual differences
    Parents and educators observe that what works for one child does not work for another. How do individual differences shape children’s learning, development, and life chances?
  • Statistical inference
    Smoking in pregnancy was incorrectly inferred to reduce mortality rates for low-birth weight infants, because low-birth weight in infants of non-smoking mothers was from more severe causes. How can we use design and methodology to make better statistical inferences?
  • Measurement
    Grace Hopper observed, “one accurate measurement is worth a thousand expert opinions”. How can we use statistical methods to improve and validate measurement of early experiences and child outcomes?

Research Impacts

Interdisciplinary applied and basic research

The major theme of Peter's work is using a broad research background and high-level statistical skills to answer applied and basic research questions. Previously, he focused on environmental conservation and marine science. In the present, he has transitioned into developmental psychology, early education and care, and child development. The future focus for Peter's work is examining inter-individual differences in intra-individual process of development. That is, establishing patterns of change in child developmental outcomes and examining how characteristics of the individuals influence individual variation in response to unique and shared developmental experience. This will help establish, from a developmental lens, what works, and what works for whom.

Methodological rigour

The second theme of Peter's work is methodological rigour. His work has outlined the limits of knowledge, and critically reflected on limitations within research areas and scoped improvement. This includes work on better estimation strategies for analytical models, improving and understanding psychometric measurement, and critically evaluating bodies of evidence to understand gaps in knowledge and providing suggestions to improve research design and analytical practice. His focus on methodology remains a focal point moving forwards.

Statistical leadership

The third theme is statistical leadership. A major component of Peter's work is providing leadership to multiple research teams on appropriate statistical methodology. Peter’s statistical leadership has informed several key discoveries, including how activity and time of day influences assessments of childcare quality and the link between emotional quality of early education and cognitive development.


  • Doctor of Philosophy, The University of Queensland
  • Bachelor (Honours) of Science (Advanced), The University of Queensland


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