Publications

  1. Risk for Congenital Rubella. Clinical Infectious Diseases 8(5), 830-830.
  2. Examples of Uncorrelated Dependent Variables. Teaching Statistics 10(1), 29-29.
  3. & On a class of three dimensional radially symmetric positive definite functions. Metrika 36(1), 327-330.
  4. & On the Assessment of Equipment Reliability: Trading Data Collection Costs for Precision. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 205(2), 105-109.
  5. & Maximum likelihood estimation and prediction mean square error in the spatial linear model. Journal of Applied Statistics 19(1), 49-59.

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Teaching

  • PMIM01 Scientific Computing and Healthcare

    The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate. Module leader is Dan Thayer

  • PMIM02 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. Module leader is Dr Joanne Demmler

  • PMIM102 Scientific Computing and Health Care

    The module aims to raise the awareness of students about scientific computing in the field of health data science. It focuses on basic software development workflows, tools, and skills that health data scientists most often employ. Students will also learn about the professional context within which health data scientists operate. This is a core / compulsory module and worth 20 Masters level credits. Module leader is Dan Thayer

  • PMIM202 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. This is a core / compulsory module and worth 20 Masters level credits. Module leader is Dr Joanne Demmler

Supervision

  • Paramedic Supplied "Take Home" Naloxone: A Randomised Feasibility Study (current)

    Student name:
    PhD
    Other supervisor: Prof Alan Watkins
    Other supervisor: Prof Helen Snooks
  • Estimating the social care needs of looked after children (LAC) and those at risk of being in care: Utilising anonymised linked data (Escalate) (current)

    Student name:
    PhD
    Other supervisor: Prof Alan Watkins
    Other supervisor: Prof Hayley Hutchings
  • The development and validation of a patient-reported outcome assess listening effort in adult cochlear implant patients (current)

    Student name:
    PhD
    Other supervisor: Prof Frances Rapport
    Other supervisor: Prof Alan Watkins
    Other supervisor: Prof Hayley Hutchings
  • Examining the causal mechanisms of improvements to health and wellbeing associated with green-blue spaces: a mixed methods approach (current)

    Student name:
    PhD
    Other supervisor: Prof Alan Watkins
    Other supervisor: Dr Alison Porter
  • Epidemiology of Opioid Overdose and Psychological Predictors of Engagement with Harm Reduction Strategies and Abstinence in Opioid Users (current)

    Student name:
    PhD
    Other supervisor: Miss Ceri Bradshaw
    Other supervisor: Prof Alan Watkins
  • Colorectal cancer - effects of surgery and chemotherapy on quality of life (awarded 2018)

    Student name:
    MSc
    Other supervisor: Prof Ian Russell
    Other supervisor: Prof Hayley Hutchings
    Other supervisor: Prof Alan Watkins
  • 'On the Statistical Analysis of Reliability and Warranty Claims Data' (awarded 2018)

    Student name:
    PhD
    Other supervisor: Dr Alan Mayer
    Other supervisor: Prof Alan Watkins