Biography

Michael Barrowman is currently finalising his Thesis on Multi-State Clinical Prediction Models in Renal Replacement Therapy as a PhD Candidate within the University of Manchester, whilst tutoring Maths, Stats & IT at Liverpool John Moores University.

His PhD project encompasses the development and validation of a multi-state clinical predication model, as well as the methodological advancements to produce such a model. This has led to multiple publications and the creation of software as a by-product.

He has previously worked within both the public and private sector providing data analysis to many industries, particularly education and health. During this time, he has contributed to SAPs and SOPs for a pioneering pragmatic clinical trial and improved the efficiency of examination marking by over 10%.

He is interested in Data Science, particularly using R and RStudio to their fullest potential, encouraging others to do the same and is an advocate for neat and reproducible coding practices.

He lives in Merseyside, UK and he enjoy walks down by the local canal and to the park with his two children, visiting castles & historic monuments and camping.

Interests

  • Clinical Prediction Modelling
  • Multi-State Models
  • Data Flow & Coding

Education

  • PhD in Medicine (pending), 2020

    University of Manchester

  • MSci in Mathematics, 2013

    University of Lancaster

Skills

Statistics

Communication

Data Visualisation

R

git

CI

spss

SPSS

nvivo

NVivo

SQL

Office

Excel/Sheets

G Suite

Markdown

LaTeX

HTML/CSS

 
 
 
 
 

Maths, Stats & IT Tutor

Liverpool John Moores University

Dec 2019 – Present Liverpool, UK
Assisting undergraduate and postgraduate students with Mathematics, Statistics and IT issues relating to their university course, and extending this support to teaching and research staff. Writing and providing tutorial sessions on a variety of subjects and softwares including Microsoft Word, R for Statistics, nVivo for Qualitative Research and SPSS.
 
 
 
 
 

PhD Candidate

University of Manchester

Oct 2016 – Present Manchester, UK
The goal of this PhD is to improve the academic knowledge surrounding Multi-State Clinical Prediction Models (MSCPMs). To accomplish this, I am writing articles to solve methodological issues that are yet to be addressed and applying these novel techniques (along with the present literature) to develop and validate an MSCPM to predict outcomes for Chronic Kidney Disease patients.
(2020). Toward a Framework for the Design, Implementation, and Reporting of Methodology Scoping Reviews. J CLIN EPIDEMIOL.

PDF DOI

(2019). How Unmeasured Confounding in a Competing Risks Setting Can Affect Treatment Effect Estimates in Observational Studies. BMC Med Res Methodol.

PDF DOI

(2018). Study Investigating the Generalisability of a COPD Trial Based in Primary Care (Salford Lung Study) and the Presence of a Hawthorne Effect. BMJ Open Respir Res.

PDF DOI