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A greyscale headshot of Elliot McClenaghan
Elliot McClenaghan

Elliot McClenaghan profile page

Epidemiologist and PhD Candidate

 at London School of Hygiene and Tropical Medicine

Elliot is a statistical epidemiologist and doctoral candidate in pharmacoepidemiology in the department of Medical Statistics and the Electronic Health Records group at London School of Hygiene and Tropical Medicine (LSHTM), where his research focuses on optimal causal inference and target trial emulation methodologies for treatment effects in cystic fibrosis. Previously, he worked as a research fellow in the Department of Infectious Disease Epidemiology, working on COVID-19 transmission and seroprevalence studies. Before that he was a medical statistician at the UK Cystic Fibrosis Registry, where he designed and conducted post-authorization drug safety studies and was lead statistician of a global registry collaboration on the impact of COVID-19 in people with cystic fibrosis.


Education

Newcastle University  

Queen’s University Belfast  


Awards & Certifications

Doctoral scholarship to undertake his PhD research as part of an industry–academic partnership between LSHTM and GlaxoSmithKline (GSK)


Accreditations

BSc Biomedical Sciences recognised by Newcastle University

MPH Masters in Public Health (quantitative focus) recognised by Queen’s University Belfast


Areas of Expertise

Statistics
Epidemiology

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Published Content
Total: 16
Post-Hoc Tests in bold, dark blue writing on a white background.
Article

Post-Hoc Tests in Statistical Analysis

In this article, we review the function of post-hoc tests in statistical analysis, how to interpret them and when to use them (and not use them).
The Wilcoxon Signed-Rank Test.
Article

The Wilcoxon Signed-Rank Test

The Wilcoxon signed rank test, which is also known as the Wilcoxon signed rank sum test and the Wilcoxon matched pairs test, is a non-parametric statistical test used to compare two dependent samples (in other words, two groups consisting of data points that are matched or paired). In this article, we explain how and when this test should be used.
The Kruskal Wallis Test
Article

The Kruskal–Wallis Test

The Kruskal–Wallis test is a statistical test used to compare two or more groups for a continuous or discrete variable. This article explores what the Kruskal–Wallis test is, what it tells us and when it should be used.
Bold writing reading "The Chi-Squared Test" with a formula written faintly in the background.
Article

The Chi-Squared Test

The chi-squared test, often written as χ2 test, is a statistical hypothesis test used in the analysis of categorical variables to determine whether observed data are different from expectations. In this article, we explore the basics of this important test.
An example of a binomial distribution graph.
Article

The Binomial Test

The Binomial test, sometimes referred to as the Binomial exact test, is a test used in sampling statistics to assess whether a proportion of a binary variable is equal to some hypothesized value.
Blue text on a white background: Mann-Whitney U Test
Article

Mann-Whitney U Test: Assumptions and Example

The Mann-Whitney U Test, also known as the Wilcoxon Rank Sum Test, is a non-parametric statistical test used to compare two samples or groups. In this article, we explore the basics of the Test and work through an example.


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