Statistical Methods for Causal Inference

Theme overview

Statistical models lie behind much of the research investigating relationships between genetics, epigenetics, lifestyle behaviours and physical and mental health outcomes.

We develop and use a range of methods, in particular focusing on instrumental variable methods, models for change over time, ways to allow for missing data, and methods for bringing together evidence from different sources. Instrumental variable methods, and particularly Mendelian randomization, are one way of avoiding bias due to confounding and measurement error. Our research focusses on the assumptions necessary for the instrumental variables method to work, and ways to use this method to answer complex questions.

Change over time is important partly because it allows us to assess causality (e.g. whether changes in smoking behaviour pre-date changes in blood pressure) and partly because it may indicate when an intervention would be useful (e.g. if weight gain during childhood has a greater effect on adult blood pressure than actual weight during adulthood, this would suggest that public health interventions for child weight would be a good idea). We are developing methods to measure change, particularly in complex situations where many aspects of a person are changing simultaneously. We are also looking at pathways over time, for example the effect of maternal smoking during pregnancy on offspring BMI in later childhood.

The amount of research available to answer any question grows every year, as current research builds on previous research, and it is vital to be able to bring together all available evidence on a particular issue. We are particularly interested in developing automated ways to search the literature (cutting down time and human error) and methods for combining results from studies which do not all measure the same things in the same ways. All these developments allow researchers to make better use of the wealth of data available to answer important questions about human health and wellbeing.

Reseach Highlights

Professor Kate Tilling


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