B3306 - Modelling techniques for accelerated longitudinal studies - 07/05/2019

B number: 
B3306
Principal applicant name: 
Gwen Fernandes | Population Health Sciences (United Kingdom)
Co-applicants: 
Dr Jon Heron, Dr Fanny Kilpi , Professor Kate Tilling, Professor Debbie Lawlor
Title of project: 
Modelling techniques for accelerated longitudinal studies
Proposal summary: 

I met with Dr Fanny Kilpi following her presentation on some of the maternal data with cognitive outcomes from ALSPAC. Dr Jon Heron noticed the similarity in terms of structure of her dataset and wondered whether we could use these data to trial a new method of handling data produced from another study that we are involved with called cVEDA.

The purpose of this exercise is to trial a method/s of dealing with data including missing data that is completely new to me and the cVEDA (Indian cohort) team. It is purely for learning purposes and to consider any assumptions and adjustments we may make to our models when our final dataset is officially released at the end of 2020 i.e. a practice dataset.

Despite a publishable manuscript not being our primary goal it would be useful to have some input into how best to use these data, and which exclusions to make (e.g. HRT etc). Also, we may discover the analytical approach to be useful to you and then a publication may result if all collaborators consider this a worthwhile exercise and outcome.

Impact of research: 
The most tangible impact of this work will be to help guide our analysis plans for the final cVEDA dataset. As this is exploratory, we do not envisage publishing any of our findings but we will share these with Dr Kilpi and her team at every stage to ensure that we have their statistical input but also, if it might help inform their results, the collaboration could be mutually helpful.
Date proposal received: 
Wednesday, 1 May, 2019
Date proposal approved: 
Tuesday, 7 May, 2019
Keywords: 
Epidemiology, Methodological development without focus on specific outcome however we will be using either grip strength (biomechanical outcome) or cognitive functioning (mental health outcome) , Computer simulations/modelling/algorithms, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc.