Dr Graciela Muniz Terrera
Senior Lecturer in Biostatistics and Epidemiology

- Centre for Clinical Brain Sciences
- Centre for Dementia Prevention
Contact details
- Email: g.muniz@ed.ac.uk
Background
Dr. Muniz Terrera is a Senior Lecturer in Biostatistics and Epidemiology at the Centre for Dementia Prevention where she works in collaboration with colleagues in the EPAD (European Prevention of Alzheimer's Dementia) and the IALSA (Integrative Analysis of Longitudinal Studies of Ageing) network of longitudinal studies of ageing and dementia.
Before working in Edinburgh, she was a Lecturer at UCL and Programme Leader Track at the MRC Lifelong Health and Ageing Unit and also worked for several years in Cambridge at the MRC Biostatistics Unit, where she also did her PhD. Her research has been supported by an MRC Career Development Award in Biostatistics, the Alzheimer's Society and the IALSA Programme Grant from the US National Institute of Health.
She has extensive experience developing and applying longitudinal methods to gain a better understanding of ageing and dementia. She is also interested in harmonisation methods for evidence synthesis and reproducible research.
Qualifications
- PhD in Biostatistics, MRC Biostatistics Unit, University of Cambridge
- Masters in Mathematical Statistics, School of Sciences, Universidad de la Republica del Uruguay
- BA in Mathematcis, School of Sciences, Universidad de la Republica del Uruguay
Research summary
Graciela is interested in the application and development of new analytical methods to improve knowledge about normative and pathological cognitive and physical declines experienced by older adults. She is particularly interested in understanding how individuals change relative to their previous level of functioning (within-person changes) as the manifestations of these changes are those that usually concern older adults. She is also interested in the development of analytical tools to predict the risk of developing dementia.
Research aims & areas of interest
- Longitudinal methods
- Risk prediction models
- Data harmonisation (see www.maelstrom-research.org)
- Analytical methods to facilitate replication and reproducible research (see www.ialsa.org)
- Graciela often runs workshops aimed at early-career researchers who want to learn and apply statistical methods to answer relevant questions about ageing and dementia
Group members
Dr Rebecca Bendayan - statistician
Dr Lucy Stirland - PhD student
Dr Hinesh Topiwala - MD student
Collaborators
- European Prevention of Alzheimer’s Disease Consortium (EPAD)
- Prof. Andrea Piccinin and Prof Scott Hofer, University of Victoria, BC, Canada
- IALSA affiliated researchers
- Dr Ardo Van den Hout, Dept. of Statistics, UCL
- Dr Brian Tom, MRC Biostatistics Unit, Cambridge
- Maelstrom Research Group, McGill University, Montreal, Canada
-
Predictors of Mild Cognitive Impairment stability, progression, or reversion in the Lothian Birth Cohort 1936
In:
Journal of Alzheimer's Disease
DOI: https://doi.org/10.3233/JAD-201282
Research output: Contribution to Journal › Article (E-pub ahead of print) -
Predictive models for mild cognitive impairment to Alzheimer’s disease conversion
In:
Neural Regeneration Research, vol. 16, pp. 1766
DOI: https://doi.org/10.4103/1673-5374.306071
Research output: Contribution to Journal › Article (E-pub ahead of print) -
Prevalence of Mild Cognitive Impairment in the Lothian Birth Cohort 1936
In:
Alzheimer disease and associated disorders
DOI: https://doi.org/10.1097/WAD.0000000000000433
Research output: Contribution to Journal › Article (E-pub ahead of print) -
Higher midlife CAIDE score is associated with increased brain atrophy in a cohort of cognitively healthy middle-aged individuals
In:
Journal of Neurology
DOI: https://doi.org/10.1007/s00415-020-10383-8
Research output: Contribution to Journal › Article (Published) -
Life Course Air Pollution Exposure and Cognitive Decline: Modelled Historical Air Pollution Data and the Lothian Birth Cohort 1936
In:
Journal of Alzheimer's Disease, pp. 1-12
DOI: https://doi.org/10.3233/JAD-200910
Research output: Contribution to Journal › Article (Published)