Dr Eduwin Pakpahan

Associate Professor

School: Engineering, Physics and Mathematics

Eduwin Pakpahan is Associate Professor in Mathematics in the School of Engineering, Physics, and Mathematics, Northumbria University, where he leads the Applied Statistics and Data Science (ASDS) research group and is Theme Lead for Mathematics.

His research examines how disadvantage accumulates across a life course and surfaces decades later as cognitive decline and multimorbidity, and how far associations observed in cohort data can bear a causal reading. He works with harmonised cohort studies of ageing — ELSA, SHARE, HRS and CLHLS — and with data from low- and middle-income settings, including the Indonesia Family Life Survey. He is developing dementia risk prediction models for low- and middle-income countries, where instruments built in high-income cohorts typically lose calibration and formal diagnosis is sparse or absent.

The methodological work sits in longitudinal data analysis: mixed-effects and latent variable models for repeated measures, with attention to heterogeneity in individual trajectories, informative dropout, and confounders that are themselves time-varying. His doctorate, completed at the University of Perugia (Italy), was on causal inference in Gaussian graphical Markov models. That training still shapes his approach: he treats a model's assumptions as claims to be scrutinised rather than caveats to be listed.

A longstanding interest concerns the relationship between quantitative and qualitative evidence. Causal claims in population health seldom rest on statistical estimates alone; they depend on mechanism, context and judgement that survey data document only in part. He is interested in how the two kinds of evidence can be made to constrain each other rather than proceed in parallel.

Before joining Northumbria in 2020 he was at Newcastle University and the University of East Anglia, and earlier a research associate at the European University Institute in Florence. His first degree in Statistics is from Bogor Agricultural University, Indonesia. He is a Fellow of the Royal Statistical Society. He welcomes enquiries from prospective PhD students and from colleagues with longitudinal or cohort data that raise causal questions.

Email Eduwin

Research Themes and Scholarly Interests

Mixed-effects models and longitudinal data analysis — heterogeneity in individual trajectories, attrition and informative dropout, measurement invariance over time

Causal inference with graphical models — instrumental variable methods, Gaussian graphical Markov models, time-varying confounding in observational data

Latent variable and multivariate models for constructs that are measured only indirectly

Life-course models of ageing, cognition and health inequality

Dementia risk prediction in low- and middle-income settings

Cross-country harmonised cohort studies (ELSA, SHARE, HRS)

Key Publications

Please visit the Pure Research Information Portal for further information
Development and validation of a dementia risk prediction model for low- and middle-income countries: the 10/66 Study, Pakpahan, E., Guan, Z., Siervo, M., Muniz Terrera, G., Mohan, D., Acosta, D., Sosa, A., Acosta, I., Llibre-Rodriguez, J., Llibre-Guerra, J., Prince, M., Worrall, A., Naheed, A., Vella, A., Jiang, J., Lipnicki, D., Sachdev, P., Robinson, L., Prina, M., Stephan, B. 2 Jun 2026, In: American Journal of Epidemiology
Longitudinal Pattern of Multimorbidity in Older Adult Population: Latent Transition Analysis in 34 Countries, Izzati, R., Pakpahan, E. 1 Mar 2026, In: American Journal of Epidemiology
Prediction of dementia risk in low-income and middle-income countries (the 10/66 Study): an independent external validation of existing models, Stephan, B., Pakpahan, E., Siervo, M., Licher, S., Muniz-Terrera, G., Mohan, D., Acosta, D., Rodriguez Pichardo, G., Sosa, A., Acosta, I., Llibre-Rodriguez, J., Prince, M., Robinson, L., Prina, M. 1 Apr 2020, In: The Lancet Global Health
The long arm of childhood circumstances on health in old age: Evidence from SHARELIFE, Pakpahan, E., Hoffmann, R., Kröger, H. 1 Mar 2017, In: Advances in Life Course Research
Structured Cardiac Assessment and Treatment Following Exacerbations of COPD (SCATECOPD): A Pilot Randomised Controlled Trial, Kibbler, J., Pakpahan, E., McCarthy, S., Webb-Mitchell, R., Prasad, A., Ripley, D., Gray, J., Bourke, S., Steer, J. 7 Mar 2025, In: Biomedicines

Current and Recent Projects

Please visit the Pure Research Information Portal for further information
tNIVOW - Standard versus accelerated weaning from non-invasive ventilation in COPD directed by the NIV Outcomes score, Gray, J. (Principal Investigator), Pakpahan, E. (Co Investigator), National Institute for Health Research, 01/08/22 - 31/07/25, £55,043.00

PGR Supervision

Ridho Al Izzati ??The Long Arm of Childhood: Cross-national Comparisons using Big Cohort Data? Start Date: 01/10/2023
Ridho Al Izzati The long-arm of childhood: Cross-national comparisons using Big Cohort Data Start Date: 01/10/2023 End Date: 17/10/2025

Qualifications