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Dr Eduwin Pakpahan

Senior Lecturer

Department: Mathematics, Physics and Electrical Engineering

I completed my first degree in Statistics at Bogor Agricultural University, Indonesia, and PhD at University of Perugia, Italy (2012). My thesis examined the causal inference in Gaussian graphical Markov model (an extension of the instrumental variable method). Then I moved to European University Institute, Firenze as a research associate, and in Nov 2016 I moved to UK; first to School of Health Science, Univ of East Anglia, Norwich, then in Sept 2017 to Newcastle University.

I joined Northumbria University in June 2020 as a lecturer in statistics at Dept of Mathematics, Physics and Electrical Engineering. My research interests are in the mixed effect model and generalized latent variable model with application in health and social sciences (particularly in aging research and using cross-country cohort studies, such as SHARE, ELSA, or HRS). In addition, not limited to the statistical side, I am also interested in "causal reasoning" and the interplay between quantitative and qualitative approaches.


ORCID ID: 0000-0002-0058-1808

Eduwin Pakpahan

Research Themes and Scholarly Interests

Mixed effect model and longitudinal data analysis
Graphical model and multivariate analysis
Life-course models in aging
Epidemiology and Public Health

In collaboration with colleagues from Newcastle and Nottingham, among others, we are developing the risk prediction model of dementia in low- and middle-income countries (LMIC).

Key Publications

  • Please visit the Pure Research Information Portal for further information
  • 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
  • Factors associated with change in self-reported physical activity in the very old: The Newcastle 85+ study, Granic, A., Davies, K., Dodds, R., Duncan, R., Uwimpuhwe, G., Pakpahan, E., Robinson, S., Sayer, A. 16 Jul 2019, In: PLoS One
  • The reciprocal relationship between material factors and health in the life course: evidence from SHARE and ELSA, Hoffmann, R., Kröger, H., Pakpahan, E. 1 Dec 2018, In: European Journal of Ageing
  • Health inequalities and the interplay of socioeconomic factors and health in the life course, Hoffmann, R., Kröger, H., Pakpahan, E. 31 Mar 2018, The Palgrave Handbook of Biology and Society, London, Palgrave Macmillan
  • 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
  • Statistical methods for causal analysis in life course research: an illustration of a cross-lagged structural equation model, a latent growth model, and an autoregressive latent trajectories model, Pakpahan, E., Hoffmann, R., Kröger, H. 2 Jan 2017, In: International Journal of Social Research Methodology
  • Consequences of measurement error for inference in cross-lagged panel design-the example of the reciprocal causal relationship between subjective health and socio-economic status, Kröger, H., Hoffmann, R., Pakpahan, E. 1 Feb 2016, In: Journal of the Royal Statistical Society. Series A: Statistics in Society
  • Identification of causal effects in linear models: beyond instrumental variables, Stanghellini, E., Pakpahan, E. 1 Sep 2015, In: Test
  • What causes health inequality?: A systematic review on the relative importance of social causation and health selection, Kröger, H., Pakpahan, E., Hoffmann, R. Dec 2015, In: European Journal of Public Health


  • PhD December 11 2012
  • Fellow Society for Longitudinal & Life Course Studies (SLLS) 2013
  • Fellow Royal Statistical Society (RSS) 2013

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