Dr Nema Dean

  • Reader (Statistics)

telephone: 01413306820
email: Nema.Dean@glasgow.ac.uk

R341, Mathematics & Statistics Building, University Place, Glasgow G12 8QW

Import to contacts

ORCID iDhttps://orcid.org/0000-0002-5080-2517

Biography

I received my M.A. in Mathematics from Trinity College Dublin in 2002 and my Ph.D. in Statistics from the University of Washington, Seattle in 2006. I joined the University of Glasgow in 2006.

I am predominantly an applied statistician with an interest in methodological development driven by interesting practical problems. Areas I have worked on in the past/currently include:

  • Educational testing
  • Food authenticity
  • Forensic statistics
  • Chemometrics
  • Medical applications
  • Urban studies
  • Many others...

My areas of interest methodologically are wide-ranging including: cluster analysis - particularly model-based and hierarchical, semi-supervised learning, variable selection, disease mapping, hierarchical Bayesian models, Bayesian approximation methods, boundary detection, areal modelling, spatio-temporal modelling and others. Both likelihood and Bayesian estimation are welcome (I'm a pragmatist).

Research interests

  • Unsupervised learning/Clustering
    • Model-based clustering
    • Hierarchical clustering
    • Growth mixture models
  • Variable selection
  • Spatial areal boundary detection
  • Spatio-temporal modelling
  • Disease Mapping
  • Mixtures/Hierarchical mixtures of experts
  • Item response theory models
  • Bayesian approximate estimators
  • Social network analysis

Research groups

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2019 | 2017 | 2016 | 2014 | 2013 | 2011 | 2010 | 2009 | 2008
Number of items: 24.

2024

Muegge, R. , Jack, E. , Dean, N. and Lee, D. (2024) COVID-19 vaccine fatigue in Scotland: how do the trends in attrition rates for the second and third doses differ by age, sex, and council area? Journal of the Royal Statistical Society: Series A (Statistics in Society), (Accepted for Publication)

McNealis, V., Moodie, E. E.M. and Dean, N. (2024) Revisiting the effects of maternal education on adolescents' academic performance: Doubly robust estimation in a network-based observational study. Journal of the Royal Statistical Society: Series C (Applied Statistics), (doi: 10.1093/jrsssc/qlae008) (Early Online Publication)

2023

Van Mechelen, I., Boulesteix, A.‐L., Dangl, R., Dean, N. , Hennig, C., Leisch, F., Steinley, D. and Warrens, M. J. (2023) A white paper on good research practices in benchmarking: the case of cluster analysis. WIREs Data Mining and Knowledge Discovery, 13(6), e1511. (doi: 10.1002/widm.1511)

Muegge, R. , Dean, N. , Jack, E. and Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, 100559. (doi: 10.1016/j.sste.2022.100559) (PMCID:PMC9719849)

2019

Dean, N. , Dong, G., Piekut, A. and Pryce, G. (2019) Frontiers in residential segregation: understanding neighbourhood boundaries and their impacts. Tijdschrift voor Economische en Sociale Geografie, 110(3), pp. 271-288. (doi: 10.1111/tesg.12316)

Jack, E. , Lee, D. and Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(3), pp. 1061-1080. (doi: 10.1111/rssa.12447) (PMID:31217673) (PMCID:PMC6563432)

Flynt, A. and Dean, N. (2019) Growth mixture modeling with measurement selection. Journal of Classification, 36(1), pp. 3-25. (doi: 10.1007/s00357-018-9275-9)

Flynt, A., Dean, N. and Nugent, R. (2019) sARI: a soft agreement measure for class partitions incorporating assignment probabilities. Advances in Data Analysis and Classification, 13(1), pp. 303-323. (doi: 10.1007/s11634-018-0346-x)

2017

Dean, N. and Pryce, G. (2017) Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration. Urban Studies, 54(13), pp. 3058-3070. (doi: 10.1177/0042098016668779)

Anderson, C. , Lee, D. and Dean, N. (2017) Spatial clustering of average risks and risk trends in Bayesian disease mapping. Biometrical Journal, 59(1), pp. 41-56. (doi: 10.1002/bimj.201600018) (PMID:27492753)

2016

Martyna, A., Zadora, G., Neocleous, T. , Michalska, A. and Dean, N. (2016) Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra. Analytica Chimica Acta, 931, pp. 34-46. (doi: 10.1016/j.aca.2016.05.016) (PMID:27282749)

Flynt, A. and Dean, N. (2016) A survey of popular R packages for cluster analysis. Journal of Educational and Behavioral Statistics, 41(2), pp. 205-225. (doi: 10.3102/1076998616631743)

Anderson, C., Lee, D. and Dean, N. (2016) Bayesian cluster detection via adjacency modelling. Spatial and Spatio-Temporal Epidemiology, 16, pp. 11-20. (doi: 10.1016/j.sste.2015.11.005) (PMID:26919751)

2014

Moodie, E. E.M., Dean, N. and Sun, Y. R. (2014) Q-learning: flexible learning about useful utilities. Statistics in Biosciences, 6(2), pp. 223-243. (doi: 10.1007/s12561-013-9103-z)

Anderson, C., Lee, D. and Dean, N. (2014) Identifying clusters in Bayesian disease mapping. Biostatistics, 15(3), pp. 457-469. (doi: 10.1093/biostatistics/kxu005) (PMID:24622038)

2013

Dean, N. and Nugent, R. (2013) Clustering student skill set profiles in a unit hypercube using mixtures of multivariate betas. Advances in Data Analysis and Classification, 7(3), pp. 339-357. (doi: 10.1007/s11634-013-0149-z)

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

2011

Dean, N. and Nugent, R. (2011) Comparing different clustering models on the unit hypercube. In: 58th World Statistics Congress of the International Statistical Institute, Dublin, Ireland, 21-26 Aug 2011,

2010

Dean, N. and Raftery, A. E. (2010) Latent class analysis variable selection. Annals of the Institute of Statistical Mathematics, 62(1), pp. 11-35. (doi: 10.1007/s10463-009-0258-9)

Murphy, T.B., Dean, N. and Raftery, A.E. (2010) Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications. Annals of Applied Statistics, 4(1), pp. 396-421. (doi: 10.1214/09-AOAS279)

Nugent, R., Dean, N. and Ayers, E. (2010) Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers. In: EDM2010: 3rd International Conference on Educational Data Mining, Pittsburgh, USA, 11-13 June 2010,

2009

Ayers, E., Nugent, R. and Dean, N. (2009) A comparison of student skill knowledge estimates. In: EDM2009: 2nd International Conference on Educational Data Mining, Cordoba, Spain, 1-3 July 2009,

Nugent, R., Elizabeth, A. and Nema, D. (2009) Conditional subspace clustering of skill mastery: identifying skills that separate students. In: EDM2009: 2nd International Conference on Educational Data Mining, Cordoba, Spain, 1-3 July 2009,

2008

Ayers, E., Nugent, R. and Dean, N. (2008) Skill set profile clustering based on student capability vectors computed from online tutoring data. In: EDM2008: 1st International Conference on Educational Data Mining, Montreal, Canada, 20-21 June 2008,

This list was generated on Wed May 29 21:37:27 2024 BST.
Number of items: 24.

Articles

Muegge, R. , Jack, E. , Dean, N. and Lee, D. (2024) COVID-19 vaccine fatigue in Scotland: how do the trends in attrition rates for the second and third doses differ by age, sex, and council area? Journal of the Royal Statistical Society: Series A (Statistics in Society), (Accepted for Publication)

McNealis, V., Moodie, E. E.M. and Dean, N. (2024) Revisiting the effects of maternal education on adolescents' academic performance: Doubly robust estimation in a network-based observational study. Journal of the Royal Statistical Society: Series C (Applied Statistics), (doi: 10.1093/jrsssc/qlae008) (Early Online Publication)

Van Mechelen, I., Boulesteix, A.‐L., Dangl, R., Dean, N. , Hennig, C., Leisch, F., Steinley, D. and Warrens, M. J. (2023) A white paper on good research practices in benchmarking: the case of cluster analysis. WIREs Data Mining and Knowledge Discovery, 13(6), e1511. (doi: 10.1002/widm.1511)

Muegge, R. , Dean, N. , Jack, E. and Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, 100559. (doi: 10.1016/j.sste.2022.100559) (PMCID:PMC9719849)

Dean, N. , Dong, G., Piekut, A. and Pryce, G. (2019) Frontiers in residential segregation: understanding neighbourhood boundaries and their impacts. Tijdschrift voor Economische en Sociale Geografie, 110(3), pp. 271-288. (doi: 10.1111/tesg.12316)

Jack, E. , Lee, D. and Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(3), pp. 1061-1080. (doi: 10.1111/rssa.12447) (PMID:31217673) (PMCID:PMC6563432)

Flynt, A. and Dean, N. (2019) Growth mixture modeling with measurement selection. Journal of Classification, 36(1), pp. 3-25. (doi: 10.1007/s00357-018-9275-9)

Flynt, A., Dean, N. and Nugent, R. (2019) sARI: a soft agreement measure for class partitions incorporating assignment probabilities. Advances in Data Analysis and Classification, 13(1), pp. 303-323. (doi: 10.1007/s11634-018-0346-x)

Dean, N. and Pryce, G. (2017) Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration. Urban Studies, 54(13), pp. 3058-3070. (doi: 10.1177/0042098016668779)

Anderson, C. , Lee, D. and Dean, N. (2017) Spatial clustering of average risks and risk trends in Bayesian disease mapping. Biometrical Journal, 59(1), pp. 41-56. (doi: 10.1002/bimj.201600018) (PMID:27492753)

Martyna, A., Zadora, G., Neocleous, T. , Michalska, A. and Dean, N. (2016) Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra. Analytica Chimica Acta, 931, pp. 34-46. (doi: 10.1016/j.aca.2016.05.016) (PMID:27282749)

Flynt, A. and Dean, N. (2016) A survey of popular R packages for cluster analysis. Journal of Educational and Behavioral Statistics, 41(2), pp. 205-225. (doi: 10.3102/1076998616631743)

Anderson, C., Lee, D. and Dean, N. (2016) Bayesian cluster detection via adjacency modelling. Spatial and Spatio-Temporal Epidemiology, 16, pp. 11-20. (doi: 10.1016/j.sste.2015.11.005) (PMID:26919751)

Moodie, E. E.M., Dean, N. and Sun, Y. R. (2014) Q-learning: flexible learning about useful utilities. Statistics in Biosciences, 6(2), pp. 223-243. (doi: 10.1007/s12561-013-9103-z)

Anderson, C., Lee, D. and Dean, N. (2014) Identifying clusters in Bayesian disease mapping. Biostatistics, 15(3), pp. 457-469. (doi: 10.1093/biostatistics/kxu005) (PMID:24622038)

Dean, N. and Nugent, R. (2013) Clustering student skill set profiles in a unit hypercube using mixtures of multivariate betas. Advances in Data Analysis and Classification, 7(3), pp. 339-357. (doi: 10.1007/s11634-013-0149-z)

Dean, N. and Raftery, A. E. (2010) Latent class analysis variable selection. Annals of the Institute of Statistical Mathematics, 62(1), pp. 11-35. (doi: 10.1007/s10463-009-0258-9)

Murphy, T.B., Dean, N. and Raftery, A.E. (2010) Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications. Annals of Applied Statistics, 4(1), pp. 396-421. (doi: 10.1214/09-AOAS279)

Research Reports or Papers

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

Conference Proceedings

Dean, N. and Nugent, R. (2011) Comparing different clustering models on the unit hypercube. In: 58th World Statistics Congress of the International Statistical Institute, Dublin, Ireland, 21-26 Aug 2011,

Nugent, R., Dean, N. and Ayers, E. (2010) Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers. In: EDM2010: 3rd International Conference on Educational Data Mining, Pittsburgh, USA, 11-13 June 2010,

Ayers, E., Nugent, R. and Dean, N. (2009) A comparison of student skill knowledge estimates. In: EDM2009: 2nd International Conference on Educational Data Mining, Cordoba, Spain, 1-3 July 2009,

Nugent, R., Elizabeth, A. and Nema, D. (2009) Conditional subspace clustering of skill mastery: identifying skills that separate students. In: EDM2009: 2nd International Conference on Educational Data Mining, Cordoba, Spain, 1-3 July 2009,

Ayers, E., Nugent, R. and Dean, N. (2008) Skill set profile clustering based on student capability vectors computed from online tutoring data. In: EDM2008: 1st International Conference on Educational Data Mining, Montreal, Canada, 20-21 June 2008,

This list was generated on Wed May 29 21:37:27 2024 BST.

Grants

Understanding Inequalities (ESRC) Life at the Frontier: The Impact of Social Frontiers on the Social Mobility and Integration of Migrants (Nordforsk)

Supervision

I am currently interested in supervising students in the area of multivariate analysis and spatial/spatio-temporal modelling.

Current PhD students:

  • Kirstie English
  • Riham Hamza M Ismail
  • Robin Muegge
  • Jorge Alfredo Sanchez Gomez

Former PhD students:

  • Craig Anderson
  • Cunyi Wang
  • Eilidh Jack
  • Simona Simona
  • Sebastián Martínez
  • Ivona Voroneckaja
  • Shuhrah Alghamdi

Teaching

I teach a variety of courses at various levels in undergraduate and postgraduate programmes. In the past I have taught Honours courses on Multivariate Methods, Linear Models, Linear Mixed Models and Data Mining as well as Statistics 1Z and 1C. I enjoy incorporating new methodologies and parts of my research in my courses where possible.

Current courses:

  • Data Mining & Machine Learning I (ODL)
  • Measurement & Scaling (Q-step) - not in 2022/23
 

 

Professional activities & recognition

Prizes, awards & distinctions

  • 2011: Statistics in Chemistry Award (American Statistical Association)

Professional & learned societies

  • 2011 - 2018: Treasurer, International Federation of Classification Societies
  • 2020: Board Member, British Classification Society