BIAS: Research Programme

Social science data are notoriously full of missing values, non-responses, selection biases and other idiosyncrasies. Simple analyses are usually very misleading; instead a comprehensive set of inter-dependent sub-models are needed to model the data complexities and core processes that social scientists want to understand. It is also invariably the case that a single dataset fails to provide all the necessary information, and many of the complex research questions require the combination of datasets from multiple sources.

Bayesian graphical and hierarchical models offer a natural tool for linking together many different sub-models and data sources.

The BIAS I research programme consists of three methodological components:

In BIAS II, our aims are to address new methodological challenges in the modelling of observational data, in particular surveys, longitudinal studies and small area data; to extend and apply our BIAS I methods to new social science problems; and to foster a number of new collaborations with social scientists, both nationally and internationally. The methodological components of the BIAS II research programme are

We are also collaborating with government and social scientists to apply our methods to in four substantive areas

Published papers and books

2012

Mason A; Richardson S; Best N. (2012). Two-pronged strategy for using DIC to compare selection models with non-ignorable missing responses. Bayesian Analysis. 7:109-146 DOI.

Mason, A., Richardson, S., Plewis, I., and Best, N. Strategy for modelling non-random missing data mechanisms in observational studies using Bayesian methods. Journal of Official Statistics. The accepted version of the paper can be downloaded from here and the abstract can be found here.

G. Li, N. Best, A. Hansell, I. Ahmed, and S. Richardson. BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice. Biostatistics 2012; doi: 10.1093/biostatistics/kxs005.

2011

G. Li, S. Richardson, L. Fortunato, I. Ahmed, A. Hansell, M. Toledano and N. Best. Data mining cancer registries: retrospective surveillance of small area time trends in cancer incidence using BaySTDetect. published in the Proceedings of the IEEE ICDM'11 Spatial and Spatiotemporal Workshop. Paper can be obtained from here.

L. Fortunato, JJ Abellan, L. Beale, S. LeFevre, and S. Richardson (2011). Spatio-temporal patterns of bladder cancer incidence in Utah (1973-2004) and their association with the presence of toxic release inventory sites. Int J Health Geogr. 10:16 Full paper can be found here.

S. Geneletti, A. Mason and N. Best. Adjusting for Selection Effects in Epidemiologic Studies: Why Sensitivity Analysis is the Only "Solution". (2011). Epidemiology. 22(1), 36-39. Paper can be found here.

2010

R. Haining, G. Li, R. Maheswaran, M. Blangiardo, J. Law, S. Richardson and N. Best. Inference from ecological models: estimating the relative risk of stroke from air pollution exposure using small area data. Spatial and Spatio-temporal Epidemiology 2-3:123-131 (2010). For full paper, please follow this link.

P Gustafson, L.C Mc Candless, A.R. Levy and S. Richardson Simplified Bayesian sensitivity analysis for mismeasured and unobserved confounders,Biometrics, Published Online: 11 Jan 2010. DOI: 10.1111/j.1541-0420.2009.01377.x. Paper available from here.

2009

David Lunn, David Spiegelhalter, Andrew Thomas, Nicky Best. The BUGS project: Evolution, critique and future directions. Statistics in Medicine. (2009). 28(25):3049-3067. Official URL http://onlinelibrary.wiley.com/doi/10.1002/sim.3680/abstract

S. Richardson and C. Guihenneuc-Jouyaux. Impact of Cliff and Ord (1969, 1981) on Spatial Epidemiology Geographical Analysis, 41(4): 444-451 (2009). Paper available here.

G. Ormond, M.J. Nieuwenhuijsen, P. Nelson, M.B. Toledano, N. Iszatt, S. Geneletti and P. Elliott. Endocrine Disruptors in the Workplace, Hair Spray, Folate Supplementation, and Risk of Hypospadias: Case–Control Study. Environmental Health Perspectives (2009) 117(2): 303-307. http://www.ehponline.org/docs/2008/11933/abstract.html.

Jackson, C., Best, N.G. and Richardson, S. Bayesian graphical models for regression on multiple data sets with different variables. Biostatistics (2009) 10(2): 335-351. Paper is available here.

D. Lunn, N. Best, D. Spiegelhalter, G. Graham and B. Neuenschwander. Combining MCMC with 'sequential' PKPD modeling. Journal of Pharmacokinetics and Pharmacodynamics (2009) doi: 10.1007/s10928-008-9109-1. Published online in advance of print. Open access.

S. Geneletti, S. Richardson and N. Best. Adjusting for selection bias in case control studies. Biostatistics (2009) 10(1) 17-31. Paper is available here.

N.T. (Jassy) Molitor, N. Best, C. Jackson and S. Richardson. Using Bayesian graphical models to model biases in observational studies and to combine multiple datasources: Application to low birth-weight and water disinfection by-products. Journal of the Royal Statistical Society, Series A (2009) 172(3) 615-637. Paper is available here.

C. Jackson, N. Best and S. Richardson. Bayesian graphical models for regression on multiple datasets with different variables Biostatistics (2009) 10(2): 335-351 PDF (open access).

S. Geneletti, N. Best and S. Richardson. Adjusting for selection bias in retrospective case control studies. Biostat (2009) 10 (1): 17-31. Paper available here.

2008

Abellan JJ, Richardson S and Best N. Use of space-time models to investigate the stability of patterns of disease. Environ Health Perspect 116(8), (2008), 1111-1119. Available on open access from here .

R.S. Bivand, E.J. Pebesma and V. Gómez-Rubio. Applied Spatial Data Analysis with R. Springer (2008). For more detail, click here.

C. Jackson, S. Richardson and N. Best. Studying place effects on health by synthesising individual and area-level outcomes, Social Science and Medicine (2008) 67:1995-2006. Available online at ScienceDirect.

C. Jackson, N. Best and S. Richardson. Hierarchical related regression for combining aggregate and individual data in studies of socio-economic disease risk factors. Blackwell Synergy Society Series A: Statistics in Society 171(1):159-178. (January 2008)

2007

Abellan JJ, Fecht D, Best N, Richardson S, Briggs DJ. Bayesian analysis of the multivariate geographical distribution of the socio-economic environment in England. Environmetrics 18(7), (2007), 745-758. Abstract available from here .

2006

Richardson, S., Abelan, J.J.,and Best, N. Bayseian spatio-temporal analysis of joint patterns of male and female lung cancer in Yorkshire (UK). Statistical Methods in Medical Research 15, (2006), 385-407. Abstract available from here.

C. Jackson, N. Best and S. Richardson. Improving ecological inference using individual-level data (Statistics in Medicine, 2006, 25(12):2136-2159, June 30). Available from Wiley InterScience.

2005

S. Richardson, C. Jackson and N. Best. Bayesian hierarchical models in ecological studies. PDF. Abstract of invited paper, International Workshop for Statistical Modelling, Sydney, July 2005.

N. Best, C. Jackson and S. Richardson. Modelling complexity in health and social sciences: Bayesian graphical models as a tool for combining multiple sources of information. DOC. In: Proceedings of the 3rd ASC International Conference on Survey Research Methods, eds. Banks, R., Cornelius, R., Evans, S. and Manners, T

Working papers

Del Bono E, Francesconi M and Best N. Health information and health outcomes: An application of the Regression Discontinuity design to the 1995 UK contraceptive pill scare case. Report can be found here.

Nicoletti C and Best N. Quantile regression with aggregated data. Report can be found here.

G. Li, R. Haining, S. Richardson and N. Best. Evaluating Neighbourhood Policing using Bayesian Hierarchical Models: No Cold Calling in Peterborough, England. PDF is available here.

A. Mason, S. Richardson, I. Plewis and N. Best. Strategy for modelling non-random missing data mechanisms in observational studies using Bayesian methods . Submitted and pdf is available here.

L. C. McCandless, S. Richardson and N. Best. Adjustment for Missing Confounders Using External Validation Data and Propensity Scores. Get pdf here.

L. C. McCandless, P. Gustafson, A. R. Levy and S. Richardson. Hierarchical Priors for Bias Parameters in Bayesian Adjustment for Unmeasured Confounding. Get pdf here.

S. Geneletti, N. Best, M. Toledano, P. Elliot and S. Richardson. Uncovering selection bias in case-control studies using Bayesian poststratification. PDF. Submitted.

V. Gómez Rubio, N. Best, S. Richardson, G. Li and P. Clarke. Bayesian Statistics Small Area Estimation. Get pdf here.

V. Gómez Rubio, N. Best and S. Richardson. A comparison of different methods for small area estimation. PDF. In preparation.

Technical reports

Alexina Mason, Nicky Best, Ian Plewis and Sylvia Richardson. Insights into the use of Bayesian models for informative missing data. The report can be downloaded here.

Presentations

Guangquan Li et al. "BaySTDetect: Detecting unusual temporal patterns in small area disease rates using Bayesian posterior model probabilities" presented at the International Society of Bayesian Analysis conference in Kyoto, June 29, 2012. Slides can be downloaded here.

Guangquan Li et al. "BaySTDetect: Detecting unusual temporal patterns in small area disease rates using Bayesian posterior model probabilities" presented at the American Annual Geographer conference New York, February 24-28, 2012. Slides can be downloaded here.

Alexina Mason et al. "A comparison of fully Bayesian and two-stage imputation strategies for missing covariate data" presented at the 5th Annual Bayesian Biostatistics Conference at the University of Texas, January 23-25, 2012. Slides can be downloaded here.

Guangquan Li et al. "Data mining cancer registries: Retrospective surveillance of small area time trends in cancer incidence using BaySTDetect" presented at the International Workshop on Spatial Spatio-temporal Data Mining, Dec. 11-14, 2011. Slides can be downloaded here.

Nicky Best. "Bayesian space-time models for surveillance and policy evaluation using small area data" a seminar was given at the Southampton Statistical Sciences Research Institute (S3RI), Nov. 2011. Slides can be downloaded here.

Guangquan Li, Philip Clarke, Alan Taylor, Sylvia Richardson and Nicky Best. "Improving small area estimates of income using Bayesian hierarchical models with heteroscedastic sampling error variances". A poster presented at the Small Area Estimation conference at Trier, Germany (11-13 August, 2011). The poster can be downloaded from here.

Guangquan Li. "Evaluation neighbourhood policing using Bayesian hierarchical models: No Cold Calling in Peterborough, England". British Society of Criminology annual conference, 3-6 July 2011 at the University of Northumbria, Newcastle. Slides are avaiable here.

Alexina Mason. "Eliciting expert opinion about missing data in longitudinal studies". Understanding Society/BHPS 2011 Conference, 1 July 2011 at the University of Essex, Colchester. Slides are here.

Jane Holmes. "Hierarchically Related Regression: combining ecological inference and multilevel modelling". A poster presentation given at the conference of Hierarchical models and Markov Chain Monte Carlo, Crete, June 2-5, 2011. It is available for download here.

Guangquan Li. "Bayesian hierarchical models for small area data with applications in social science". Presentation given at the NCRM and SRA joint event series in 2011 (May 11, 2011). Talk slides can be downloaded here

Alexina Mason. "Why missing data should not be ignored and Bayesian methods are good". Presentation given to the Neonatal Research Team at the Chelsea and Westminster Hospital, April 2011. Slides are available here.

Nicky Best. "Bayesian approaches for combining multiple data sources to adjust for missing confounders". Plenary Lecture, 4th International Joint Meeting of the Institute of Mathematical Statistics and the International Society for Bayesian Analysis, Utah, Jan 5-7 2011. Slides are available here.

Nicky Best. Models for small area data, with applications in health care. Invited tutorial presented at symposium on “Disease Mapping applications in Health Economics and Health Services Research”, Valencia, Spain, June 22 2010. Slides can be downloaded here.

Alexina Mason, Sylvia Richardson, Lawrence McCandless and Nicky Best. Bayesian approaches for combining multiple data sources to adjust for missing confounders. EAM-SMABS 2010, July 21-23, 2010 in Potsdam/Berlin. Slides are available here.

Stephen Fisher, Jane Holmes, Nicky Best and Sylvia Richardson. Combining individual and aggregate data to improve estimates of ethnic voting in Britain in 2001 and 2005. Research Methods Festival, 8 July 2010 in Oxford. Slides are available here.

Alexina Mason, Sylvia Richardson and Nicky Best. Bayesian Graphical Models for Combining Multiple Data Sources. Research Methods Festival, 8 July 2010 in Oxford. Slides are available here.

Guangquan Li, Sylvia Richardson, Robert Haining and Nicky Best. A Bayesian mixture model for detecting unusual time trends: Modelling burglary counts in Cambridge. Research Methods Festival, 7 July 2010 in Oxford. Slides are available here.

Alexina Mason, Nicky Best, Sylvia Richardson and Ian Plewis Strategy for modelling non-random missing data mechanisms in longitudinal studies: application to income data from the Millennium Cohort Study A poster presented at the Ninth Valencia International Meeting on Bayesian Statistics, June 3-8, 2010 in Benidorm, Spain. PDF

Guangquan Li, Sylvia Richardson, Anna Hansell and Nicky Best. A Bayesian mixture model for detecting unusual time trends in small area estimates: application to COPD mortality in England. A poster presented at the Ninth Valencia International Meeting on Bayesian Statistics, June 3-8, 2010 in Benidorm, Spain. PDF

Guangquan Li, Sylvia Richardson, Anna Hansell and Nicky Best. A Bayesian mixture model for detecting unusual time trends in small area estimates: application to COPD mortality in England. A poster presented at the Statistical methods for outbreak detection conference, 19 May, 2010 Open University, Milton Keynes. PDF

S. Richardson, A. Mason, L. McCandless and N. Best. Bayesian graphical models for combining multiple data sources, with applications in environmental epidemiology presented at the 2010 Eastern North American Region (ENAR) conference. Slides are available here .

A. Mason Strategy for modelling non-random missing data mechanisms in longitudinal studies using Bayesian methods: application to income data from the Millennium Cohort Study. An invited seminar at the University of Manchester, Feb. 2010. pdf.

S. Richardson. Introduction to spatial epidemiology: some methodological issues and recent developments A tutorial lecture given at the opening workshop for the SAMSI program on Space-time analysis for Environmental Mapping, Epidemiology and Climate Change, September 13-16, 2009. The slides are available here with a list of references.

G. Li, N. Best, P. Clark and S. Richardson. Detecting unusual time trends: A Bayesian mixture modelling approach given in the Annual Royal Geographical Society Conference, 2009 in Manchester. The slides are available here.

S. Fisher, J. Key, N. Best and S. Richardson. Ethnic dealignment? Combining individual and aggregate data to improve estimates of ethnic voting in Britain in 2001 and 2005, presented at the Political Studies Association Conference, April 2009, Manchester. Presentation slides are available here.

G. Li, N. Best, P. Clark and S. Richardson. A mixture model for detecting unusual temporal patterns with an application to income modelling given in the conference on Small Area Estimation, 2009 in Elche, Spain. The slides are here.

A.P. Dawid and S. Geneletti. The decision theoretic approach to causal inference to give in the BIRS Causal Inference workshop in May 2009. PDF.

S. Geneletti. Identifying direct and indirect effects given in Graphical Models and Genetic Applications, Warwick, 15-17 April 2009. PDF.

N. Best, G. Li, V. Gómez-Rubio and S. Richardson. Spatial and Spatial-temporal models for small area data , a poster presented. pdf.

N. Best, C. Jackson and S. Richardson. Studying place effects on health by synthesising individual and area-level outcomes using a new class of multilevel models , Invited seminar, University of Manchester, Oct 2008. Slides are available here.

S. Geneletti, N. Best and S. Richardson. Adjusting for selection bias in case control studies. given at the International Biometric Society conference in July 2008 in Dublin. PDF.

V. Gómez-Rubio, N. Best, S. Richardson and P. Clarke. Bayesian statistics for Small Area Estimation. PDF. Presented at 'GSS Methodology Conference 2008'. London, June 2008.

S. Geneletti, N. Best and S. Richardson. Sample Surveys and Bayesian Statistics: Adjusting for selection bias in case control studies using Bayesian post-stratification 2008. PDF.

S. Geneletti. What are graphical models? presented at the NCRM Research Methods Festival 2008. PDF.

S. Geneletti. Invited to talk at ECNIS Workshop: Graphical Approaches to Assessing Causality in Epidemiology. Using directed acyclic graphs (DAGs) and conditional independence to understand complex relationships in epidemiology. 7th Febuary 2008. PDF .

S. Geneletti. Invited to talk at the University of Cambridge Statistical Laboratory Seminar series on Identifying direct and indirect effects. 25th January 2008. PDF

Sylvia Richardson, Lawrence McCandless, Jassy Molitor and Nicky Best. Bayesian Approaches to Adjustment for Unmeasured Confounders. PDF.

Nuoo-Ting (Jassy) Molitor, Chris Jackson, Nicky Best and Sylvia Richardson. Bayesian graphical models for combining mismatched administrative and survey data: application to low birth weight and water disinfection by-products. PPT. Presented at 'Recent Advances in Multilevel Modelling Methodology and Applications', Joint Meeting of the RSS Social Statistics and General Applications Sections 5 December 2007.

S. Geneletti and L. McCandless. Bayesian methods for combining multiple Individual and Aggregate data Sources in observational studies. PDF.

V. Gómez-Rubio, N. Best, S. Richardson and P. Clarke. Bayesian Statistics, Small Area Estimation and why no one is poor in Sweden. PDF. Presented at the Royal Statistical Society Conference. York, U.K. 16-19 July 2007.

J. Molitor, S. Richardson and N. Best. Low birthweight and water disinfection byproducts: a multiple-bias modelling approach. Powerpoint. Presented at the Taipei International Statistical Symposium and ICSA International Conference. Academia Sinica, Taipei. 25-27 June, 2007.

N. Best, C. Jackson. Bayesian graphical models for inference from combinations of data. PowerpointPresented at the ESRC NCeSS workshop on combining and enhancing data, Manchester, Jan 2007

C. Jackson. Combining administrative and survey data in a study of low birth weight and air pollution. Powerpoint. Presented at the annual meeting of the ESRC National Centre for Research Methods, Manchester, Jan 2007.

V. Gómez Rubio. Bayesian methods for small area estimation using spatio-temporal models. PDF. Presented at the International Workshop on Spatio-Temporal Modelling (METMA3). Pamplona, Spain, 27-29 September 2006.

S. Geneletti and A.P. Dawid. Talk in RSS conference: The Effect of treatment on the treated, a decision theoretic view. 10-14th September 2006. PDF .

C. Jackson. Hierarchical models for combining multiple data sources measured at individual and small area levels. Powerpoint. Presented at the ESRC Research Methods Festival, Oxford, 17-20 July 2006.

N. Best. Introduction to Bayesian inference and computation for social science data analysis. Powerpoint. Presented at the ESRC Research Methods Festival, Oxford, 17-20 July 2006.

V. Gómez Rubio. A comparison of different methods for small area estimation. PDF. Presented at the 3rd Joint Meeting GUDO 3 of the Spanish Region of the IBS and the Spanish Society of Epidemiology, Valencia, Spain, 22 - 23 June 2006. Also PDF, presented at the Spatial Epidemiology Conference, London, May 2006.

C. Jackson. Hierarchical modelling of traffic-related benzene exposure and childhood leukaemia. Powerpoint. Presented at the 8th Valencia Meeting on Bayesian Statistics in Benidorm, Spain, 1-7 June 2006. Also Powerpoint, presented at the Spatial Epidemiology Conference, London, May 2006.

S. Geneletti. DAGs for selection bias in case-control studies. PDF. Presented at the 8th Valencia Meeting on Bayesian Statistics in Benidorm, Spain, 1-7 June 2006.

N. Best. Graphical models for combining multiple sources of information in observational studies. Powerpoint. Internal seminar, Imperial College, November 2005.

C. Jackson. Graphical models for combining multiple sources of information in observational studies. ii) Case study of socioeconomic risk factors for cardiovascular disease . Powerpoint. Internal seminar, Imperial College, November 2005.

N. Best. Graphical models for combining multiple data sources. Powerpoint. Given at the launch event of the National Centre for Research Methods, Oxford, June 2005.

PhD thesis

A. Mason (2009) Bayesian methods for modelling non-random missing data mechanisms in longitudinal studies, Imperial College London. The thesis is available from here.

Press articles

Putting ill-health in its place. ESRC The Edge, November 2005.


Presentations by collaborators

R.Haining, G.Li, S.Richardson and N.Best. "Space-time Modelling to support local policing". A plenary lecture presented at the American Annual Geographer conference New York, February 24-28, 2012. Slides can be downloaded here.

R.Haining, G.Li, S.Richardson and N.Best. "Evaluating Peterborough’s 'no cold calling' initiative using space-time Bayesian hierarchical modelling". Paper presented at the CSI Special One-Day Meeting 26th September 2011, Cambridge. Slides can be downloaded here.

R.Haining, G.Li, S.Richardson and N.Best. "The application of space-time bayesian hierarchical modelling to policy assessment: evaluating Peterborough's no cold calling initiative". Paper presented at the Symposium on Spatio-Temporal Analysis and Data Mining, University College, London, UK, July 18-19, 2011.

R.Haining, G.Li, S.Richardson and N.Best. "Change detection in space-time data using Bayesian hierarchical modelling." Research seminar to be presented to the State Key laboratory of Resources and Environmental Information Systems, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China, July 5th-6th, 2011.

R.Haining, G.Li, S.Richardson and N.Best. "Advancing spatial and spatio-temporal data analysis: examples from the BIAS II project." Keynote paper to be presented to the 1st IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (in conjunction with the 8th Beijing International Workshop on Geographical Information Science), Fuzhou, June 29th-July 1st 2011.

R.Haining, G.Li, S.Richardson and N.Best. "A Bayesian hierarchical modelling approach to policy assessment: evaluating the 'no cold calling scheme in Peterborough, England." Paper presented to the Annual Conference of the Association of American Geographers, Seattle, Washington, USA, April 12th-16th 2011. Slides can be downloaded here.

John Molitor. Spatial Mapping of Multivariate Profiles given at the 19th International Conference on Computational Statistics in Paris (August 22-27, 2010).Talk slides (ppt format) are available here.

Ravi Maheswaran, Guangquan Li, Jane Law, Robert Haining, Marta Blangiardo, Sylvia Richardson and Nicky Best. Inference from ecological models: air pollution and stroke using data from Sheffield, England given at the GEOMED 2009 at the Institute of Psychiatry auditorium, MUSC, Charleston, SC, USA. Talk slides (ppt) are available here.

Alexina Mason (with thanks to Nicky Best, Ian Plewis and Sylvia Richardson). Methodological developments for combining data. PDF. Presented at the 'ESRC Research Methods Festival'. Oxford, July 2008.

Jon Forster (University of Southampton, UK). Bayesian Methods for Multivariate Categorical Data. PDF. Presented at the ESRC Research Methods Festival, Oxford, 17-20 July 2006.

Juanjo Abellan (Imperial College, London). Bayesian methods for small area estimation and spatial analysis. PDF. Presented at the ESRC Research Methods Festival, Oxford, 17-20 July 2006.