Dr Andrew Bell
School of Education
Senior Lecturer
+44 114 222 6065
Full contact details
School of Education
The Wave
2 Whitham Road
Sheffield
S10 2AH
- Profile
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Before moving to Sheffield, Dr. Bell was a lecturer at the University of Bristol, where he also completed his undergraduate degree (in Geography) and PhD (in Advanced Quantitative Methods). His research spans a diverse range of subject areas: his work includes a focus on health inequalities, for example looking at mental health trajectories from a life-course perspective; but he has also contributed to other disciplines including geography, political science, and economics. His work is united by a methodological interest in the development and application of multilevel models, including age-period-cohort analysis and fixed and random effects models. He is currently working on developing and applying multilevel models for uncovering intersectional inequalities, particularly in health outcomes.
- Research interests
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Multilevel modelling, longitudinal modelling, mental health and wellbeing, life course research, political science, social epidemiology
- Publications
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Books
Edited books
- Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem. Abingdon: Routledge.
Journal articles
- The statistical advantages of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy for estimating intersectional inequalities. Sociological Methods & Research. View this article in WRRO
- Corrigendum to “An analysis of intersectional disparities in alcohol consumption in the US” [Soc. Sci. Med. Volume 363, December 2024, 117514]. Social Science & Medicine, 117577-117577.
- An analysis of intersectional disparities in alcohol consumption in the US. Social Science and Medicine, 363.
- Commentary on: “age period cohort analysis – a review of what we should and shouldn’t do”. Annals of Human Biology, 51(1). View this article in WRRO
- Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to study individual longitudinal trajectories, with application to mental health in the UK. Social Science and Medicine, 351.
- Clarifications on the Intersectional MAIHDA Approach: A conceptual guide and response to Wilkes and Karimi (2024). Social Science and Medicine, 350.
- A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). SSM - Population Health, 26. View this article in WRRO
- Preferences for work and leisure: is labour supply a function of what workers prefer?. Momentum Quarterly, 11(4), 204-269. View this article in WRRO
- The role of socioeconomic deprivation in explaining neighborhood and clinic effects in the effectiveness of psychological interventions. Journal of Consulting and Clinical Psychology, 91(2), 82-94. View this article in WRRO
- Methods for disentangling period and cohort changes in mortality risk over the twentieth century: comparing graphical and modelling approaches. Quality and Quantity, 57(4), 3219-3239. View this article in WRRO
- Understanding the effect of universal credit on housing insecurity in England: a difference-in-differences approach. Housing Studies.
- Neighbourhood deprivation and intersectional inequalities in biomarkers of healthy ageing in England. Health and Place, 77.
- Revisiting the Effects of Organized Mammography Programs on Inequalities in Breast Screening Uptake: A Multilevel Analysis of Nationwide Data From 1997 to 2017. Frontiers in Public Health, 10.
- Can intersectionality help with understanding and tackling health inequalities? Perspectives of professional stakeholders. Health Research Policy and Systems, 19(1).
- Mapping intersectional inequalities in biomarkers of healthy ageing and chronic disease in older English adults. Scientific Reports, 10.
- Age period cohort analysis: a review of what we should and shouldn’t do. Annals of Human Biology, 47(2), 208-217. View this article in WRRO
- Human papillomavirus 16 promotes microhomology-mediated end-joining. Proceedings of the National Academy of Sciences, 116(43), 21573-21579.
- Research culture : a survey of new PIs in the UK. eLife, 2019(8).
- Using shrinkage in multilevel models to understand intersectionality: a simulation study and a guide for best practice. Methodology, 15(2), 88-96. View this article in WRRO
- Fixed and random effects models: making an informed choice. Quality & Quantity, 53(2), 1051-1074.
- ERCC2
Helicase Domain Mutations Confer Nucleotide Excision Repair Deficiency and Drive Cisplatin Sensitivity in Muscle-Invasive Bladder Cancer. Clinical Cancer Research, 25(3), 977-988.
- Talazoparib Is a Potent Radiosensitizer in Small Cell Lung Cancer Cell Lines and Xenografts. Clinical Cancer Research, 24(20), 5143-5152.
- Cross‐Classified Multilevel Modelling of the Effectiveness of Similarity‐Based Virtual Screening. ChemMedChem, 13(6), 582-587.
- Understanding and misunderstanding group mean centering: a commentary on Kelley et al.’s dangerous practice. Quality and Quantity, 52(5), 2031-2036.
- The hierarchical age–period–cohort model: Why does it find the results that it finds?. Quality and Quantity, 52(2), 783-799.
- Urban geography and protest mobilization in Africa. Political Geography, 53, 54-64. View this article in WRRO
- Formula for success: Multilevel modelling of Formula One Driver and Constructor performance, 1950-2014. Journal of Quantitative Analysis in Sports, 12(2), 99-112.
- Should age-period-cohort analysts accept innovation without scrutiny? A response to Reither, Masters, Yang, Powers, Zheng, and Land. Social science & medicine, 128, 331-333. View this article in WRRO
- Bayesian Informative Priors with Yang and Land’s Hierarchical Age-Period-Cohort model. Quality and Quantity, 49(1), 255-266. View this article in WRRO
- Stylised fact or situated messiness? The diverse effects of increasing debt on national economic growth. Journal of Economic Geography, 15(2), 449-472. View this article in WRRO
- Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data. Political Science Research and Methods, 3(1), 133-153. View this article in WRRO
- Life-course and cohort trajectories of mental health in the UK, 1991–2008 – A multilevel age–period–cohort analysis. Social science & medicine, 120, 21-30. View this article in WRRO
- Current practice in the modelling of Age, Period and Cohort effects with panel data: a commentary on Tawfik et al. (2012), Clarke et al. (2009), and McCulloch (2012). Quality and Quantity, 48(4), 2089-2095. View this article in WRRO
- Another 'futile quest'? A simulation study of Yang and Land's Hierarchical Age-Period-Cohort model. Demographic Research, 30, 333-360. View this article in WRRO
- Don't birth cohorts matter? A commentary and simulation exercise on Reither, Hauser and Yang's (2009) age-period-cohort study of obesity. Social Science & Medicine, 101, 176-180. View this article in WRRO
- The impossibility of separating age, period and cohort effects. Social science & medicine, 93, 163-165. View this article in WRRO
- Intersectional inequalities in neighbourhood air pollution concentration in England: A quantitative analysis of ecological data using Eco-Intersectional Multilevel (EIM) modelling. Applied Spatial Analysis and Policy.
- Intersectional inequalities in advanced stage diagnosis of colorectal cancer in England: a cross-sectional study of National cancer registry data from 2013 to 2019. Journal of Epidemiology and Community Health.
Book chapters
- Age-period-cohort analysis of attitudes towards foreigners in Germany, 1980–2016 In Hochman O, Stanciu A & Hadjar A (Ed.), 40 Jahre ALLBUS - Die deutsche Gesellschaft im Wandel (pp. 141-178). Springer VS Wiesbaden View this article in WRRO
- Introducing age, period and cohort effects In Bell A (Ed.), Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem Abingdon: Routledge.
- Multilevel models for age–period–cohort analysis In Bell A (Ed.), Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem (pp. 23-40). Abingdon: Routledge. View this article in WRRO
- Cross-Sectional and Longitudinal Studies. In Morin J-F, Olsson C & Atikcan EÖ (Ed.), Research Methods in the Social Sciences: A A-Z of Key Concepts (pp. 72-75). Oxford University Press.
- Age, period and cohort processes in longitudinal and life course analysis: a multilevel perspective In Burton-Jeangros C, Cullati S, Sacker A & Blane D (Ed.), A Life Course Perspective on Health Trajectories and Transitions (pp. 197-213). Springer International Publishing View this article in WRRO
Conference proceedings
- P100 Inequalities in colorectal cancer screening participation in Europe: the impact of screening programmes across population subgroups in a quasi-experimental study. SSM Annual Scientific Meeting (pp A84.1-A84)
- Effect of defective ERCC2 on cisplatin and ionizing radiation (IR) sensitivity in bladder cancer cells.. Journal of Clinical Oncology, Vol. 35(6_suppl) (pp 333-333)
Digital content
- Intersectional modelling in health policy: a case study on remote GP appointments and patient experience.
- Multilevel models to study intersectionality.
- Age Period Cohort models: the identification problem and what to do about it. Retrieved from https://digitalmedia.sheffield.ac.uk/id/1_y55wuyu9
- Intersectionality and health explained. Youtube. Retrieved from https://www.youtube.com/watch?v=rwqnC1fy_zc
- Making Sense Of Data In The 2019 General Election. Social Science Space. Retrieved from https://www.socialsciencespace.com/2020/01/making-sense-of-data-in-the-2019-general-election/
- Female scientists get less money and staff for their first labs. Nature News. Retrieved from https://www.nature.com/articles/d41586-019-00933-0
- Using Longitudinal Multilevel Models to Investigate the Relationship Between Urbanization and Protest Mobilization in Africa. Sage Research Methods Case Studies. Retrieved from http://methods.sagepub.com/case/longitudinal-multilevel-models-urbanization-and-protest-mobilization-africa
- Fake news: Universities offer tips on how to spot it. BBC News. Retrieved from http://www.bbc.co.uk/news/education-41902914
- The Age Period Cohort Identification Problem. YouTube video. Retrieved from https://www.youtube.com/watch?v=t0GuikebSNw
- Who is the Greatest Formula 1 Driver of All Time? - Why Numbers Matter, Episode 5. Retrieved from https://www.youtube.com/watch?v=rzzSEMNmxmI&list=PLfcfWl4oIvSRzF_bE8Snz2jqdYZX1CRKN&index=5
- Chocolate Helps You Lose Weight - Why Numbers Matter, Episode 4. Retrieved from https://www.youtube.com/watch?v=S3aLo_rYBgQ&list=PLfcfWl4oIvSRzF_bE8Snz2jqdYZX1CRKN&index=4
- Are You Above Average? - Why Numbers Matter, Episode 3. Retrieved from https://www.youtube.com/watch?v=hQLCWHww9OQ&list=PLfcfWl4oIvSRzF_bE8Snz2jqdYZX1CRKN&index=3
- Blue Monday and the problem of junk science. Futurelearn blog. Retrieved from https://www.futurelearn.com/info/blog/blue-monday-and-the-problem-of-junk-science?category=learning
- The impossibility of separating age, period and cohort effects. Conference presentation at NCRM Research Methods Festival, 2014. Retrieved from https://www.youtube.com/watch?v=j0Cb5g-lx9g
- The varying relationship between economic growth and national debt. NCRM MethodsNews. Retrieved from http://eprints.ncrm.ac.uk/3699/4/MethodsNewsAutumn2014.pdf
- Significant variation across countries means that simple conclusions regarding growth and debt, like those offered by Reinhart & Rogoff, have no policy relevance. Retrieved from http://blogs.lse.ac.uk/politicsandpolicy/debt-and-economic-growth-but-no-geography-a-cautionary-tale/
- Module 12: Cross-Classified Multilevel Models - MLwiN practical. Retrieved from http://www.bristol.ac.uk/media-library/sites/cmm/migrated/documents/12-mlwin-example.pdf
Preprints
- The Statistical Advantages of MAIHDA for Estimating Intersectional Inequalities, Center for Open Science.
- The Statistical Advantages of MAIHDA for Estimating Intersectional Inequalities, Center for Open Science.
- A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), Center for Open Science.
- A Tutorial for Conducting Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), Center for Open Science.
- Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) for longitudinal data, with application to mental health trajectories in the UK, Center for Open Science.
- Period and cohort changes in mortality risk over the twentieth century in the UK: an exploratory analysis, Center for Open Science.
- Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem. Abingdon: Routledge.
- PhD Supervision
- Christie Butcher: The characteristics and experiences of carers in the UK trends and variations 2001-2021 (with Prof Matt Bennett and Professor Sue Yeandle) ESRC-funded Data Analytics and Society CDT, in partnership with CarersUK
- Harriet Ann Patrick: The financial costs of unpaid care in a geographical context (with Prof Matt Bennett and Professor Sue Yeandle) ESRC-funded Data Analytics and Society CDT, in partnership with Office for National Statistics
- Rhiannon Williams: Tackling homelessness in the UK: a data analytics approach (with Prof Gwilym Price and Dr Beth Garratt). ESRC-funded Data Analytics and Society CDT, in partnership with Shelter