Lucinda Archer BSc (Hons) MSc MPH (HTA) PGCHE FHEA

Lucinda Archer

Department of Applied Health Sciences
Assistant Professor in Biostatistics

Contact details

Address
Public Health Building
Applied Health Research
University of Birmingham
Edgbaston
Birmingham
B63 4HA

Lucinda is an Assistant Professor in Biostatistics, in the Tests and Prediction group at the University of Birmingham. Her research focuses on prediction modelling research, both prognostic and diagnostic, with a particular interest in statistical methods development and improving methodological quality of published research.

ORCiD iD: 0000-0003-2504-2613 

Google Scholar profile 

Qualifications

  • Postgraduate Certificate in Higher Education (PGCHE), Keele University, 2020
  • Master of Public Health (MPH), University of Birmingham, 2018
  • MSc Operational Research and Applied Statistics, Cardiff University, 2015
  • BSc (Hons) Mathematics, Cardiff University, 2014

Teaching

Under/Post-graduate modules:

  • Public Health MPH/Diploma/Certificate – Epidemiology, Statistics and Research Methods (ESRM), Practical Epidemiology and Statistics (PEaS), Dissertation supervision.
  • Medicine and Surgery (MBChB) — Medical Statistics component in Professional and Academic Skills 2
  • Mathematics BSc/MSci – Medical Statistics

 Continuing Professional Development

  • Statistical Methods for Risk Prediction and Prognostic Models
  • Prognosis Research in Healthcare, International Summer School
  • Statistical Methods for IPD Meta-Analysis
  • Systematic reviews of prediction and prognosis studies

Publications

Recent publications

Article

Archer, L, Hattle, M, Riley, RD & The eFI+ investigators 2024, 'Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults', Age and Ageing, vol. 53, no. 3, afae057. https://doi.org/10.1093/ageing/afae057

for the International Prediction of Pregnancy Complications collaborative network 2024, 'Development and validation of a prognostic model to predict birth weight: individual participant data meta-analysis', BMJ Medicine, vol. 3, no. 1, e000784. https://doi.org/10.1136/bmjmed-2023-000784

Moriarty, AS, Paton, LW, Snell, KIE, Archer, L, Riley, RD, Buckman, JEJ, Chew Graham, CA, Gilbody, S, Ali, S, Pilling, S, Meader, N, Phillips, B, Coventry, PA, Delgadillo, J, Richards, DA, Salisbury, C & McMillan, D 2024, 'Development and validation of a prognostic model to predict relapse in adults with remitted depression in primary care: secondary analysis of pooled individual participant data from multiple studies', BMJ Mental Health, vol. 27, no. 1, e301226. https://doi.org/10.1136/bmjment-2024-301226

Collins, GS, Dhiman, P, Ma, J, Schlussel, MM, Archer, L, Van Calster, B, Jr, FEH, Martin, GP, Moons, KGM, van Smeden, M, Sperrin, M, Bullock, GS & Riley, RD 2024, 'Evaluation of clinical prediction models (part 1): from development to external validation', BMJ, vol. 384, e074819. https://doi.org/10.1136/bmj-2023-074819

Riley, RD, Archer, L, Snell, KIE, Ensor, J, Dhiman, P, Martin, GP, Bonnett, LJ & Collins, GS 2024, 'Evaluation of clinical prediction models (part 2): how to undertake an external validation study', BMJ (Clinical research ed.), vol. 384, e074820. https://doi.org/10.1136/bmj-2023-074820

Riley, RD, Snell, KIE, Archer, L, Ensor, J, Debray, TPA, Van Calster, B, Van Smeden, M & Collins, GS 2024, 'Evaluation of clinical prediction models (part 3): calculating the sample size required for an external validation study', BMJ, vol. 384, e074821. https://doi.org/10.1136/bmj-2023-074821

Archer, L, Peat, G, Snell, KIE, Hill, JC, Dunn, KM, Foster, NE, Bishop, A, van der Windt, D & Wynne-Jones, G 2024, 'Musculoskeletal Health and Work: Development and Internal-External Cross-Validation of a Model to Predict Risk of Work Absence and Presenteeism in People Seeking Primary Healthcare', Journal of Occupational Rehabilitation. https://doi.org/10.1007/s10926-024-10223-w

Riley, RD, Pate, A, Dhiman, P, Archer, L, Martin, GP & Collins, GS 2023, 'Clinical prediction models and the multiverse of madness', BMC medicine, vol. 21, no. 1, 502. https://doi.org/10.1186/s12916-023-03212-y

Archer, L, Snell, KIE, Stynes, S, Axén, I, Dunn, KM, Foster, NE, Wynne-Jones, G, van der Windt, DA & Hill, JC 2023, 'Development and External Validation of Individualized Prediction Models for Pain Intensity Outcomes in Patients With Neck Pain, Low Back Pain, or Both in Primary Care Settings', Physical Therapy, vol. 103, no. 11, pzad128. https://doi.org/10.1093/ptj/pzad128

Hudda, MT, Archer, L, Smeden, MV, Moons, KGM, Collins, GS, Steyerberg, EW, Wahlich, C, Reitsma, JB, Riley, RD, Calster, BV & Wynants, L 2023, 'Minimal reporting improvement after peer review in reports of COVID-19 prediction models: systematic review', Journal of Clinical Epidemiology, vol. 154, pp. 75-84. https://doi.org/10.1016/j.jclinepi.2022.12.005

Koshiaris, C, Archer, L, Lay-Flurrie, S, Snell, K, Riley, R, Stevens , R, Banerjee, A, Usher-Smith, JA, Clegg, A, Payne , RA, Ogden , M, Hobbs, FDR, McManus, RJ & Sheppard, JP 2023, 'Predicting the risk of acute kidney injury: Derivation and validation of STRATIFY-AKI', British Journal of General Practice . https://doi.org/10.3399/BJGP.2022.0389

Booth, S, Mozumder, SI, Archer, L, Ensor, J, Riley, RD, Lambert, PC & Rutherford, MJ 2023, 'Using temporal recalibration to improve the calibration of risk prediction models in competing risk settings when there are trends in survival over time', Statistics in Medicine. https://doi.org/10.1002/sim.9898

Archer, L, Koshiaris, C, Lay-Flurrie, S, Snell, KIE, Riley, RD, Stevens, R, Banerjee, A, Usher-Smith, JA, Clegg, A, Payne, RA, Hobbs, FDR, McManus, RJ & Sheppard, JP 2022, 'Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study', BMJ, no. 379, e070918. https://doi.org/10.1136/bmj-2022-070918

Riley, RD, Collins, GS, Ensor, J, Archer, L, Booth, S, Mozumder, SI, Rutherford, MJ, van Smeden, M, Lambert, PC & Snell, KIE 2022, 'Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome', Statistics in Medicine, vol. 41, no. 7, pp. 1280-1295. https://doi.org/10.1002/sim.9275

Review article

Salazar de Pablo, G, Iniesta, R, Bellato, A, Caye, A, Dobrosavljevic, M, Parlatini, V, Garcia-Argibay, M, Li, L, Cabras, A, Haider Ali, M, Archer, L, Meehan, AJ, Suleiman, H, Solmi, M, Fusar-Poli, P, Chang, Z, Faraone, SV, Larsson, H & Cortese, S 2024, 'Individualized prediction models in ADHD: a systematic review and meta-regression', Molecular Psychiatry. https://doi.org/10.1038/s41380-024-02606-5

View all publications in research portal