Riley, Richard D.

A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes

Debray, T. P., Damen, J. A., Riley, R. D., Snell, K., Reitsma, J. B., Hooft, L., Collins, G. S., & Moons, K. G. (2019) · Statistical Methods in Medical Research

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 278

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about “what is likely to happen” should shape clinical practice

Croft, P., Altman, D. G., Deeks, J. J., Dunn, K. M., Hay, A. D., Hemingway, H., LeResche, L., Peat, G., Perel, P., Petersen, S. E., et al. (2015) · BMC Medicine

Clinical Reasoning and Diagnostic SkillsMedicine, History, and Philosophy

Cited by 250

Random effects meta‐analysis: Coverage performance of 95 % confidence and prediction intervals following REML estimation

Partlett, C., & Riley, R. D. (2017) · Statistics in Medicine

Meta-analysis and systematic reviewsStatistical Methods and Bayesian Inference

Cited by 240

Detecting small‐study effects and funnel plot asymmetry in meta‐analysis of survival data: A comparison of new and existing tests

Debray, T. P. A., Moons, K. G. M., & Riley, R. D. (2018) · Research Synthesis Methods

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 212

Stability of clinical prediction models developed using statistical or machine learning methods

Riley, R. D., & Collins, G. S. (2023) · Biometrical Journal

Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare

Cited by 211

Minimum sample size for external validation of a clinical prediction model with a continuous outcome

Archer, L., Snell, K. I. E., Ensor, J., Hudda, M. T., Collins, G. S., & Riley, R. D. (2021) · Statistics in Medicine

Statistical Methods in EpidemiologyStatistical Methods in Clinical Trials

Cited by 198

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice

Willis, B. H., & Riley, R. D. (2017) · Statistics in Medicine

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 171

Exercise treatment effect modifiers in persistent low back pain: an individual participant data meta-analysis of 3514 participants from 27 randomised controlled trials

Hayden, J. A., Wilson, M. N., Stewart, S., Cartwright, J. L., Smith, A. O., Riley, R. D., van Tulder, M., Bendix, T., Cecchi, F., Costa, L. O. P., et al. (2020) · British Journal of Sports Medicine

Musculoskeletal pain and rehabilitationPregnancy-related medical research

Cited by 146

Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small

Riley, R. D., Snell, K. I. E., Martin, G. P., Whittle, R., Archer, L., Sperrin, M., & Collins, G. S. (2021) · Journal of Clinical Epidemiology

Statistical Methods and InferenceStatistical Methods in Epidemiology

Cited by 142

Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review

Dhiman, P., Ma, J., Andaur Navarro, C. L., Speich, B., Bullock, G., Damen, J. A. A., Hooft, L., Kirtley, S., Riley, R. D., Van Calster, B., et al. (2022) · BMC Medical Research Methodology

Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare

Cited by 140

Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?

Jenkins, D. A., Martin, G. P., Sperrin, M., Riley, R. D., Debray, T. P. A., Collins, G. S., & Peek, N. (2021) · Diagnostic and Prognostic Research

Statistical Methods in EpidemiologyMachine Learning in Healthcare

Cited by 131

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models

Andaur Navarro, C. L., Damen, J. A. A., van Smeden, M., Takada, T., Nijman, S. W. J., Dhiman, P., Ma, J., Collins, G. S., Bajpai, R., Riley, R. D., et al. (2023) · Journal of Clinical Epidemiology

Artificial Intelligence in HealthcareStatistical Methods in Epidemiology

Cited by 121

One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information: One-Stage IPD Meta-Analysis Models Must Avoid Ecological Bias

Hua, H., Burke, D. L., Crowther, M. J., Ensor, J., Tudur Smith, C., & Riley, R. D. (2017) · Statistics in Medicine

Meta-analysis and systematic reviewsStatistical Methods in Clinical Trials

Cited by 113

Validation of prediction models in the presence of competing risks: a guide through modern methods

van Geloven, N., Giardiello, D., Bonneville, E. F., Teece, L., Ramspek, C. L., van Smeden, M., Snell, K. I. E., van Calster, B., Pohar-Perme, M., Riley, R. D., et al. (2022) · BMJ

Statistical Methods in EpidemiologyStatistical Methods and Inference

Cited by 106

Methodology over metrics: current scientific standards are a disservice to patients and society

Van Calster, B., Wynants, L., Riley, R. D., van Smeden, M., & Collins, G. S. (2021) · Journal of Clinical Epidemiology

Meta-analysis and systematic reviewsAcademic Publishing and Open Access

Cited by 105

Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE

Ensor, J., Riley, R. D., Moore, D., Snell, K. I. E., Bayliss, S., & Fitzmaurice, D. (2016) · BMJ Open

Venous Thromboembolism Diagnosis and ManagementBlood Coagulation and Thrombosis Mechanisms

Cited by 84

Risk of bias of prognostic models developed using machine learning: a systematic review in oncology

Dhiman, P., Ma, J., Andaur Navarro, C. L., Speich, B., Bullock, G., Damen, J. A. A., Hooft, L., Kirtley, S., Riley, R. D., Van Calster, B., et al. (2022) · Diagnostic and Prognostic Research

Statistical Methods in EpidemiologyMachine Learning in Healthcare

Cited by 79

Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review

Dhiman, P., Ma, J., Andaur Navarro, C. L., Speich, B., Bullock, G., Damen, J. A. A., Hooft, L., Kirtley, S., Riley, R. D., Van Calster, B., et al. (2023) · Journal of Clinical Epidemiology

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 41

Study protocol: differential effects of diet and physical activity based interventions in pregnancy on maternal and fetal outcomes—individual patient data (IPD) meta-analysis and health economic evaluation.

Ruifrok, A. E., Rogozinska, E., van Poppel, M. N., Rayanagoudar, G., Kerry, S., de Groot, C. J., Yeo, S., Molyneaux, E., McAuliffe, F. M., Poston, L., et al. (2014) · Systematic Reviews

Gestational Diabetes Research and ManagementObesity, Physical Activity, Diet

Cited by 33

Open science practices need substantial improvement in prognostic model studies in oncology using machine learning

Collins, G. S., Whittle, R., Bullock, G. S., Logullo, P., Dhiman, P., de Beyer, J. A., Riley, R. D., & Schlussel, M. M. (2024) · Journal of Clinical Epidemiology

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 21

Up Front and Open? Shrouded in Secrecy? Or Somewhere in Between? A Meta-Research Systematic Review of Open Science Practices in Sport Medicine Research

Bullock, G. S., Ward, P., Impellizzeri, F. M., Kluzek, S., Hughes, T., Hillman, C., Waterman, B. R., Danelson, K., Henry, K., Barr, E., et al. (2023) · Journal of Orthopaedic & Sports Physical Therapy

Academic Publishing and Open AccessResearch Data Management Practices

Cited by 15