Sperrin, Matthew
Manchester Academic Health Science Centre · University of Manchester
10 papers on CoChatORCID 0000-0002-5351-9960
Most cited papers
- Verified
Evaluation of clinical prediction models (part 1): from development to external validation
Collins, G. S., Dhiman, P., Ma, J., Schlussel, M. M., Archer, L., Van Calster, B., Harrell, F. E., Martin, G. P., Moons, K. G. M., van Smeden, M., et al. (2024) · BMJ
Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare
Cited by 798
- Verified
Framework to construct and interpret latent class trajectory modelling
Lennon, H., Kelly, S., Sperrin, M., Buchan, I., Cross, A. J., Leitzmann, M., Cook, M. B., & Renehan, A. G. (2018) · BMJ Open
Statistical Methods in EpidemiologyPsychometric Methodologies and Testing
Cited by 419
- Verified
Outcome-sensitive multiple imputation: a simulation study
Kontopantelis, E., White, I. R., Sperrin, M., & Buchan, I. (2017) · BMC Medical Research Methodology
Statistical Methods and Bayesian InferenceAdvanced Causal Inference Techniques
Cited by 205
- Verified
A review of statistical updating methods for clinical prediction models
Su, T.-L., Jaki, T., Hickey, G. L., Buchan, I., & Sperrin, M. (2018) · Statistical Methods in Medical Research
Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare
Cited by 147
- Verified
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
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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
- Verified
Human activity recognition from inertial sensor time-series using batch normalized deep LSTM recurrent networks
Zebin, T., Sperrin, M., Peek, N., & Casson, A. J. (2018) · 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Context-Aware Activity Recognition SystemsGait Recognition and Analysis
Cited by 107
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Imputation and missing indicators for handling missing data in the development and deployment of clinical prediction models: A simulation study
Sisk, R., Sperrin, M., Peek, N., van Smeden, M., & Martin, G. P. (2023) · Statistical Methods in Medical Research
Statistical Methods and Bayesian InferenceStatistical Methods in Epidemiology
Cited by 99
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Body mass index relates weight to height differently in women and older adults: serial cross-sectional surveys in England (1992–2011)
Sperrin, M., Marshall, A. D., Higgins, V., Renehan, A. G., & Buchan, I. E. (2016) · Journal of Public Health
Obesity, Physical Activity, DietBody Composition Measurement Techniques
Cited by 83
- Verified
Investigation of the robustness of two models for assessing synergy in pre‐clinical drug combination studies
Whitehead, A., Su, T., Thygesen, H., Sperrin, M., & Harbron, C. (2013) · Pharmaceutical Statistics
Statistical Methods in Clinical TrialsOptimal Experimental Design Methods
Cited by 6
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