Biography
Lucinda completed a BSc Mathematics followed by an MSc Operational Research and Applied Statistics, both at Cardiff University.
Lucinda previously held a post in the Institute of Applied Health Research at the University of Birmingham, where she was employed under an NIHR Research Methods Fellowship. During this time, she completed an MPH in Public Health and worked on projects focused within the fields of prognostic and diagnostic research.
She continues to work in the field of prognosis research and is completing her PhD part time in the application and development of statistical methods for prognostic modelling.
Research and scholarship
Lucinda's research interests lie in the application and development of statistical methods for prognostic modelling.
Selected Publications
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What exactly is meant by ‘‘Loss of Domain’’ for ventral hernia? Systematic Review of Definitions. World Journal of Surgery, 396-404, vol. 43(2). doi> link> full text>2018.
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Development and validation of a combined metabolic and immune prognostic classifier for head and neck cancer. Journal of Clinical Oncology, 6049, vol. 36. doi>2018.
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Development and validation of a combined metabolic and immune prognostic classifier for head and neck cancer.
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How accurately do trialists pre-specify sample sizes for test evaluation trials? The experience in NIHR funded trials in the HTA and EME programmes.
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Minimum sample size for external validation of a clinical prediction model with a continuous outcome. Stat Med, 133-146, vol. 40(1). link> doi> full text>2021.
Full Publications Listshow
Journal Articles
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What exactly is meant by ‘‘Loss of Domain’’ for ventral hernia? Systematic Review of Definitions. World Journal of Surgery, 396-404, vol. 43(2). doi> link> full text>2018.
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Development and validation of a combined metabolic and immune prognostic classifier for head and neck cancer. Journal of Clinical Oncology, 6049, vol. 36. doi>2018.
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Minimum sample size for external validation of a clinical prediction model with a continuous outcome. Stat Med, 133-146, vol. 40(1). link> doi> full text>2021.
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Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small. J Clin Epidemiol, 88-96, vol. 132. link> doi> full text>2020.
Other
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Development and validation of a combined metabolic and immune prognostic classifier for head and neck cancer.
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How accurately do trialists pre-specify sample sizes for test evaluation trials? The experience in NIHR funded trials in the HTA and EME programmes.
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Selecting biomarkers for evaluation in a prognostic systematic review: a case study from Crohn’s disease.