| Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues GL Hickey, P Philipson, A Jorgensen, R Kolamunnage-Dona BMC medical research methodology 16, 1-15, 2016 | 216 | 2016 |
| Evaluating the quality of research into a single prognostic biomarker: a systematic review and meta-analysis of 83 studies of C-reactive protein in stable coronary artery disease H Hemingway, P Philipson, R Chen, N Fitzpatrick, J Damant, M Shipley, ... PLoS Medicine 7 (6), 2010 | 184 | 2010 |
| Joint modelling of longitudinal and competing risks data PR Williamson, R Kolamunnage‐Dona, P Philipson, AG Marson Statistics in medicine 27 (30), 6426-6438, 2008 | 138 | 2008 |
| joineR: Joint modelling of repeated measurements and time-to-event data P Philipson, P Diggle, I Sousa, R Kolamunnage-Dona, P Williamson, ... Comprehensive R Archive Network, 2012 | 111* | 2012 |
| South Asians and coronary disease: is there discordance between effects on incidence and prognosis? MJS Zaman, P Philipson, R Chen, A Farag, M Shipley, MG Marmot, ... Heart 99 (10), 729-736, 2013 | 104 | 2013 |
| joineRML: a joint model and software package for time-to-event and multivariate longitudinal outcomes GL Hickey, P Philipson, A Jorgensen, R Kolamunnage-Dona BMC medical research methodology 18, 1-14, 2018 | 80 | 2018 |
| Measuring the impact of research: Lessons from the UK’s Research Excellence Framework 2014 G Chowdhury, K Koya, P Philipson PloS one 11 (6), e0156978, 2016 | 68 | 2016 |
| Joint models of longitudinal and time-to-event data with more than one event time outcome: a review GL Hickey, P Philipson, A Jorgensen, R Kolamunnage-Dona The international journal of biostatistics 14 (1), 20170047, 2018 | 42 | 2018 |
| A comparison of joint models for longitudinal and competing risks data, with application to an epilepsy drug randomized controlled trial GL Hickey, P Philipson, A Jorgensen, R Kolamunnage-Dona Journal of the Royal Statistical Society Series A: Statistics in Society 181 …, 2018 | 41 | 2018 |
| A condition-based maintenance policy for continuously monitored multi-component systems with economic and stochastic dependence JL Oakley, KJ Wilson, P Philipson Reliability Engineering & System Safety 222, 108321, 2022 | 40 | 2022 |
| Reducing inequalities in care for patients with non-malignant diseases: insights from a realist evaluation of an integrated palliative care pathway SM Dalkin, M Lhussier, P Philipson, D Jones, W Cunningham Palliative medicine 30 (7), 690-697, 2016 | 37 | 2016 |
| Comparative review of methods for handling drop-out in longitudinal studies P Philipson, WK Ho, R Henderson Statistics in Medicine 27 (30), 6276–6298, 2008 | 35 | 2008 |
| Faster Monte Carlo estimation of joint models for time-to-event and multivariate longitudinal data P Philipson, GL Hickey, MJ Crowther, R Kolamunnage-Dona Computational Statistics & Data Analysis 151, 107010, 2020 | 24 | 2020 |
| Translational phases of evidence in a prognostic biomarker: a systematic review and meta-analysis of natriuretic peptides and the prognosis of stable coronary disease S Sutaria, P Philipson, N Fitzpatrick, K Abrams, S Moreno, A Timmis, ... Heart 98, 615-622, 2012 | 20 | 2012 |
| Higher education outreach: Examining key challenges for academics M Johnson, E Danvers, T Hinton-Smith, K Atkinson, G Bowden, J Foster, ... British Journal of Educational Studies 67 (4), 469-491, 2019 | 18 | 2019 |
| Random-effects models for joint analysis of repeated-measurement and time-to-event outcomes P Diggle, R Henderson, P Philipson Longitudinal data analysis, 349-366, 2009 | 18 | 2009 |
| Open communication strategies between a triad of ‘experts’ facilitates death in usual place of residence: A realist evaluation S Dalkin, M Lhussier, D Jones, P Phillipson, W Cunningham Palliative medicine, 0269216318757132, 2018 | 15 | 2018 |
| A fast approximate EM algorithm for joint models of survival and multivariate longitudinal data J Murray, P Philipson Computational Statistics & Data Analysis 170, 107438, 2022 | 14 | 2022 |
| On the ranking of test match batsmen RJ Boys, PM Philipson Journal of the Royal Statistical Society, Series C, 2018 | 14 | 2018 |
| Mid-regional proadrenomedullin (MR-proADM), C-reactive protein (CRP) and other biomarkers in the early identification of disease progression in patients with COVID-19 in the … N Moore, R Williams, M Mori, B Bertolusso, G Vernet, J Lynch, P Philipson, ... Journal of Clinical Pathology 76 (6), 400-406, 2023 | 13 | 2023 |
Ruwanthi Kolamunnage-DonaProfessor of Medical Statistics, University of LiverpoolVerifierad e-postadress på liverpool.ac.uk
