Using a Dose-Finding Benchmark to Quantify the Loss Incurred by Dichotomisation in Phase II Dose-Ranging Studies

Mozgunov, P., Jaki, T. & Paoletti, X., 1/11/2020, In: Biometrical Journal. 62, 7, p. 1717-1729 13 p.

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Using a dose-finding benchmark to quantify the loss incurred by dichotomization in Phase II dose-ranging studies

Mozgunov, P., Jaki, T. & Paoletti, X., 1/11/2020, In: Biometrical Journal. 62, 7, p. 1717-1729 13 p.

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A Benchmark for Dose Finding Studies with Unknown Ordering

Mozgunov, P., Paoletti, X. & Jaki, T., 31/07/2022, In: Biostatistics. 23, 3, p. 721-737 17 p.

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Using an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study

Mozgunov, P., Knight, R., Barnett, H. & Jaki, T., 5/01/2021, In: International Journal of Environmental Research and Public Health. 18, 1, 19 p., 345.

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A dose-finding design for dual-agent trials with patient-specific doses for one agent with application to an opiate detoxification trial

Mozgunov, P., Cro, S., Lingford-Hughes, A., Paterson, L. M. & Jaki, T., 31/03/2022, In: Pharmaceutical Statistics. 21, 2, p. 476-495 20 p.

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Practical implementation of the partial ordering continual reassessment method in a Phase I combination‐schedule dose‐finding trial

Mozgunov, P., Jaki, T., Gounaris, I., Goddemeier, T., Victor, A. & Grinberg, M., 30/12/2022, In: Stat. Med.. 41, 30, p. 5789-5809 21 p.

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Simultaneous confidence regions for multivariate bioequivalence

Pallmann, P. S. & Jaki, T. F., 20/12/2017, In: Statistics in Medicine. 36, 29, p. 4585-4603 19 p.

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Designing and evaluating dose-escalation studies made easy: The MoDEsT web app

Pallmann, P., Wan, F., Mander, A. P., Wheeler, G. M., Yap, C., Clive, S., Hampson, L. V. & Jaki, T., 1/04/2020, In: Clinical Trials. 17, 2, p. 147-156 10 p.

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Multiplicity: discussion points from the PSI multiplicity expert group

Phillips, A., Fletcher, C., Atkinson, G., Channon, E., Douiri, A., Jaki, T., Maca, J., Morgan, D., Roger, J. H. & Terrill, P., 09/2013, In: Pharmaceutical Statistics. 12, 5, p. 255-259 5 p.

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Telmisartan and Insulin Resistance in HIV (TAILoR): protocol for a dose-ranging phase II randomised open-labelled trial of Telmisartan as a strategy for the reduction of insulin resistance in HIV-positive individuals on combination antiretroviral therapy

Pushpakom, S. P., Taylor, C., Kolamunnage-Dona, R., Spowart, C., Vora, J., Garcıa-Finana, M., Kemp, G. J., Whitehead, J., Jaki, T., Khoo, S., Williamson, P. & Pirmohamed, M., 15/10/2015, In: BMJ Open. 5, 10, 13 p., e009566.

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TAILoR (TelmisArtan and InsuLin Resistance in Human Immunodeficiency Virus [HIV]): An Adaptive-design, Dose-ranging Phase IIb Randomized Trial of Telmisartan for the Reduction of Insulin Resistance in HIV-positive Individuals on Combination Antiretroviral Therapy

Pushpakom, S., Kolamunnage-Dona, R., Taylor, C., Foster, T., Spowart, C., García-Fiñana, M., Kemp, G. J., Jaki, T., Khoo, S., Williamson, P. & Pirmohamed, M., 15/05/2020, In: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. 70, 10, p. 2062-2072 11 p.

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Proposing a Core Outcome Set for Physical Activity and Exercise Interventions in People With Rare Neurological Conditions

Ramdharry, G., Buscemi, V., Boaz, A., Dawes, H., Jaki, T., Jones, F., Marsden, J., Paul, L., Playle, R., Randell, E., Robling, M., Rochester, L. & Busse, M., 21/10/2021, (E-pub ahead of print) In: Frontiers in Rehabilitation Sciences. 2, 13 p., 705474.

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Point estimation for adaptive trial designs I: A methodological review

Robertson, D. S., Choodari‐Oskooei, B., Dimairo, M., Flight, L., Pallmann, P. & Jaki, T., 30/01/2023, In: Statistics in Medicine. 42, 2, p. 122-145 24 p.

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A novel measure of drug benefit–risk assessment based on Scale Loss Score

Saint-Hilary, G., Robert, V., Gasparini, M., Jaki, T. F. & Mozgunov, P., 1/09/2019, In: Statistical Methods in Medical Research. 28, 9, p. 2738-2753 16 p.

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Statistical approaches for the determination of cut points in anti-drug antibody bioassays

Schaarschmidt, F., Hofmann, M., Jaki, T., Gruen, B. & Hothorn, L. A., 03/2015, In: Journal of Immunological Methods. 418, p. 84-100 17 p.

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Toward Accelerated Authorization and Access to New Medicines for Juvenile Idiopathic Arthritis

Schanberg, L. E., Ramanan, A. V., De Benedetti, F., Beukelman, T., Eakin, G. S., Del Gaizo, V., Ringold, S., Vesely, R., Schrandt, S., Jaki, T., Bili, A., Chung, J. B., De Bono, S., Douglass, W., Enejosa, J. V., Kanik, K. S., Knobe, K., Kunder, R., Leite-Schnell, J. C., Suehiro, R. M., & 6 othersWong, R. L., Mieszkalski, K. L., Marrow, L. C., Siebenaler, K., Fraulo, E. & Kimura, Y., 1/12/2019, In: Arthritis and Rheumatology. 71, 12, p. 1976-1984 9 p.

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An order restricted multi-arm multi-stage clinical trial design

Serra, A., Mozgunov, P. & Jaki, T., 30/04/2022, In: Statistics in Medicine. 41, 9, p. 1613-1626 14 p.

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What is the expected benefit of patient-centric clinical development in oncology?

Serra, A., Mozgunov, P., Jaki, T. & Rigat, F., 31/07/2022, In: Journal of Biopharmaceutical Statistics. 32, 3, p. 414-426 13 p.

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A Bayesian multi‐arm multi‐stage clinical trial design incorporating information about treatment ordering

Serra, A., Mozgunov, P. & Jaki, T., 20/07/2023, In: Statistics in Medicine. 42, 16, p. 2841-2854 14 p.

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Development of consensus-driven SPIRIT and CONSORT extensions for early phase dose-finding trials: the DEFINE study

Solovyeva, O., Dimairo, M., Weir, C. J., Hee, S. W., Espinasse, A., Ursino, M., Patel, D., Kightley, A., Hughes, S., Jaki, T., Mander, A., Evans, T. R. J., Lee, S., Hopewell, S., Rantell, K. R., Chan, A-W., Bedding, A., Stephens, R., Richards, D., Roberts, L., & 3 othersKirkpatrick, J., de Bono, J. & Yap, C., 5/07/2023, In: BMC Medicine. 21, 1, 246.

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Probabilistic relabelling strategies for the label switching problem in Bayesian mixture models.

Sperrin, M., Jaki, T. & Wit, E., 07/2010, In: Statistics and Computing. 20, 3, p. 357-366 10 p.

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Direct effects testing : a two-stage procedure to test for effect size and variable importance for correlated binary predictors and a binary response.

Sperrin, M. & Jaki, T., 30/10/2010, In: Statistics in Medicine. 29, 24, p. 2544-2556 13 p.

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Recovering Independent Associations in Genetics: A Comparison

Sperrin, M. & Jaki, T., 08/2012, In: Journal of Computational Biology. 19, 8, p. 978–987 10 p.

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Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19

Stallard, N., Hampson, L., Benda, N., Brannath, W., Burnett, T., Friede, T., Kimani, P. K., Koenig, F., Krisam, J., Mozgunov, P., Posch, M., Wason, J., Wassmer, G., Whitehead, J., Williamson, S. F., Zohar, S. & Jaki, T., 1/10/2020, In: Statistics in Biopharmaceutical Research. 12, 4, p. 483-497 15 p.

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A review of statistical updating methods for clinical prediction models

Su, T-L., Jaki, T. F., Hickey, G., Buchan, I. & Sperrin, M., 1/01/2018, In: Statistical Methods in Medical Research. 27, 1, p. 185-197 13 p.

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Tilting the lasso by knowledge-based post-processing

Tharmaratnam, K., Sperrin, M., Jaki, T. F., Reppe, S. & Frigessi, A., 2/09/2016, In: BMC Bioinformatics. 17, 9 p., 344.

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Recurrent events modelling of haemophilia bleeding events

Titman, A., Wolfsegger, M. J. & Jaki, T., 1/03/2021, In: Journal of the Royal Statistical Society: Series C (Applied Statistics). 70, 2, p. 351-371 21 p.

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Using Multilevel Mixtures to Evaluate Intervention Effects in Group Randomized Trials.

Van Horn, M. L., Fagan, A. A., Jaki, T., Brown, E. C., Hawkins, J. D., Arthur, M. W., Abbott, R. D. & Catalano, R. F., 04/2008, In: Multivariate Behavioral Research. 43, 2, p. 289-326 38 p.

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Assessing differential effects: Applying regression mixture models to identify variations in the influence of family resources on academic achievement.

Van Horn, M. L., Jaki, T., Maysn, K., Ramey, S. L., Smith, J. A. & Antaramian, S., 09/2009, In: Developmental Psychology. 45, 5, p. 1298-1313 16 p.

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Not quite normal: Consequences of violating the assumption of normality with regression mixture models

Van Horn, M. L., Smith, J., Fagan, A., Jaki, T., Maysn, K., Hawkins, D., Feaster, D. & Howe, G., 2012, In: Structural Equation Modeling. 19, 2, p. 227-249 23 p.

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Evaluating differential effects using regression interactions and regression mixture models

Van Horn, M. L., Jaki, T., Maysn, K., Howe, G., Feaster, D., Lamont, A. E., George, M. & Kim, M., 08/2015, In: Educational and Psychological Measurement. 75, 4, p. 677-714 38 p.

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Using multilevel regression mixture models to identify level-1 heterogeneity in level-2 effects

Van Horn, M. L., Feng, Y., Kim, M., Lamont, A. E., Feaster, D. & Jaki, T., 2016, In: Structural Equation Modeling. 23, 2, p. 259-269 11 p.

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A Bayesian model to estimate the cutoff and the clinical utility of a biomarker assay

Vradi, E., Jaki, T. F., Vonk, R. & Brannath, W., 1/08/2019, In: Statistical Methods in Medical Research. 28, 8, p. 2538-2556 19 p.

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Model selection based on combined penalties for biomarker identification

Vradi, E., Brannath, W., Jaki, T. & Vonk, R., 4/07/2018, In: Journal of Biopharmaceutical Statistics. 28, 4, p. 735-749 15 p.

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Extrapolation of efficacy and other data to support the development of new medicines for children: a systematic review of methods

Wadsworth, I., Hampson, L. V. & Jaki, T. F., 1/02/2018, In: Statistical Methods in Medical Research. 27, 2, p. 398-413 16 p.

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Clinical drug development in epilepsy revisited: a proposal for a new paradigm streamlined using extrapolation

Wadsworth, I., Jaki, T. F., Sills, G. J., Appleton, R., Cross, J. H., Marson, A. G., Martland, T., McLellan, A., Smith, P. E. M., Pellock, J. M. & Hampson, L. V., 11/2016, In: CNS Drugs. 30, 11, p. 1011-1017 7 p.

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A quantitative framework to inform extrapolation decisions in children

Wadsworth, I., Hampson, L. V., Jaki, T., Sills, G. J., Marson, A. G. & Appleton, R., 1/02/2020, In: Journal of the Royal Statistical Society: Series A Statistics in Society. 183, 2, p. 515-534 20 p.

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Exposure–response modelling approaches for determining optimal dosing rules in children

Wadsworth, I., Hampson, L. V., Bornkamp, B. & Jaki, T., 1/09/2020, In: Statistical Methods in Medical Research. 29, 9, p. 2583-2602 20 p.

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Confidence regions for treatment effects in subgroups in biomarker stratified designs

Wan, F., Kunz, C. U. & Jaki, T. F., 1/01/2019, In: Biometrical Journal. 61, 1, p. 27-39 13 p.

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Subgroup analysis of treatment effects for misclassified biomarkers with time-to-event data

Wan, F., Titman, A. & Jaki, T., 1/11/2019, In: Journal of the Royal Statistical Society: Series C (Applied Statistics). 68, 5, p. 1447-1463 17 p.

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Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial

Wang, Y., Zhang, D., Du, G., Du, R., Zhao, J., Jin, Y., Fu, S., Gao, L., Cheng, Z., Lu, Q., Hu, Y., Luo, G., Wang, K., Lu, Y., Li, H., Wang, S., Ruan, S., Yang, C., Mei, C., Ding, D., & 25 othersWu, F., Tang, X., Ye, X., Ye, Y., Liu, B., Yang, J., Yin, W., Wang, A., Fan, G., Zhou, F., Liu, Z., Gu, X., Xu, J., Shang, L., Zhang, Y., Cao, L., Guo, T., Wan, Y., Qin, H., Jiang, Y., Jaki, T., Hayden, F. G., Horby, P. W., Cao, B. & Wang, C., 16/05/2020, In: The Lancet. p. 1569-1578 10 p.

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Evaluation of the efficacy and safety of intravenous remdesivir in adult patients with severe COVID-19: Study protocol for a phase 3 randomized, double-blind, placebo-controlled, multicentre trial

Wang, Y., Zhou, F., Zhang, D., Zhao, J., Du, R., Hu, Y., Cheng, Z., Gao, L., Jin, Y., Luo, G., Fu, S., Lu, Q., Du, G., Wang, K., Lu, Y., Fan, G., Zhang, Y., Liu, Y., Ruan, S., Liu, W., & 5 othersJaki, T., Hayden, F. G., Horby, P. W., Cao, B. & Wang, C., 24/05/2020, In: Trials. 21, 1, 11 p., 422.

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Optimal design of multi-arm multi-stage trials

Wason, J. & Jaki, T., 30/12/2012, In: Statistics in Medicine. 31, 30, p. 4269-4279 11 p.

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Some recommendations for multi-arm multi-stage trials

Wason, J., Magirr, D., Law, M. & Jaki, T., 04/2016, In: Statistical Methods in Medical Research. 25, 2, p. 716-727 12 p.

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Planning multi-arm screening studies within the context of a drug development programme

Wason, J., Jaki, T. & Stallard, N., 10/09/2013, In: Statistics in Medicine. 32, 20, p. 3424-3435 12 p.

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A review of statistical designs for improving the efficiency of phase II studies in oncology

Wason, J. & Jaki, T., 06/2016, In: Statistical Methods in Medical Research. 25, 3, p. 1010-1021 12 p.

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Practical guidance for planning resources required to support publicly-funded adaptive clinical trials

Wason, J. M. S., Dimairo, M., Biggs, K., Bowden, S., Brown, J., Flight, L., Hall, J., Jaki, T., Lowe, R., Pallmann, P., Pilling, M. A., Snowdon, C., Sydes, M. R., Villar, S. S., Weir, C. J., Wilson, N., Yap, C., Hancock, H. & Maier, R., 10/08/2022, In: BMC Medicine. 20, 1, 12 p., 254.

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How to design a dose-finding study using the continual reassessment method

Wheeler, G. M., Mander, A. P., Bedding, A., Brock, K., Cornelius, V., Grieve, A. P., Jaki, T., Love, S. B., Odondi, L., Weir, C. J., Yap, C. & Bond, S. J., 18/01/2019, In: BMC Medical Research Methodology. 19, 1, 15 p., 18.

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One- and two-stage design proposals for a phase II trial comparing three active treatments with control using an ordered categorical endpoint.

Whitehead, J. & Jaki, T., 28/02/2009, In: Statistics in Medicine. 28, 5, p. 828-847 20 p.

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A novel phase I/IIa design for early phase oncology studies and its application in the evaluation of MK-0752 in pancreatic cancer

Whitehead, J., Thygesen, H., Jaki, T., Davis, S., Halford, S., Turner, H., Cook, N. & Jodrell, D., 15/08/2012, In: Statistics in Medicine. 31, 18, p. 1931-1943 13 p.

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