Analysis of responder-based endpoints: improving power through utilising continuous components

[1]  J. Wason,et al.  Sample size estimation using a latent variable model for mixed outcome co‐primary, multiple primary and composite endpoints , 2019, Statistics in medicine.

[2]  J. Wason,et al.  Employing latent variable models to improve efficiency in composite endpoint analysis , 2019, 1902.07037.

[3]  Elizabeth Gargon,et al.  Choosing important health outcomes for comparative effectiveness research: 4th annual update to a systematic review of core outcome sets for research , 2018, PloS one.

[4]  J. Wason,et al.  Improving the analysis of composite endpoints in rare disease trials , 2018, Orphanet Journal of Rare Diseases.

[5]  P. Williamson,et al.  A taxonomy has been developed for outcomes in medical research to help improve knowledge discovery , 2017, Journal of clinical epidemiology.

[6]  Jane M Blazeby,et al.  Core Outcome Set-STAndards for Development: The COS-STAD recommendations , 2017, PLoS medicine.

[7]  J. Wason,et al.  Improving phase II oncology trials using best observed RECIST response as an endpoint by modelling continuous tumour measurements , 2017, Statistics in medicine.

[8]  J. Wason,et al.  Improving the power of clinical trials of rheumatoid arthritis by using data on continuous scales when analysing response rates: an application of the augmented binary method , 2016, Rheumatology.

[9]  Michael Proschan,et al.  Two‐part test of vaccine effect , 2015, Statistics in medicine.

[10]  Gustavo Leon,et al.  Effects of Fostamatinib, an Oral Spleen Tyrosine Kinase Inhibitor, in Rheumatoid Arthritis Patients With an Inadequate Response to Methotrexate: Results From a Phase III, Multicenter, Randomized, Double‐Blind, Placebo‐Controlled, Parallel‐Group Study , 2014, Arthritis & rheumatology.

[11]  Paula R. Williamson,et al.  Choosing Important Health Outcomes for Comparative Effectiveness Research: A Systematic Review , 2014, PloS one.

[12]  J. Wason,et al.  Using continuous data on tumour measurements to improve inference in phase II cancer studies , 2013, Trials.

[13]  Marcello Gallucci,et al.  A conceptual and empirical examination of justifications for dichotomization. , 2009, Psychological methods.

[14]  Anne-Marie R. Iselin,et al.  A Conceptual and Empirical Examination of Justifications for Dichotomization , 2009 .

[15]  S. Ross.  Composite outcomes in randomized clinical trials: arguments for and against. , 2007, American journal of obstetrics and gynecology.

[16]  Patrick Royston,et al.  The cost of dichotomising continuous variables , 2006, BMJ : British Medical Journal.

[17]  Steven V Owen,et al.  Why carve up your continuous data? , 2005, Research in nursing & health.

[18]  S. Senn.  Disappointing dichotomies , 2003 .

[19]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[20]  Peter A Lachenbruch,et al.  Analysis of data with excess zeros , 2002, Statistical methods in medical research.

[21]  S. Suissa,et al.  Binary regression with continuous outcomes. , 1995, Statistics in medicine.

[22]  S. Suissa,et al.  Binary methods for continuous outcomes: a parametric alternative. , 1991, Journal of clinical epidemiology.

[23]  D. Cox,et al.  An Analysis of Transformations , 1964 .