The prevention and treatment of missing data in clinical trials

"Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studie...

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Detalles Bibliográficos
Autor principal: National Research Council (U.S.).
Autores Corporativos: National Research Council (U.S.). Panel on Handling Missing Data in Clinical Trials (-), National Research Council (U.S.). Committee on National Statistics, National Academies Press (U.S.)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Washington, D.C. : National Academies Press 2010.
Edición:1st ed
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009820292106719
Descripción
Sumario:"Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data."--Publisher's description.
Notas:Description based upon print version of record.
Descripción Física:1 online resource (162 p.)
Bibliografía:Includes bibliographical references (p. 115-122).
ISBN:9780309186513
9781282975972
9786612975974
9780309158152