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Assessing Quality of Life in Clinical Trials
Researchers in all clinical fields are fully aware of the importance of Quality of Life measurements in judging the efficacy of a given treatment. Psychological criteria play an important role in this evaluation. Assessment of Quality of Life in Clinical Trials: methods and practice explores the current state of the art and illustrates the benefits and potential of health related quality of life assessment in clinical trials. It covers a wide range of analytical issues, emphasizing new and innovative approaches that are of practical and clinical importance.
Design and Analysis of Quality of Life Studies in Clinical Trials
Design Principles and Analysis Techniques for HRQoL Clinical TrialsSAS, R, and SPSS examples realistically show how to implement methods Focusing on longitudinal studies, Design and Analysis of Quality of Life Studies in Clinical Trials, Second Edition addresses design and analysis aspects in enough detail so that readers can apply statistical meth
Methods and Biostatistics in Oncology
This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach. Evidence-based medicine (EBM) has been in vogue in the last few decades, particularly in rapidly advancing fields such as oncology. This approach has been used to support decision-making processes worldwide, sparking new clinical research and guidelines on clinical and surgical oncology. Clinical oncology research has many peculiarities, including specific study endpoints, a special focus on survival analyses, and a unique perspective on EBM. However, during medical studies and in general practice, these topics are barely...
Annual Progress in Child Psychiatry and Child Development, 1988
The 21st annual edition of a respected review. Covers developmental studies, child-care and methodological issues, temperament, clinical issues, autism, physical illness, child abuse, adolescence. Not indexed. Annotation copyright Book News, Inc. Portland, Or.
Statistical Analysis of Gene Expression Microarray Data
Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies
Patient-Centered Measurement
Patients often are asked to fill out questionnaires before or after going to the doctor's office or hospital. What is the point of these questionnaires? Why do the questions often seem irrelevant? Does it matter if patients fill them out or ignore them? This book addresses these questions while also providing historical context about how these questionnaires became so popular. These questionnaires, which philosopher Leah M. McClimans calls 'Patient-Centered Measures' have a fascinating history that combines the contemporary emphasis in medical ethics on patient-centered care with the contemporary preoccupation with evidence-based medicine (the idea that medical decisions should be based on empirical evidence). Patient-centered measures sit between these two concerns and thus serve as an excellent example of a medical technology for the twenty-first century.
Evidence-Based Outcome Research
This edited volume provides both conceptual and practical information for conducting and evaluating evidence-based outcome studies. It encompasses psychotherapy research for traditional mental health disorders (eg. depression, anxiety), as well as psychosocial-based treatments provided to medical patient populations to have impact either on the disease process itself (pain, cardiovascular risk) or to improve the quality of life of such individuals. This is a hands-on book, whose major emphasis is on the practical nuts-and-bolts implementation of psychosocial-based RCTs from conception to completion.
Measurement Error and Misclassification in Statistics and Epidemiology
Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments examines the consequences and Bayesian remedies in those cases where the explanatory variable cannot be measured with precision. The author explores both measurement error in continuous variables and misclassification in discrete variables, and shows how Bayesian methods might be used to allow for mismeasurement. A broad range of topics, from basic research to more complex concepts such as "wrong-model" fitting, make this a useful research work for practitioners, students and researchers in biostatistics and epidemiology."
Generalized Latent Variable Modeling
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many ...
