Sample Size Choice
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Sampling Essentials
"Designed for the nontechnical researcher or generalist, this text provides the reader with a good understanding of sampling principles. The author gives a detailed, nontechnical description and guidelines with limited presentation of formulas to help reach basic research decisions, such as when to choose a sample vs. census and nonprobability vs. probability sampling as well as how to select sample size and sample type. Intended for the social and behavioral sciences, Sampling Essentials is appropriate for undergraduate students, graduate students, and research practitioners"--
Methods and Applications of Sample Size Calculation and Recalculation in Clinical Trials
This book provides an extensive overview of the principles and methods of sample size calculation and recalculation in clinical trials. Appropriate calculation of the required sample size is crucial for the success of clinical trials. At the same time, a sample size that is too small or too large is problematic due to ethical, scientific, and economic reasons. Therefore, state-of-the art methods are required when planning clinical trials. Part I describes a general framework for deriving sample size calculation procedures. This enables an understanding of the common principles underlying the numerous methods presented in the following chapters. Part II addresses the fixed sample size design, where the required sample size is determined in the planning stage and is not changed afterwards. It covers sample size calculation methods for superiority, non-inferiority, and equivalence trials, as well as comparisons between two and more than two groups. A wide range of further topics is discussed, including sample size calculation for multiple comparisons, safety assessment, and multi-regional trials. There is often some uncertainty about the assumptions to be made when calculating the sample size upfront. Part III presents methods that allow to modify the initially specified sample size based on new information that becomes available during the ongoing trial. Blinded sample size recalculation procedures for internal pilot study designs are considered, as well as methods for sample size reassessment in adaptive designs that use unblinded data from interim analyses. The application is illustrated using numerous clinical trial examples, and software code implementing the methods is provided. The book offers theoretical background and practical advice for biostatisticians and clinicians from the pharmaceutical industry and academia who are involved in clinical trials. Covering basic as well as more advanced and recently developed methods, it is suitable for beginners, experienced applied statisticians, and practitioners. To gain maximum benefit, readers should be familiar with introductory statistics. The content of this book has been successfully used for courses on the topic.
Sampling and Choosing Cases in Qualitative Research
All qualitative researchers sample, yet methods of sampling and choosing cases have received relatively little attention compared to other qualitative methods. This innovative book critically evaluates widely used sampling strategies, identifying key theoretical assumptions and considering how empirical and theoretical claims are made from these diverse methods. Nick Emmel presents a groundbreaking reworking of sampling and choosing cases in qualitative research. Drawing on international case studies from across the social sciences he shows how ideas drive choices, how cases are used to work out the relation between ideas and evidence, and why it is not the size of a sample that matters, it is how cases are used to interpret and explain that counts. Fresh, dynamic and timely, this book is essential reading for researchers and postgraduate students engaging with sampling and realism in qualitative research.