Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research

<p>Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study. </p><p></p><p><strong>Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research</strong> explains how to determine sample size for studies with correlated outcomes which are widely implemented in medical epidemiological and behavioral studies.</p><p></p><p>The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration analysis and sample size requirement.</p><p></p><p>Addressing the overarching theme of sample size determination for correlated outcomes this book provides a useful resource for biostatisticians clinical investigators epidemiologists and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.</p>