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Cross-Over Studies --- Data Interpretation, Statistical --- Sample Size --- Statistical Distributions --- Models, statistical --- Clinical Trials as Topic

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Focusing on an integral part of pharmaceutical development, Sample Size Calculations in Clinical Research, Second Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. It provides sample size formulas and procedures for testing equality, noninferiority/superiority, and equivalence. A comprehensive and unified presentation of statistical concepts and practical applications, this book highlights the interactions between clinicians and biostatisticians, includes a well-balanced summary of current and emerging clinical issues, and explores recently developed statistical methodologies for sample size calculation. Whenever possible, each chapter provides a brief history or background, regulatory requirements, statistical designs and methods for data analysis, real-world examples, future research developments, and related references. One of the few books to systematically summarize clinical research procedures, this edition contains new chapters that focus on three key areas of this field. Incorporating the material of this book in your work will help ensure the validity and, ultimately, the success of your clinical studies.

Mathematical statistics --- Clinical medicine --- Drug development --- Sampling (Statistics) --- Sample Size --- Biometry --- Research --- Statistical methods --- methods --- Sample Size. --- Statistical methods. --- methods. --- Sampling (Statistics). --- Clinical medicine - Research - Statistical methods --- Drug development - Statistical methods --- Biometry - methods

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Clinical Trials as Topic --- Sample Size --- Clinical trials --- Sampling (Statistics) --- Etudes cliniques --- Echantillonnage (Statistique) --- methods --- Statistical methods --- Méthodes statistiques --- Méthodes statistiques --- Sample Size. --- methods. --- Clinical trials - Statistical methods --- Clinical Trials as Topic - methods

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Research Design --- Clinical Trials as Topic --- Sample Size --- Statistics as Topic --- Clinical trials --- Etudes cliniques --- Tables. --- Tables. --- Tables. --- Tables. --- Statistical methods --- Tables. --- Méthodes statistiques --- Tables

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Many highly-disaggregated cross-country indicators of institutional quality and the business environment have been developed in recent years. The promise of these indicators is that they can be used to identify specific reform priorities that policymakers and aid donors can target in their efforts to improve institutional and regulatory quality outcomes. Doing so however requires evidence on the partial effects of these many very detailed variables on outcomes of interest, for example, investor perceptions of corruption or the quality of the regulatory environment. In this paper we use Bayesian Model Averaging (BMA) to systematically document the partial correlations between disaggregated indicators and several closely-related outcome variables of interest using two leading datasets: the Global Integrity Index and the Doing Business indicators. We find major instability across outcomes and across levels of disaggregation in the set of indicators identified by BMA as important determinants of outcomes. Disaggregated indicators that are important determinants of one outcome are on average not important determinants of other very similar outcomes. And for a given outcome variable, indicators that are important at one level of disaggregation are on average not important at other levels of disaggregation. These findings illustrate the difficulties in using highly-disaggregated indicators to identify reform priorities.

Access to information --- Algorithms --- Causation --- Correlations --- Econometrics --- Economic activity --- Economic development --- Economic growth --- Economic Theory & Research --- Economists --- Empirical analysis --- Empirical evidence --- Environment --- Environmental Economics & Policies --- Governance --- Governance Indicators --- Instrumental variables --- Linear regression --- Macroeconomics and Economic Growth --- Matrix --- Probabilities --- Probability --- Sample size --- Science and Technology Development --- Standard deviation --- Standard deviations --- Statistical & Mathematical Sciences --- Statistical significance