Medical : Biostatistics

Regulatory bodies and medical journals regularly raise their standards in terms of the quality of statistical analyses presented, wanting to ensure statistical methods are not misused leading to wrong conclusions. Following this trend there is a growing need for robust statistics in medical research.  Robust statistics is an extension of classical statistics that specifically takes into account that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable withy respect to changes in the data or model departures. Robust Methods in Biostatistics is the first book on robust methodology to be directed specifically at biostatistics, which would benefit both fields greatly. It allows students, biostatisticians and researchers of all levels easy access by introducing each chapter’s topic with the classical approach before explaining the robust alternatives. more...

Price: $110.00

About 8000 clinical trials are undertaken annually in all areas of medicine, from the treatment of acne to the prevention of cancer. Correct interpretation of the data from such trials depends largely on adequate design and on performing the appropriate statistical analyses. In this book, the statistical aspects of both the design and analysis of trials are described, with particular emphasis on recently developed methods of analysis. more...

Price: $100.10

Drug development is the process of finding and producing therapeutically useful pharmaceuticals, turning them into safe and effective medicine, and producing reliable information regarding the appropriate dosage and dosing intervals. With regulatory authorities demanding increasingly higher standards in such developments, statistics has become an intrinsic and critical element in the design and conduct of drug development programmes. Statistical Issues in Drug Development presents an essential and thought provoking guide to the statistical issues and controversies involved in drug development. . This highly readable second edition has been updated to include:.:.; Comprehensive coverage of the design and interpretation of clinical trials.; Expanded sections on missing data, equivalence, meta-analysis and dose finding.; An examination of both Bayesian and frequentist methods.; A new chapter on pharmacogenomics and expanded coverage of pharmaco-epidemiology and pharmaco-economics.; Coverage of the ICH guidelines, in particular ICH E9, Statistical Principles for Clinical Trials. It is hoped that the book will stimulate dialogue between statisticians and life scientists working within the pharmaceutical industry. The accessible and wide-ranging coverage make it essential reading for both statisticians and non-statisticians working in the pharmaceutical industry, regulatory bodies and medical research institutes. There is also much to benefit undergraduate and postgraduate students whose courses include a medical statistics component. more...

Price: $125.00

Boost Your grades with this illustrated quick-study guide. You will use it from an undergraduate school all the way to graduate school and beyond. Written in concise and clear English. Illustrated with graphs and diagrams. Use your down time to prepare for an exam. Includes Glossary of probability and statistics. Table of Contents. Introduction: History | Conceptual overview | Statistical methods | Specialized disciplines | Software. Probability: Event | Statistical Independence | Interpretations | Classical definition | Permutation | Combination | Random element | Random variable | Random Vector. Rules of Probability: Probability Axioms | Odds | Probability Theory | Bayesian Probability. Expectations and Decisions: Mathematical Expectation | Decision Theory | Chebyshev''s Inequality. Probability Distribution: Discrete Probability Distribution | Bernoulli Distribution | Binomial Distribution | Hypergeometric Distribution | Poisson Distribution | Multinomial Distribution | Standard Deviation | Chi-square Distribution | Student''s t-Distribution. Normal Distribution: Continuous Probability Distribution | Normal Distribution | Infinite Divisibility. Sampling: Simple Random Sample | Sampling Distribution | Central Limit Theorem. Tests of Hypotheses: Null Hypothesis | Statistical Hypothesis Testing | Pearson''s Chi-square test | Student''s t-test | Z-test | General Linear Model | ANOVA | Generating Function | Non-parametric Statistics. Regression: Regression Analysis | Linear Model | Linear Regression | Nonlinear Regression | Kernel Regression | Robust Regression. Correlation: Pearson''s product-moment coefficient | Non-parametric correlation coefficients | Other measures of dependence among random variables | Copulas and correlation | Correlation matrices. Applications: Borel algebra | Cumulative Distribution Function | Probability Mass Function. more...

Price: $19.99

Self-assembly is a process that creates complex heirarchical structures through the statistical exploration of alternative configurations. These processes occur without external intervention. Self-Assembly processes are ubiquitous in nature. Understanding how nature produces self-assembled systems will represent an enormous leap forward in our technological capabilities. Robustness and versatility are some of the most important properties of self-assembling natural systems. Although systems where self-assembly occurs, or which are created by a self-assembling process, are remarkably vaired, some common principles are starting to be discerned. The unifying thread throughout the book is the "Computational Nature of Self-Assembling Systems." more...

Price: $160.00