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"Pharmaceutical Research Methodology and Bio-Statistics: Theory and Practice" is aimed in understanding the fundamental concepts of developing a research bent of mind by careful planning, execution, collection of data and analyzing for statistical significance. The book is aimed at B. Pharm, Pharm D, Pharm D (PB), M. Pharm, allied course students, researchers at the academic and industry levels, Ph. D scholars, policy makers, regulators etc. Key Features: - Distinguishing statistics and bio-statistics - How to identify a problem, plan for research and execute the idea - Chemical abstract literature search - Anatomy of a research paper - Compare and contrast of research proposal, research report, research paper, patent document, synopsis - Concept of meta-analysis to resolve research ambiguities - Data collection, cleansing, presenting - How to overcome missing data - Introduction to Probability, Permutations and Combinations - Parametric distributions - binomial, poisson, normal, chi-square, student 't', F distributions - Extra information on Bernoulli Distribution and Chebyshev's Theorem - Role of Type I and Type II errors, Power, sample size, confidence level, confidence interval, confidence limits - How to judge whether data upon analysis is statistical significant or not - Developing hypothesis as null, alternate and how to draw conclusion after conducting suitable statistical test - Non-parametric statistical test - Run, Sign, Wilcoxon Signed rank, Wilcoxon rank sum tests - Parametric, Non-parametric ANOVAs (1-way with multiple comparisons, 2-way, cross over, 3-way) - Step wise Parametric and non-parametric problem solving - Applications of linear regression and correlation coef ficient relating to pharmaceuticals - Appended with Multi-linear Regression Analysis (Mathematical and Excel Calculation)
This book contains 13 chapters. They include Basic concepts, Probability and Probability distributions, Tests of Hypotheses, Chi-square test, Analysis of Variance, Experimental Designs, Non-Parametric statistics and Research Methodology. All chapters are written in a lucid manner so that students can understand easily without much mathematical background. Live examples are added for illustration purpose for all the statistical methods. In some cases more than one example is added for wide applicability of the statistical tools. SPSS data analysis procedure is included for most of the popular statistical methods by giving an example in each case. Research Methodology chapter is useful to the P.G students for undertaking research for their dissertation work. This book is also intended to serve as a text book for Pharmacy students at U.G. and P.G. level
A respected introduction to biostatistics, thoroughly updated and revised The first edition of Biostatistics: A Methodology for the Health Sciences has served professionals and students alike as a leading resource for learning how to apply statistical methods to the biomedical sciences. This substantially revised Second Edition brings the book into the twenty-first century for today’s aspiring and practicing medical scientist. This versatile reference provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and levels of proficiency. Written with an eye toward the use of computer applications, the book examines the design of medical studies, descriptive statistics, and introductory ideas of probability theory and statistical inference; explores more advanced statistical methods; and illustrates important current uses of biostatistics. New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selected problems and solutions, and examples from such current topics as HIV/AIDS, this is a thoroughly current, comprehensive introduction to the field.
Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods. Use of SAS and Stata statistical software is illustrated in full, including how to interpret results. Focusing on statistical models without all the theory, the book is complete with exercises, case studies, take-away points, and data sets. Readers will be able to maximize their statistical abilities in hypothesis testing, data interpretation, and application while also learning when and how to consult a biostatistician. This book will be an invaluable tool for students and clinical and public health practitioners.
Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials. - Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines - Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health - Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.
This book is specifically geared towards students in pharmacy programs and covers all the essential topics in research methodology, from the basics of research design to statistical analysis. It also includes a section on biostatistics, which is essential for pharmaceutical research. This book is a more general introduction to research methods, but it still has a lot to offer students in pharmacy programs. It covers a wide range of topics, including research design, data collection, data analysis, and scientific writing. This book will be a great resource for any student in a Masters in Pharmacy and Bachelors in Pharmacy programme.
The last decade has produced many textbooks on Biostatistics, with varying emphasis and degrees of mathematical complexity. This book has stood the test of time and continues to enjoy wide acceptance among students of all health and allied professions, other students and even qualified health investigators, who find it practical, simple and yet precise. This fully updated and thoroughly revised Fifth Edition, while retaining the fundamental concepts, acquaints the reader with the advances in the subject. The book explains the concepts involved in arriving at the sample size and also a quick solution to the estimation of sample size. Survival analysis and log-rank test are illustrated with examples. The essentials of Chi square tests are simplified and presented. Two-way analysis of variance (ANOVA) is explained with two examples, with and without interaction term. The chapters on Research Methods, Interventional Studies and Observational Studies provide step-by-step guide to plan and carry out quality research. Questions given in each chapter will help the learner to gauge the level of understanding of the principles and applications. Clues to the use of computer packages are provided whenever necessary. Intended for undergraduate and postgraduate medical students as well as for nursing and paramedical students, the book will also be immensely useful to medical/health faculty and researchers in the field of Biostatistics. KEY FEATURES : A new chapter on Sample Size Determination Several new sections Extensive revision of practically all chapters Provision of new examples Chapter-end exercises
Learn to evaluate and apply statistics in medicine, medical research, and all health-related fields A Doody's Core Title for 2023! Basic & Clinical Biostatistics provides medical students, researchers, and practitioners with the knowledge needed to develop sound judgment about data applicable to clinical care. This fifth edition has been updated throughout to deliver a comprehensive, timely introduction to biostatistics and epidemiology as applied to medicine, clinical practice, and research. Particular emphasis is on study design and interpretation of results of research. The book features “Presenting Problems” drawn from studies published in the medical literature, end-of-chapter exercises, and a reorganization of content to reflect the way investigators ask research questions. To facilitate learning, each chapter contain a set of key concepts underscoring the important ideas discussed. Features: Key components include a chapter on survey research and expanded discussion of logistic regression, the Cox model, and other multivariate statistical methods Extensive examples illustrate statistical methods and design issues Updated examples using R, an open source statistical software package Expanded coverage of data visualization, including content on visual perception and discussion of tools such as Tableau, Qlik and MS Power BI Sampling and power calculations imbedded with discussion of the statistical model Updated content, examples, and data sets throughout
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 taught. Moreover, even when EBM and clinical cancer research are discussed, they are presented in a theoretical fashion, mostly focused on formulas and numbers, rather than on clinical application for a proper literature appraisal. Addressing that gap, this book discusses more practical aspects of clinical research and biostatistics in oncology, instead of relying only on mathematical formulas and theoretical considerations. Methods and Biostatistics in Oncology will help readers develop the skills they need to understand the use of research on everyday oncology clinical practice for study design and interpretation, as well to demystify the use of EBM in oncology.