Introduction To Biostatistics And Research Methods

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

Concise, fast-paced, intensive introduction to clinical research design for students and clinical research professionals Readers will gain sufficient knowledge to pass the United States Medical Licensing Examination part I section in Epidemiology

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.

INTRODUCTION TO BIOSTATISTICS AND RESEARCH METHODOLOGY: A Comprehensive Guide for Health Care Professionals is a precisely written textbook for undergraduate and postgraduate medical, dental, nursing, physiotherapy, clinical psychology and other allied health care profession students. This book contains all the essentials of Biostatistics, research methods, demography and health statistics that lay a good foundation for anyone interested in these subjects. Biostatistics is a biological science and a branch of medicine that involves the processes of collection, collation, analysis, interpretation, presentation of health and health related information that may lead to conclusion and decision making. Biostatistics therefore embraces those techniques pertaining to health and health related sciences. This text book is a comprehensive, user friendly and easy to read resource on Biostatistics and Research Methodology. It is meant for undergraduate and postgraduate medical students and allied biomedical sciences (Dental, Nursing, Psychology, AYUSH, Nutrition, MSc and PhD students). Health researchers, research supervisors and faculty members may find it useful as a reference book.

Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation. The book explains basic statistical concepts with a simple yet rigorous language. The development of ideas is in the context of real applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this book is an introduction to Bayesian analysis. This author discusses basic statistical analysis through a series of biological examples using R and R-Commander as computational tools. The book is ideal for instructors of basic statistics for biologists and other health scientists. The step-by-step application of statistical methods discussed in this book allows readers, who are interested in statistics and its application in biology, to use the book as a self-learning text.

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.

Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields. Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. This extensive update of Introductory Biostatistics, Second Edition includes: • A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs • A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes • R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software • Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts • Notes on Computations sections to provide further guidance on the use of software • A related website that hosts the large data sets presented throughout the book Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.