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Mahajan`S Methods In Biostatistics For Medical Students And Research Workers, Banerjee Bratati


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Автор: Banerjee Bratati
Название:  Mahajan`S Methods In Biostatistics For Medical Students And Research Workers
ISBN: 9789352703104
Издательство: JayPee Brothers India
Классификация:
ISBN-10: 9352703103
Обложка/Формат: Paperback
Страницы: 488
Вес: 0.00 кг.
Дата издания: 2018
Издание: 9 revised edition
Размер: 216 x 140
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Индия
Описание: All chapters have been thoroughly revised and edited in this edition. Basic concepts have been clearly explained in all the chapters and all data have been updated based on Census 2011 and SRS 2017, and all other latest available sources.


The Analysis of Biological Data

Автор: Michael C. Whitlock, Dolph Schluter
Название: The Analysis of Biological Data
ISBN: 1319325343 ISBN-13(EAN): 9781319325343
Издательство: Macmillan Learning
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Цена: 13858.00 р.
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Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.

Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials

Автор: John O`Quigley, Alexia Iasonos, Bjorn Bornkamp
Название: Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials
ISBN: 0367330687 ISBN-13(EAN): 9780367330682
Издательство: Taylor&Francis
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Цена: 11482.00 р.
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Описание: This handbook provides an overview of up-to-date statistical methods required for design, monitoring and analysis for dose finding clinical trials, focusing both on the clinical aspects as well as statistical considerations. This book will not cover statistical methods for Phase II non-dose finding studies or Phase III clinical trials.

Research Methods for the Health Sciences

Автор: Cunningham
Название: Research Methods for the Health Sciences
ISBN: 1118135407 ISBN-13(EAN): 9781118135402
Издательство: Wiley
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Цена: 18683.00 р.
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Описание: Offers an introduction to behavioral and social science research methods in the health sciences. This book provides complete coverage of the process behind these research methods, including information-gathering, decision formation, and results presentation.

Applied Mixed Model Analysis: A Practical Guide

Автор: Jos W. R. Twisk
Название: Applied Mixed Model Analysis: A Practical Guide
ISBN: 110872776X ISBN-13(EAN): 9781108727761
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: This book explains all aspects of mixed model analysis without mathematical jargon, so that non-statisticians can understand the basic principles, analyze their own data, and interpret the results with confidence. Worked examples are analyzed with STATA, and all datasets are available for download, equipping readers to replicate the methods.

Learning Statistics: A Manual for Sociology Students

Автор: David Swanson
Название: Learning Statistics: A Manual for Sociology Students
ISBN: 1609274792 ISBN-13(EAN): 9781609274795
Издательство: Mare Nostrum (Eurospan)
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Цена: 11504.00 р.
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Описание: Helps students learn and retain important statistical concepts. New graduates face numerous challenges when applying statistics in the workplace. This text presents a unique and class-tested set of pedagogical tools that increase learning and retention, and prepare students for real-world application.

Practical Statistics for Medical Research

Автор: Altman
Название: Practical Statistics for Medical Research
ISBN: 0412276305 ISBN-13(EAN): 9780412276309
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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Описание: Primarily aimed at medical researchers, this book aims to provide an understanding of the basic principles that underlie research design, data analysis and the interpretation of results, and to enable the reader to carry out a wide range of statistical analyses.

Medical Statistics: A Practical Approach

Автор: Lee Tze-san
Название: Medical Statistics: A Practical Approach
ISBN: 9811218420 ISBN-13(EAN): 9789811218422
Издательство: World Scientific Publishing
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Цена: 8712.00 р.
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Описание: This book is suitable to be used as a textbook for all levels of students in medical school. It is also useful as a reference book for students interested in the application of biostatistics in medicine. Materials from the Introduction to Chapter 6 are similar to those of an elementary statistical textbook.This book is more modern than the current textbook in medical statistics. In this book, biostatistics and epidemiologic concepts are nicely blended. In contrast to the fallacy of the p-value, it introduces the Bayes factor as a measure of the evidence hidden in the sample data. It illustrates the application of the regression to the mean in medicine. Many epidemiologic concepts such as sensitivity and specificity of the diagnostic test, classification and discrimination, types of bias, etc. are discussed in the book.Chapter 7 on 'Correlation and Regression' includes the concept of regression to the mean, generalized linear (Poisson and Logistic) regression models, and discrimination of new data to belong to which sample data sets. Chapter 8 covers the nonparametric inference, including Kolmogorov and Smirnov test. Via the estimation and hypothesis testing, sample sizes are determined in Chapter 9. Chapter 10 discusses the study of design for collecting sample data, including cohort, cross-sectional, case-control, and clinical trial. In addition, types of bias are expounded as a last section in Chapter 10.Chapter 11 covers in detail the inference on contingency tables, including 2 x 2, two-way, and three-way. Five tests (Pearson, log-odds-ratio, Fisher-Irwin, McNemar, and Ejigou-McHugh) are listed in Section 11.1. Six tests (Pearson, First-order interaction, Yate's linear trend, Stuart's marginal homogeneity, Kendall, and Wilcoxon-Mann-Whitney) are described in Section 11.2. Three tests (Pearson, log-odds-ratio on first-order interaction, Barlett's on second-order interaction) and Simpson's paradox are covered in Section 11.3.Chapter 12 covers analysis of survival data. Two methods (life-table and Kaplan-Meier) are introduced for estimating the survivor function in Section 12.2. Four methods (maximum likelihood, Armitage's preference, Wald's sequential sign, and Armitage's restricted sequential) for comparing two survival curves are covered in Section 12.3. Proportional hazard model and the log-rank test are discussed, respectively, in Section 12.4 and 12.5.In addition, advanced techniques in comparing two survival curves are included in the book such as Armitage's preference method, Armitage's restricted sequential test and Wald's sequential sign test. Also, inference on contingency tables are treated in more detail than other books.

Medical Statistics: A Practical Approach

Автор: Lee Tze-san
Название: Medical Statistics: A Practical Approach
ISBN: 9811217513 ISBN-13(EAN): 9789811217517
Издательство: World Scientific Publishing
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Цена: 17424.00 р.
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Описание: This book is suitable to be used as a textbook for all levels of students in medical school. It is also useful as a reference book for students interested in the application of biostatistics in medicine. Materials from the Introduction to Chapter 6 are similar to those of an elementary statistical textbook.This book is more modern than the current textbook in medical statistics. In this book, biostatistics and epidemiologic concepts are nicely blended. In contrast to the fallacy of the p-value, it introduces the Bayes factor as a measure of the evidence hidden in the sample data. It illustrates the application of the regression to the mean in medicine. Many epidemiologic concepts such as sensitivity and specificity of the diagnostic test, classification and discrimination, types of bias, etc. are discussed in the book.Chapter 7 on 'Correlation and Regression' includes the concept of regression to the mean, generalized linear (Poisson and Logistic) regression models, and discrimination of new data to belong to which sample data sets. Chapter 8 covers the nonparametric inference, including Kolmogorov and Smirnov test. Via the estimation and hypothesis testing, sample sizes are determined in Chapter 9. Chapter 10 discusses the study of design for collecting sample data, including cohort, cross-sectional, case-control, and clinical trial. In addition, types of bias are expounded as a last section in Chapter 10.Chapter 11 covers in detail the inference on contingency tables, including 2 x 2, two-way, and three-way. Five tests (Pearson, log-odds-ratio, Fisher-Irwin, McNemar, and Ejigou-McHugh) are listed in Section 11.1. Six tests (Pearson, First-order interaction, Yate's linear trend, Stuart's marginal homogeneity, Kendall, and Wilcoxon-Mann-Whitney) are described in Section 11.2. Three tests (Pearson, log-odds-ratio on first-order interaction, Barlett's on second-order interaction) and Simpson's paradox are covered in Section 11.3.Chapter 12 covers analysis of survival data. Two methods (life-table and Kaplan-Meier) are introduced for estimating the survivor function in Section 12.2. Four methods (maximum likelihood, Armitage's preference, Wald's sequential sign, and Armitage's restricted sequential) for comparing two survival curves are covered in Section 12.3. Proportional hazard model and the log-rank test are discussed, respectively, in Section 12.4 and 12.5.In addition, advanced techniques in comparing two survival curves are included in the book such as Armitage's preference method, Armitage's restricted sequential test and Wald's sequential sign test. Also, inference on contingency tables are treated in more detail than other books.

Statistical Methods for Healthcare Performance Monitoring

Автор: Bottle
Название: Statistical Methods for Healthcare Performance Monitoring
ISBN: 1482246090 ISBN-13(EAN): 9781482246094
Издательство: Taylor&Francis
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Цена: 14086.00 р.
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Описание:

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it's more crucial than ever to know how well the healthcare system and all its components - from staff member to regional network - are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions.

Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists.

Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.


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