Biostatistics for Clinical and Public Health Research

2. Auflage 2025
ISBN: 978-1-032-51307-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 600 Seiten, Format (B × H): 174 mm x 246 mm, Gewicht: 453 g

The new edition of Biostatistics for Clinical and Public Health Research is the only introductory workbook to provide not only a concise overview of key statistical concepts but also step-by-step guidance on how to apply these through a range of software packages, including R, SAS, and Stata.

Providing a comprehensive survey of essential topics - including probability, diagnostic testing, probability distributions, estimation, hypothesis testing, correlation, regression, and survival analysis – each chapter features a detailed summary of the topic at hand, followed by examples to show readers how to conduct analysis and interpret the results. Also including exercises and solutions, case studies, take-away points, and data sets (Excel, SAS, and Stata formats), the new edition now includes a chapter on data literacy and data ethics, as well as examples drawn from the COVID-19 pandemic.

 Ideally suited to accompany either a course or as support for independent study, this book will be an invaluable tool for both students of biostatistics and clinical or public health practitioners.

Zielgruppe

Postgraduate, Professional Reference, Professional Training, and Undergraduate Advanced

Autoren/Hrsg.

Goodman, Melody S.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Krankenhausmanagement, Praxismanagement
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Public Health, Gesundheitsmanagement, Gesundheitsökonomie, Gesundheitspolitik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Gesundheitssystem, Gesundheitswesen

Inhaltsverzeichnis

Introduction.  1:Descriptive Statisticss. Lab A1:Introduction to R/RStudio.  Lab A2:Introduction to SAS.  Lab A3:Introduction to Stata.  2:Probability.  3:Diagnostic Testing.  4:Discrete Probability Distributions.  5:Continuous Probability Distributions.  Lab B:Probability Distributions.  6:Estimation.  7:One-Sample Hypothesis Testing.   Lab C:One-Sample Hypothesis Testing Including Power and Sample Size.  8:Two-Sample Hypothesis Testing.  9:Nonparametric Hypothesis Testing.  Lab D:Two Sample and Nonparametric Hypothesis Testing.  10:Hypothesis Testing for Categorical Data.  11:One-Way Analysis of Variance (ANOVA).  12:Correlation.  13:Linear Regression.  14:Logistic Regression.  15:Survival Analysis.  Lab E:Data Analysis Project.  16:The Importance of Data Literacy and Data Ethics.

Über Autor(innen)

Melody S. Goodman is a professor in the Department of Biostatistics at New York University School of Global Public Health. She is a biostatistician with experience in study design, developing survey instruments, data collection, data management, and data analysis for public health and clinical research projects. She has taught introductory biostatistics for masters of public health and medical students for over 15 years at multiple institutions (Stony Brook University School of Medicine, Washington University in St. Louis School of Medicine, New York University School of Global Public Health).