Regression Methods in Biostatistics

Regression Methods in Biostatistics
Author: Eric Vittinghoff
Publisher: Springer Science & Business Media
Total Pages: 526
Release: 2012-03-06
Genre: Medical
ISBN: 1461413532

Download Regression Methods in Biostatistics Book in PDF, Epub and Kindle

This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.

Regression Methods in Biostatistics

Regression Methods in Biostatistics
Author: Eric Vittinghoff
Publisher:
Total Pages: 15
Release: 2004
Genre: Medicine research-Statistical methods
ISBN:

Download Regression Methods in Biostatistics Book in PDF, Epub and Kindle

Bayesian and Frequentist Regression Methods

Bayesian and Frequentist Regression Methods
Author: Jon Wakefield
Publisher: Springer Science & Business Media
Total Pages: 700
Release: 2013-01-04
Genre: Mathematics
ISBN: 1441909257

Download Bayesian and Frequentist Regression Methods Book in PDF, Epub and Kindle

Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.

Regression Methods in Biostatistics

Regression Methods in Biostatistics
Author: Eric Vittinghoff
Publisher: Springer Science & Business Media
Total Pages: 346
Release: 2006-03-30
Genre: Mathematics
ISBN: 0387272550

Download Regression Methods in Biostatistics Book in PDF, Epub and Kindle

Here is a unified, readable introduction to multipredictor regression methods in biostatistics, including linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, and generalized linear models for counts and other outcomes. The authors describe shared elements in methods for selecting, estimating, checking, and interpreting each model, and show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.

Biostatistics and Computer-based Analysis of Health Data using Stata

Biostatistics and Computer-based Analysis of Health Data using Stata
Author: Christophe Lalanne
Publisher: Elsevier
Total Pages: 136
Release: 2016-09-06
Genre: Computers
ISBN: 0081010842

Download Biostatistics and Computer-based Analysis of Health Data using Stata Book in PDF, Epub and Kindle

This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands. Provides detailed examples of the use of Stata for common biostatistical tasks in medical research Features a work program structured around the four previous chapters and a series of practical exercises with commented corrections Includes an appendix to help the reader familiarize themselves with additional packages and commands Focuses on the practice of biostatistical methods that are essential to clinical research, epidemiology, and analysis of biomedical data

Regression Analysis of Count Data

Regression Analysis of Count Data
Author: Adrian Colin Cameron
Publisher: Cambridge University Press
Total Pages: 597
Release: 2013-05-27
Genre: Business & Economics
ISBN: 1107014166

Download Regression Analysis of Count Data Book in PDF, Epub and Kindle

This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.

Applications of Regression Models in Epidemiology

Applications of Regression Models in Epidemiology
Author: Erick Suárez
Publisher: John Wiley & Sons
Total Pages: 276
Release: 2017-02-28
Genre: Mathematics
ISBN: 1119212480

Download Applications of Regression Models in Epidemiology Book in PDF, Epub and Kindle

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUÁREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. PÉREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MARTÍNEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.

Statistical Methods for the Analysis of Biomedical Data

Statistical Methods for the Analysis of Biomedical Data
Author: Robert F. Woolson
Publisher: John Wiley & Sons
Total Pages: 714
Release: 2011-01-25
Genre: Medical
ISBN: 111803130X

Download Statistical Methods for the Analysis of Biomedical Data Book in PDF, Epub and Kindle

Dieser Band behandelt eine Reihe statistischer Themen, die bei der Analyse biologischer und medizinischer Daten allgemein Anwendung finden. Diese 2. Auflage wurde komplett überarbeitet, aktualisiert und erweitert. Einige Kapitel sind neu hinzugekommen, u.a. zur multiplen linearen Regression in der biomedizinischen Forschung. Der Stoff ist so gegliedert, dass der Leser den Text unabhängig von der jeweiligen statistischen Methode leicht nach Problemstellungen durchsuchen kann. Mit zahlreichen durchgearbeiteten Beispielen, die detaillierte Lösungsangaben zu Problemen aus der Praxis liefern.

Handbook of Regression and Modeling

Handbook of Regression and Modeling
Author: Daryl S. Paulson
Publisher: CRC Press
Total Pages: 522
Release: 2006-12-19
Genre: Mathematics
ISBN: 1420017381

Download Handbook of Regression and Modeling Book in PDF, Epub and Kindle

Carefully designed for use by clinical and pharmaceutical researchers and scientists, Handbook of Regression Analysis and Modeling explores statistical methods that have been adapted into biological applications for the quickly evolving field of biostatistics. The author clearly delineates a six-step method for hypothesis testing using data that mi