biostatistics in public health using stata

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Biostatistics In Public Health Using Stata

Author : Erick L. Suárez
ISBN : 9781498722025
Genre : Mathematics
File Size : 49. 15 MB
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Striking a balance between theory, application, and programming, Biostatistics in Public Health Using STATA is a user-friendly guide to applied statistical analysis in public health using STATA version 14. The book supplies public health practitioners and students with the opportunity to gain expertise in the application of statistics in epidemiologic studies. The book shares the authors’ insights gathered through decades of collective experience teaching in the academic programs of biostatistics and epidemiology. Maintaining a focus on the application of statistics in public health, it facilitates a clear understanding of the basic commands of STATA for reading and saving databases. The book includes coverage of data description, graph construction, significance tests, linear regression models, analysis of variance, categorical data analysis, logistic regression model, poisson regression model, survival analysis, analysis of correlated data, and advanced programming in STATA. Each chapter is based on one or more research problems linked to public health. Additionally, every chapter includes exercise sets for practicing concepts and exercise solutions for self or group study. Several examples are presented that illustrate the applications of the statistical method in the health sciences using epidemiologic study designs. Presenting high-level statistics in an accessible manner across research fields in public health, this book is suitable for use as a textbook for biostatistics and epidemiology courses or for consulting the statistical applications in public health. For readers new to STATA, the first three chapters should be read sequentially, as they form the basis of an introductory course to this software.

Biostatistics In Public Health Using Stata

Author : Erick L. Suarez Perez
ISBN : 1498721990
Genre : Mathematics
File Size : 36. 41 MB
Format : PDF, ePub
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This book helps public health practitioners and students gain expertise in applications of regression modeling in order to solve problems when data are collected in epidemiological studies. It covers linear regression models, polynomial regression models, weighted linear regression models, methods for selecting the best regression equation, logistic regression models, and Poisson regression models. One chapter solves these examples with the STATA program. Additionally, every chapter has exercise sets for practicing concepts and exercise solutions for self or group study.

An Introduction To Stata For Health Researchers

Author : Svend Juul
ISBN : 9781597180108
Genre : Computers
File Size : 59. 36 MB
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Designed to assist those working in health research, An Introduction to Stata for Health Researchers, explains how to maximize the versatile Strata program for data management, statistical analysis, and graphics for research. The first nine chapters are devoted to becoming familiar with Stata and the essentials of effective data management. The text is also a valuable companion reference for more advanced users. It covers a host of useful applications for health researchers including the analysis of stratified data via epitab and regression models; linear, logistic, and Poisson regression; survival analysis including Cox regression, standardized rates, and correlation/ROC analysis of measurements.

Applications Of Regression Models In Epidemiology

Author : Erick Suárez
ISBN : 9781119212508
Genre : Mathematics
File Size : 55. 65 MB
Format : PDF
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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.

Fundamentals Of Biostatistics

Author : Bernard Rosner
ISBN : 9781133008170
Genre : Science
File Size : 65. 21 MB
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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Essentials Of A Successful Biostatistical Collaboration

Author : Arul Earnest
ISBN : 9781315356020
Genre : Mathematics
File Size : 44. 57 MB
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The aim of this book is to equip biostatisticians and other quantitative scientists with the necessary skills, knowledge, and habits to collaborate effectively with clinicians in the healthcare field. The book provides valuable insight on where to look for information and material on sample size and statistical techniques commonly used in clinical research, and on how best to communicate with clinicians. It also covers the best practices to adopt in terms of project, time, and data management; relationship with collaborators; etc.

A Biostatistics Toolbox For Data Analysis

Author :
ISBN : 9781107113084
Genre :
File Size : 87. 86 MB
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Biostatistics For Clinical And Public Health Research

Author : Melody S. Goodman
ISBN : 9781351651714
Genre : Medical
File Size : 28. 82 MB
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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.

Handbook Of Statistical Analyses Using Stata Third Edition

Author : Sophia Rabe-Hesketh
ISBN : 1439832358
Genre : Mathematics
File Size : 29. 39 MB
Format : PDF
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The powerful statistical software Stata has streamlined data analysis, interpretation, and presentation for researchers and statisticians around the world. But because of its power and plethora of features, particularly in version 8, Stata manuals are usually quite extensive and detailed. The third edition of the Handbook of Statistical Analyses Using Stata describes the features of Stata version 8 in the same concise, convenient format that made the previous editions so popular. But the revisions updating the handbook to version 8 are not all this edition has to offer: the authors also added important material in three all-new chapters and focused more attention on Stata's improved graphical features. More Highlights of the Third Edition Ö Updates in all chapters that reflect the features of Stata 8 Ö A new chapter on random effects models Ö A new chapter on generalized estimating equations Ö A new chapter on cluster analysis Ö Increased emphasis on diagnostics Each chapter deals with a particular data set, identifies the appropriate analysis for it, and while it includes a brief account of the statistical background of the technique applied, the primary focus remains firmly on using Stata 8 and interpreting its results. Ideal for researchers, statisticians, and students alike, this handbook forms a perfect complement to the Stata manuals, by giving new users a head start on using the program and providing experienced users with a handy quick reference.

Regression Methods In Biostatistics

Author : Eric Vittinghoff
ISBN : 9781461413530
Genre : Medical
File Size : 22. 78 MB
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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.

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