An Introduction to Stata for Health Researchers, Fourth Edition methodically covers data management, simple description and analysis, and more advanced analyses often used in health research, including regression models, survival analysis, and evaluation of diagnostic methods. A chapter on graphics explores most graph types and describes how to modify the appearance of a graph before submitting it for publication. The authors emphasize the importance of good documentation habits to prevent errors and wasted time. Demonstrating the use of strategies and tools for documentation, they provide robust examples and offer the datasets for download online. Updated to correspond to Stata 13, this fourth edition is written for both Windows and Mac users. It provides improved online documentation, including further reading in online manuals.
Author: Svend Juul,Morten Frydenberg
Publisher: Stata Press
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, A Handbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many new features of Stata, including a new command for mixed models and a new matrix language. Each chapter describes the analysis appropriate for a particular application, focusing on the medical, social, and behavioral fields. The authors begin each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests, variance analysis, multiple linear regression, logistic regression, generalized linear models, survival analysis, random effects models, and cluster analysis. The core of the book centers on how to use Stata to perform analyses and how to interpret the results. The chapters conclude with several exercises based on data sets from different disciplines. A concise guide to the latest version of Stata, A Handbook of Statistical Analyses Using Stata, Fourth Edition illustrates the benefits of using Stata to perform various statistical analyses for both data analysis courses and self-study.
Author: Brian S. Everitt,Sophia Rabe-Hesketh
Publisher: CRC Press
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. The companion website supplies data, syntax, and output for the book's examples--now including files for Amos, EQS, LISREL, Mplus, Stata, and R (lavaan). New to This Edition *Extensively revised to cover important new topics: Pearl's graphing theory and the SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. *Expanded coverage of psychometrics. *Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). *Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models. Pedagogical Features *Exercises with answers, plus end-of-chapter annotated lists of further reading. *Real examples of troublesome data, demonstrating how to handle typical problems in analyses. *Topic boxes on specialized issues, such as causes of nonpositive definite correlations. *Boxed rules to remember. *Website promoting a learn-by-doing approach, including syntax and data files for six widely used SEM computer tools.
Author: Rex B. Kline
Publisher: Guilford Publications
Category: Social Science
New Edition of a Classic Guide to Statistical Applications in the Biomedical Sciences In the last decade, there have been significant changes in the way statistics is incorporated into biostatistical, medical, and public health research. Addressing the need for a modernized treatment of these statistical applications, Basic Statistics, Fourth Edition presents relevant, up-to-date coverage of research methodology using careful explanations of basic statistics and how they are used to address practical problems that arise in the medical and public health settings. Through concise and easy-to-follow presentations, readers will learn to interpret and examine data by applying common statistical tools, such as sampling, random assignment, and survival analysis. Continuing the tradition of its predecessor, this new edition outlines a thorough discussion of different kinds of studies and guides readers through the important, related decision-making processes such as determining what information is needed and planning the collections process. The book equips readers with the knowledge to carry out these practices by explaining the various types of studies that are commonly conducted in the fields of medical and public health, and how the level of evidence varies depending on the area of research. Data screening and data entry into statistical programs is explained and accompanied by illustrations of statistical analyses and graphs. Additional features of the Fourth Edition include: A new chapter on data collection that outlines the initial steps in planning biomedical and public health studies A new chapter on nonparametric statistics that includes a discussion and application of the Sign test, the Wilcoxon Signed Rank test, and the Wilcoxon Rank Sum test and its relationship to the Mann-Whitney U test An updated introduction to survival analysis that includes the Kaplan Meier method for graphing the survival function and a brief introduction to tests for comparing survival functions Incorporation of modern statistical software, such as SAS, Stata, SPSS, and Minitab into the presented discussion of data analysis Updated references at the end of each chapter Basic Statistics, Fourth Edition is an ideal book for courses on biostatistics, medicine, and public health at the upper-undergraduate and graduate levels. It is also appropriate as a reference for researchers and practitioners who would like to refresh their fundamental understanding of statistical techniques.
A Primer for the Biomedical Sciences
Author: Olive Jean Dunn,Virginia A. Clark
Publisher: John Wiley & Sons
Known for its brevity and student-friendly approach, Essential Statistics for Public Managers and Policy Analysts remains one of the most popular introductory books on statistics for public policy and public administration students, using carefully selected examples tailored specifically for them. The Fourth Edition continues to offer a conceptual understanding of statistics that can be applied readily to the real-life challenges of public administrators and policy analysts. The book provides examples from the areas of human resources management, organizational behavior, budgeting, and public policy to illustrate how public administrators interact with and analyze data.
Author: Evan Berman,Xiaohu Wang
Publisher: CQ Press
Category: Political Science
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Author: William Gould,Jeffrey Pitblado,William Sribney
Publisher: Stata Press
With Philip Pollock's Third Edition of A Stata Companion to Political Analysis, students quickly learn Stata via step-by-step instruction, more than 50 exercises, customized datasets, annotated screen shots, boxes that highlight Stata's special capabilities, and guidance on using Stata to read raw data. This attractive and value-priced workbook, an ideal complement to Pollock’s Essentials of Political Analysis, is a must-have for any political science student working with Stata.
Author: Philip H. Pollock III
Publisher: CQ Press
Category: Political Science
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata. As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming. Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.
Author: Christopher F. Baum
Publisher: Stata Press
Category: Business & Economics
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.
Author: Erick L. Suárez,Cynthia M. Pérez,Graciela M. Nogueras,Camille Moreno-Gorrín
Publisher: CRC Press
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps less mathematically-inclined readers to grasp the underlying relations among path analysis, factor analysis, and structural equation modeling, and to set up and carry out such analyses. This revised and expanded fifth edition again contains key chapters on path analysis, structural equation models, and exploratory factor analysis. In addition, it contains new material on composite reliability, models with categorical data, the minimum average partial procedure, bi-factor models, and communicating about latent variable models. The informal writing style and the numerous illustrative examples make the book accessible to readers of varying backgrounds. Notes at the end of each chapter expand the discussion and provide additional technical detail and references. Moreover, most chapters contain an extended example in which the authors work through one of the chapter’s examples in detail to aid readers in conducting similar analyses with their own data. The book and accompanying website provide all of the data for the book’s examples as well as syntax from latent variable programs so readers can replicate the analyses. The book can be used with any of a variety of computer programs, but special attention is paid to LISREL and R. An important resource for advanced students and researchers in numerous disciplines in the behavioral sciences, education, business, and health sciences, Latent Variable Models is a practical and readable reference for those seeking to understand or conduct an analysis using latent variables.
An Introduction to Factor, Path, and Structural Equation Analysis, Fifth Edition
Author: John C. Loehlin,A. Alexander Beaujean
Publisher: Taylor & Francis
Publishing Your Medical Research is the second edition of the award-winning book that provides practical information on how to write a publishable paper. This edition includes additional details to help medical researchers succeed in the competitive “publish or perish” world. Using a direct and highly informative style, it does more than help you write a paper; it presents the technical information, invaluable modern advice, and practical tips you need to get your paper accepted for publication. A singular source for the beginning and experienced researcher alike, Publishing Your Medical Research is a must for any physician, fellow, resident, medical scientist, graduate student, or biostatistician seeking to be published.
Author: Daniel W. Byrne
Publisher: Lippincott Williams & Wilkins
Evidence-Based Diagnosis explains diagnostic, screening, and prognostic tests in clinical medicine. The authors' approach is based on many years of experience teaching physicians in a clinical research training program. Although needing only a minimum of mathematics, the quantitative discussions in this book are deeper and more rigorous than in most introductory texts. The book includes numerous worked examples and 60 problems (with answers) based on real clinical situations and journal articles. This book is a great choice for anyone looking to select, develop, or apply medical tests. Topics covered include: the diagnostic process; test reliability and accuracy; testing and treatment thresholds; critical appraisal of studies of diagnostic, screening and prognostic tests; test independence and methods of combining tests; quantifying treatment benefits using randomized trials and observational studies; Bayesian interpretation of P values and confidence intervals; challenges for evidence-based diagnosis; likelihood ratios and ROC curves.
Author: Thomas B. Newman,Michael A. Kohn
Publisher: Cambridge University Press
Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/
An Introduction to Multiple Regression and Structural Equation Modeling
Author: Timothy Z. Keith
This is the only introductory statistics text written specifically for health science students. Assuming no prerequisites other than high school algebra, the authors provide numerous examples from health settings, a wealth of helpful learning aids, as well as hundreds of exercises to help students succeed in the course.
Author: Jan W. Kuzma,Stephen E. Bohnenblust
Publisher: McGraw-Hill Europe
Category: Medical statistics
Designing Clinical Research sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This product incorporates current research methodology--including molecular and genetic clinical research--and offers an updated syllabus for conducting a clinical research workshop. Emphasis is on common sense as the main ingredient of good science. The book explains how to choose well-focused research questions and details the steps through all the elements of study design, data collection, quality assurance, and basic grant-writing.
Author: Stephen B. Hulley,Steven R. Cummings,Warren S. Browner,Deborah G. Grady,Thomas B. Newman
Publisher: Lippincott Williams & Wilkins
Using diverse examples from published research, the Third Edition of The Process of Research in Psychology by Dawn M. McBride provides step-by-step coverage on how to design, conduct, and present a research study. Early chapters introduce important concepts for developing research ideas while subsequent "nuts and bolts" chapters provide more detailed coverage of topics and examine the types of research relevant to the field. This logical two-part structure creates an excellent foundation upon which students can build their knowledge of the entire research process.
Author: Dawn M. McBride
Publisher: SAGE Publications
Provides statistical modeling and simulating approaches to address the needs for intrusion detection and protection. Covers topics such as network traffic data, anomaly intrusion detection, and prediction events.
Modern Statistically-Based Intrusion Detection and Protection
Author: Wang, Yun
Publisher: IGI Global