Biostatistics in Public Health Using STATA

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Biostatistics in Public Health Using STATA

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 208 p.
  • 言語 ENG
  • 商品コード 9780367341480
  • DDC分類 610.727

Full Description

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.

Contents

Basic Commands. 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. Introduction to Advanced Programming in STATA. References. Index.

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