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An Introduction to Stata for Health Researchers

Author: Svend Juul
Publisher: Stata Press
Copyright: 2006
ISBN-13: 978-1-59718-010-8
Pages: 326; paperback
Third edition now available

Comment from the Stata technical group

An Introduction to Stata for Health Researchers, by Svend Juul, provides in-depth and insightful coverage of all three topics for which Stata is known: data management, statistics, and graphics. By focusing on those who are involved in health research, Juul is able to strongly cover each topic.

The first nine (yes, nine!) chapters of the book are devoted to getting started with using Stata and learning the essentials of data management. Throughout this section, the author leaves no key information unstated, effectively placing himself “in the shoes” of the reader new to Stata. The reader learns the ins and outs of Stata’s windows, the importance of documentation, how to use do-files, how to get help (and how to help yourself), the command syntax, how to work with datasets, and the basic data management tasks such as merging and reshaping datasets.

Chapter 10 covers summary statistics, tables, and simple tests. Chapter 11 keeps the new user in mind while providing an introduction to the modern Stata graphics systems.

Although An Introduction to Stata for Health Researchers sounds like a book created solely for beginners, even the experienced Stata user will learn from the biostatistical discussions in chapters 12–15. Juul covers the usual topics for health researchers, including the following: the analysis of stratified data via epitab and regression models; linear, logistic, and Poisson regression; and survival analysis including Cox regression, standardized rates, and correlation/ROC analysis of measurements. When discussing these methods, Juul expertly shows how they relate to each other, for example, the analysis of a stratified case–control study using both mhodds and logistic. Sometimes the methods agree exactly, but sometimes they don't; the book explains the change in model assumptions leading to the differences.

The book concludes with supplementary material on advanced topics such as sample size calculations, simulation, some Stata programming concepts, and tips on caring for your data and maintaining reproducibility.


Table of contents

List of Figures
Preface (pdf)
1 Getting started
1.1 Installing and updating Stata
1.2 Starting and stopping Stata
1.3 Customizing Stata (Windows) numbers
1.4 Windows in Stata
1.5 Issuing commands
1.6 Exercises
1.7 Managing output
1.8 Reusing commands
1.9 More exercises
2 Getting help—and more
2.1 The manuals
2.2 Online help
2.3 Other resources
2.4 Errors and error messages
3 Stata file types and names
4 Command syntax
4.1 General syntax rules
4.2 Syntax diagrams
4.3 Lists of variables and numbers
4.4 Qualifiers
4.5 Weights
4.6 Options
4.7 Prefixes
4.8 Other syntax elements
5 Variables
5.1 Types of variables
5.2 Numeric formats
5.3 Missing values
5.4 Storage types and precision
5.5 Date variables
5.6 String variables
5.7 Memory considerations
6 Getting data in and out of Stata
6.1 Opening and saving Stata data
6.2 Entering data
6.3 Reading ASCII data
6.4 Exchanging data with other programs
7 Documentation commands
7.1 Labels
7.2 Working with labels: an example
8 Calculations
8.1 generate and replace
8.2 Operators and functions in calculations
8.3 Extended functions: egen
8.4 Recoding variables
8.5 Numbering observations
8.6 Exercises
9 Commands affecting data structure
9.1 Safeguarding your data
9.2 Selecting observations and variables
9.3 Renaming and reordering variables
9.4 Sorting data
9.5 Combining files
9.6 Reshaping data
10 Description and simple analysis
10.1 Overview of a dataset
10.2 Listing observations
10.3 Simple tables for categorical variables
10.4 Analyzing continuous variables
10.5 Estimating confidence intervals
10.6 Immediate commands
11 Graphs
11.1 Anatomy of a graph
11.2 Anatomy of graph commands
11.3 Graph size
11.4 Schemes
11.5 Graph options: Axes
11.6 Graph options: Text elements
11.7 Plot options: Markers, lines, etc.
11.8 Graph examples
11.9 By-graphs and combined graphs
11.10 Saving, displaying, and printing graphs
12 Stratified analysis
12.1 Cohort data without censorings
12.2 Case–control data
13 Regression analysis
13.1 Linear regression
13.2 Logistic regression
13.3 Other regression models
13.4 Analyzing complex design data
14 Incidence, mortality, and survival
14.1 Incidence and mortality
14.2 Survival analysis
14.3 Cox regression
14.4 Reorganizing st data
14.5 Poisson regression
14.6 Standardization
14.7 Some advanced issues
15 Measurement and diagnosis
15.1 Reproducibility of measurements
15.2 Comparing methods of measurement
15.3 Using tests for diagnosis
15.4 Combining test results
16 Miscellaneous
16.1 Random samples, simulations
16.2 Sample size and study power
16.3 Other analyses
17 Advanced topics
17.1 Using saved results
17.2 Macros
17.3 Programs
17.4 Useful programming commands
17.5 Do-files and ado-files useful for handling output
18 Taking good care of your data
18.1 The audit trail
18.2 Data collection
18.3 The codebook
18.4 Folders and filenames: the log book
18.5 Entering data
18.6 Inspecting and correcting your data
18.7 Modifying data
18.8 Analysis
18.9 Backing up and archiving
18.10 Protecting against abuse
A Manuals and other good books
A.1 Stata manuals
A.2 Other books on Stata
A.3 Books using Stata
B Advice on working with Windows
References
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