An Introduction to Stata for Health Researchers - Second Edition

by Svend Juul

Svend Juul’s An Introduction to Stata for Health Researchers, Second Edition is distinguished in its careful attention to detail. The reader will learn not only how to use Stata but also the skills needed to create the reproducible analyses so necessary in the field.

The book is based on the assumption that the reader has some basic knowledge of statistics but no knowledge of Stata. Juul builds the reader’s abilities as a builder would build a house, laying a firm foundation in Stata, framing a general structure in which good work can be accomplished, and finally filling in details that are particular to various types of statistical analysis

Juul starts by teaching the reader how to communicate with Stata, not just through its unified syntax, but also by demonstrating how Stata thinks about its basic building blocks. Juul shows how Stata views data and graphics, allowing the reader to see the variety of possible data structures. He also shows how to manipulate the data to create a dataset that is well documented and how to create carefully crafted graphs. He makes the book easy to use as a learning tool and easy to refer back to for useful techniques.

Once he introduces Stata to the new user, Juul fills in the details for performing analysis in Stata. As would be expected from a book addressing health researchers, Juul demonstrates mostly the statistical techniques common in biostatistics and epidemiology: case–control and matched case–control data analysis, stratified or not; linear and generalized linear models, including logistic, Poisson, and binomial regression; survival analysis with both life tables and proportional hazards; and classification using receiver operating characteristic curves.

While teaching Stata implementation, Juul reinforces habits that allow reproducible research and graceful backtracking in case of errors. Early in the book, he introduces how to use do-files for creating and log files for tracking work. At the end of the book, Juul introduces some useful programming techniques, such as loops and branching, that simplify repetitive tasks.

Table of contents

List of Figures

Preface to the second edition

Preface to the first edition

1 Getting started

1.1 Installing and updating Stata

1.2 Starting and exiting Stata

1.3 Customizing Stata (Windows)

1.4 Windows in Stata

1.5 Issuing commands

1.6 managing Output

1.7 Reusing commands

2 Getting help—and more

22.1 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

4.8 Version control

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 Checking correctness of calculations

8.6 Numbering observations

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 The Graph Editor

11.11 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 and scalars

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

19 Appendix: Manuals and other good books

A.1 Stata manuals

A.2 Other books on Stata

A.3 Books using Stata

20 Appendix: Exercises

20.1 The user interface

20.2 Managing output

20.3 Calculations

20.4 Working with missing values

20.5 Working with date variables

20.6 Description and simple analysis

20.7 Taking good care of your data

21 Appendix: Advice on working with Windows

References

Author index

Subject index