Comment from the Stata technical group
Stata advertises itself as software for performing data management, statistics,
and graphics. Any one text claiming to cover Stata as a whole
usually performs strongly in the coverage of one, or at most two, of these
topics. An Introduction to Stata for Health Researchers provides
in-depth and insightful coverage of all three, and it manages this feat by
focusing on only those topics that are useful for those involved in medical
research.
The first nine (yes, nine!) chapters of the text are devoted to getting
started and used to Stata and to the essentials of effective data management.
Throughout this section, the author does a great job of putting himself in the
shoes of the new user, leaving no key information unstated. The reader learns
the intricacies of Stata’s windows, the importance of documentation, how to
use do-files, how to get help (and more importantly, how to help yourself),
the command syntax, working with datasets, and basic data management tasks such as
merging and reshaping datasets.
Chapter 10 is devoted to summary statistics, tables, and simple tests,
and chapter 11 provides a good introduction to the modern Stata graphics
systems, again doing so with a good eye for the intended audience, i.e.,
the Stata newbie.
Although the book is billed as a Stata introduction, even the experienced
Stata user will have much to gain from the biostatistical discussions of
chapters 12–15. The usual topics for health researchers are covered:
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;
just to name a few. In discussing these methods, the author does an excellent
job of showing how these methods relate to each other, for example, the
analysis of a stratified case–control study using both mhodds and
logistic. Sometimes the methods agree exactly, and sometimes they
don’t, and the text proceeds to explain the change in model assumptions
leading to the differences.
The text concludes with some 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)
- 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
Author index (pdf)
Subject index (pdf)
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