A Short Introduction to Stata for Biostatistics (Updated to Stata 12)
Authors: |
Michael Hills and Bianca L. De Stavola |
| Publisher: |
Timberlake |
| Copyright: |
2012 |
| ISBN-13: |
978-0-9571708-0-3 |
| Pages: |
181; paperback |
| Price: |
$52.00 |
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Comment from the Stata technical group
A Short Introduction to Stata for Biostatistics bridges the
information gap between Stata's
Getting Started manual and
Reference manuals
by providing a more detailed introduction to the
most often used analytic methods in biomedical research. Although the book
is written specifically for biostatisticians, epidemiologists, and health
professionals new to Stata, it is also useful for more-experienced users
wanting more in-depth knowledge of both Stata commands and biostatistical
issues. The book is hands on, intended to be used while working with Stata,
and includes a CD-ROM containing the datasets and several author-written
programs.
The first four chapters provide an overview of data entry and management
commands, including those used to create, label, and drop variables and those
used to sort observations. The next two chapters cover graphics. Then comes
the bulk of the book, which details methods used in data description and
analysis. Beginning with commands used to create frequency tables and
summary statistics, the authors proceed to describe commands used for
univariate and multivariate analyses, including linear regression, Poisson
regression, logistic regression, survival data analysis (proportional hazards
models and competing-risks models), and meta analysis. Included among the
final chapters is a useful tutorial on report generation.
Table of contents
0 Getting Started
1 Some basic commands
2 Tabs, menus and dialog boxes
3 Housekeeping
4 Data input and output
5 Graph commands
6 Graph dialog boxes
7 More basic tools
8 Data management
9 Repeated measurements
10 Response and explanatory variables
11 Measuring effects
12 Stratifying and controlling
13 Regression commands
14 Tests of hypotheses
15 Controlling and stratifying with regression
16 Mantel–Haenszel methods
17 Survival data and stset
18 Different time scales and standardization
19 Meta-analysis
20 Exporting results
21 How Stata is organized
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