A Short Introduction to Stata for Biostatistics

Authors: Michael Hills and Bianca L. De Stavola
Publisher: Timberlake Consultants
Copyright: 2009
ISBN-10: 0-9557076-4-1
ISBN-13: 978-0-9557076-4-3
Pages: 188; paperback
Price: $52.00
A Short Introduction to Stata for Biostatistics bridges the information in the Getting Started manual and the Reference manuals by providing a more detailed introduction to the most often used analytic methods in biomedical research. Although it is written specifically for biostatisticians, epidemiologists, and health professionals new to Stata, the book is 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. 公卫考场

The first four chapters provide an overview of data entry and management commands, including those used to create, label, and drop variables and used to sort observations. After two chapters on graphics, the bulk of the book details methods used in data description and analysis. Beginning with commands used to create frequency tables and summary statistics, the book proceeds to describe commands used for univariate and multivariate analyses, including linear regression, Poisson regression, logistic regression, and survival data analysis. Included among the final chapters is a useful tutorial for writing your own Stata programs.

New additions for Stata 11 include a section on competing-risks analysis, new chapters on report generation and on meta analysis, and a description of the factor-variable notation.

0 Getting started 公卫论坛
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 公卫家园
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 Writing Stata programs
21 Exporting results
22 How Stata is organized