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A Short Introduction to Stata for Biostatistics
Comment from the Stata technical groupA 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. This edition incorporates updates for Stata 10. The first four chapters provide an overview of data entry and management commands, including those used to create, label, and drop variables and 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. Table of contents 0 Getting started
1 Some basic commands
1.1 The births data
1.2 A first look at the data 1.3 Tables of frequencies 1.4 Tables of means and other things 1.5 Restricting the scope of commands 1.6 Generating new variables 1.7 Ordering, dropping and keeping 1.8 Sorting data 1.9 Using Stata as a calculator 1.10 Shortcuts 1.11 Stata syntax 1.12 Using the Stata help facilities 2 Tabs, menus and dialog boxes
2.1 Where to find the dialog boxes
2.2 A first look at the data 2.3 Tables of frequencies 2.4 Tables of means and other things 2.5 Restricting the scope of commands 2.6 Generating new variables 2.7 Ordering, dropping and keeping 2.8 Sorting data 2.9 Using Stata as a calculator 3 Housekeeping
3.1 Labelling a dataset
3.2 Notes 3.3 Labelling variables and their value 3.4 Data types and display formats 3.5 Recoding a variable 3.6 Missing values 3.7 Dates 3.8 Saving files 3.9 Log files 3.10 Do files 4 Data input and output
4.1 Data sources
4.2 Data from a spreadsheet 4.3 Data from a wordprocessor 4.4 Large datasets 4.5 More about dictionary files 4.6 Loading data from the keyboard 4.7 Data output 4.8 Import and export to other packages 5 Graph commands
5.1 Box plots
5.2 Histograms 5.3 Scatter plots 5.4 Overlaying graphs 5.5 Line plots 5.6 Cumulative distribution plots 5.7 Adding lines 5.8 Graph titles 5.9 Titles and labels for axes 5.10 Naming, saving, and combining graphs 5.11 Printing and exporting graphs 5.12 Schemes 5.13 Help for graphics 6 Graph dialog boxes
6.1 Histograms
6.2 Box plots 6.3 Bar charts 6.4 Twoway graphs 6.5 The graph editor 7 More basic tools
7.1 The return list
7.2 Generating variables using functions 7.3 Grouping the values of a variable 7.4 Comparing two means or two proportions 7.5 Weights 7.6 Repeating commands for different sub-groups 7.7 Repeating commands for different variables 8 Data management
8.1 Cleaning data
8.2 String variables 8.3 Appending to add more subjects 8.4 Merging to add more variables 8.5 Merging to update variables 8.6 Unmatched merges 9 Repeated measurements
9.1 Wide and long coding
9.2 Graphing repeated measures 9.3 Working at the group level 9.4 Collapsing the data 9.5 Reshaping from long to wide and vice versa 9.6 Use of system variables with by: 9.7 Merging files with long coding 10 Response and explanatory variables
10.1 Questions in statistical analysis
10.2 Producing tables with tabmore 10.3 A second explanatory variable 10.4 Odds 10.5 Case-control studies 10.6 Survival data and rates 10.7 Count data and rates 11 Measuring e_ects
11.1 A metric response
11.2 A binary response 11.3 Case-control studies 11.4 A failure response 11.5 Metric exposure variables 11.6 Metric versus grouped 12 Stratifying and controlling
12.1 Stratification
12.2 Controlling 12.3 Controlling the effect of a metric exposure 12.4 Metric control variables 12.5 Metric versus grouped 13 Regression commands
13.1 Three important regression models
13.2 A metric exposure 13.3 A categorical exposure with two levels 13.4 Categorical exposures with more than 2 levels 13.5 Fitted values and residuals 13.6 Case-control studies 14 Tests of hypotheses
14.1 Models and Likelihood
14.2 Log likelihood 14.3 Likelihood ratio and Wald tests in Stata 14.4 Joint tests of several parameters 14.5 Other regression commands 15 Controlling and stratifying with regression
15.1 Controlling with regression commands
15.2 Testing effects after controlling 15.3 Stratifying with regression commands 15.4 Testing for effect modification and interactions 15.5 Interactions with metric variables 16 Mantel-Haenszel methods
16.1 The method
16.2 The Stata command 16.3 Matched case-control studies 16.4 Mantel-Haenszel methods for rates 16.5 Exposures on more than two levels 17 Survival data and stset
17.1 The response in survival data
17.2 Summarizing survival time 17.3 Calculating rates and rate ratios 17.4 Nelson-Aalen plots of cumulative rate 17.5 Variables created by stset 17.6 A metric exposure on a log scale 17.7 Rates that vary with time 17.8 Cox regression 17.9 Time updated exposures 18 Different time scales and standardization
18.1 Follow-up time
18.2 The diet data 18.3 Rates that change with time 18.4 Using non-st commands with st data 18.5 Two time-scales 18.6 Standardization 19 Writing Stata programs
19.1 Starting with a do file
19.2 Making the do file into an ado file 19.3 Cutting out unwanted output 19.4 Making the program accept arguments 19.5 Allowing if, in, and options 19.6 Discarding previous versions of a program 19.7 Another example 19.8 Some additional programming points 20 How Stata is organized
20.1 Paths and programs
20.2 Updating Stata 20.3 The Stata Journal 20.4 User-contributed programs 20.5 The Statalist 20.6 Other sources of help |
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