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The Workflow of Data Analysis Using Stata by J. Scott Long (2009) Publisher: Stata Press ISBN: 978-1-59718-047-4 Pages: 379 pages Price: £45.00 + p&p |
List of tables
List of figures
List of examples
Preface
A word about fonts, files, commands, and examples
1 Introduction
1.1 Replication: The guiding principle for workflow
1.2 Steps in the workflow
1.2.1 Cleaning data
1.2.2 Running analysis
1.2.3 Presenting results
1.2.4 Protecting files
1.3 Tasks within each step
1.3.1 Planning
1.3.2 Organization
1.3.3 Documentation
1.3.4 Execution
1.4 Criteria for choosing a workflow
1.4.1 Accuracy
1.4.2 Efficiency
1.4.3 Simplicity
1.4.4 Standardization
1.4.5 Automation
1.4.6 Usability
1.4.7 Scalability
1.5 Changing your workflow
1.6 How the book is organized
2 Planning, organizing, and documenting
2.1 The cycle of data analysis
2.2 Planning
2.3 Organization
2.3.1 Principles for organization
2.3.2 Organizing files and directories
2.3.3 Creating your directory structure
2.3.4 Moving into a new directory structure (advanced topic)
2.4 Documentation
2.4.1 What should you document?
2.4.2 Levels of documentation
2.4.3 Suggestions for writing documentation
2.4.4 The research log
2.4.5 Codebooks
2.4.6 Dataset documentation
2.5 Conclusions
3 Writing and debugging do-files
3.1 Three ways to execute commands
3.1.1 The Command window
3.1.2 Dialog boxes
3.1.3 Do-files
3.2 Writing effective do-files
3.2.1 Making do-files robust
3.2.2 Making do-files legible
3.2.3 Templates for do-files
3.3 Debugging do-files
3.3.1 Simple errors and how to fix them
3.3.2 Steps for resolving errors
3.3.3 Example 1: Debugging a subtle syntax error
3.3.4 Example 2: Debugging unanticipated results
3.3.5 Advanced methods for debugging
3.4 How to get help
3.5 Conclusions
4 Automating your work
4.1 Macros
4.1.1 Local and global macros
4.1.2 Specifying groups of variables and nested models
4.1.3 Setting options with locals
4.2 Information returned by Stata commands
4.3 Loops: foreach and forvalues
4.3.1 Ways to use loops
4.3.2 Counters in loops
4.3.3 Nested loops
4.3.4 Debugging loops
4.4 The include command
4.4.1 Specifying the analysis sample with an include file
4.4.2 Recoding data using include files
4.4.3 Caution when using include files
4.5 Ado-files
4.5.1 A simple program to change directories
4.5.2 Loading and deleting ado-files
4.5.3 Listing variable names and labels
4.5.4 A general program to change your working directory
4.5.5 Words of caution
4.6 Help files
4.6.1 nmlabel.hlp
4.6.2 help me
4.7 Conclusions
5 Names, notes, and labels
5.1 Posting files
5.2 The dual workflow of data management and statistical analysis
5.3 Names, notes, and labels
5.4 Naming do-files
5.4.1 Naming do-files to re-create datasets
5.4.2 Naming do-files to reproduce statistical analysis
5.4.3 Using master do-files
5.4.4 A template for naming do-files
5.5 Naming and internally documenting datasets
5.5.1 One time only and temporary datasets
5.5.2 Datasets for larger projects
5.5.3 Labels and notes for datasets
5.5.4 The datasignature command
5.6 Naming variables
5.6.1 The fundamental principle for creating and naming variables
5.6.2 Systems for naming variables
5.6.3 Planning names
5.6.4 Principles for selecting names
5.7 Labeling variables
5.7.1 Listing variable labels and other information
5.7.2 Syntax for label variable
5.7.3 Principles for variable labels
5.7.4 Temporarily changing variable labels
5.7.5 Creating variable labels that include the variable name
5.8 Adding notes to variables
5.8.1 Commands for working with notes
5.8.2 Using macros and loops with notes
5.9 Value labels
5.9.1 Creating value labels is a two-step process
5.9.2 Principles for constructing value labels
5.9.3 Cleaning value labels
5.9.4 Consistent value labels for missing values
5.9.5 Using loops when assigning value labels
5.10 Using multiple languages
5.10.1 Using label language for different written languages
5.10.2 Using label language for short and long labels
5.11 A workflow for names and labels
5.11.1 Step 1: Check the source data
5.11.2 Step 2: Create clones and rename variables
5.11.3 Step 3: Revise variable labels
5.11.4 Step 4: Revise value labels
5.11.5 Step 5: Check the new names and labels
5.12 Conclusions
6 Cleaning your data
6.1 Importing data
6.1.1 Data formats
6.1.2 Ways to import data
6.1.3 Verifying data conversion
6.2 Verifying variables
6.2.1 Values review
6.2.2 Substantive review
6.2.3 Missing-data review
6.2.4 Internal consistency review
6.2.5 Principles for fixing data inconsistencies
6.3 Creating variables for analysis
6.3.1 Principles for creating new variables
6.3.2 Core commands for creating variables
6.3.3 Creating variables with missing values
6.3.4 Additional commands for creating variables
6.3.5 Labeling variables created by Stata
6.3.6 Verifying that variables are correct
6.4 Saving datasets
6.4.1 Selecting observations
6.4.2 Dropping variables
6.4.3 Ordering variables
6.4.4 Internal documentation
6.4.5 Compressing variables
6.4.6 Running diagnostics
6.4.7 Adding a data signature
6.4.8 Saving the file
6.4.9 After a file is saved
6.5 Extended example of preparing data for analysis
6.6 Merging files
6.6.1 Match-merging
6.6.2 One-to-one merging
6.6.3 Forgetting to match-merge
6.7 Conclusions
7 Analyzing data and presenting results
7.1 Planning and organizing statistical analysis
7.1.1 Planning in the large
7.1.2 Planning in the middle
7.1.3 Planning in the small
7.2 Organizing do-files
7.2.1 Using master do-files
7.2.2 What belongs in your do-file?
7.3 Documentation for statistical analysis
7.3.1 The research log and comments in do-files
7.3.2 Documenting the provenance of results
7.4 Analyzing data using automation
7.4.1 Locals to define sets of variables
7.4.2 Loops for repeated analyses
7.4.3 Matrices to collect and print results
7.4.4 Creating a graph from a matrix
7.4.5 Include files to load data and select your sample
7.5 Baseline statistics
7.6 Replication
7.6.1 Lost or forgotten files
7.6.2 Software and version control
7.6.3 Unknown seed for random numbers
7.6.4 Using a global that is not in your do-file
7.7 Presenting results
7.7.1 Creating tables
7.7.2 Creating graphs
7.7.3 Tips for papers and presentations
7.8 A project checklist
7.9 Conclusions
8 Protecting your files
8.1 Levels of protection and types of files
8.2 Causes of data loss and issues in recovering a file
8.3 Murphy’s law and rules for copying files
8.4 A workflow for file protection
8.5 Archival preservation
8.6 Conclusions
9 Conclusions
A.1 How Stata works
A.2 Working on a network
A.3 Customizing Stata
A.3.1 Fonts and window locations
A.3.2 Commands to change preferences
A.3.3 profile.do
A.4 Additional resources
References
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