Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 An Introduction to Secondary Data Analysis
- 2 Health Services Utilization Data
- 3 Health Behaviors and Risk Factors Data
- 4 Data on Multiple Health Topics
- 5 Fertility and Mortality Data
- 6 Medicare and Medicaid Data
- 7 Other Sources of Data
- Appendix I Acronyms
- Appendix II Summary of Data Sets and Years Available
- Appendix III Data Import and Transfer
- Bibliography
- Index
Appendix III - Data Import and Transfer
Published online by Cambridge University Press: 03 December 2009
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 An Introduction to Secondary Data Analysis
- 2 Health Services Utilization Data
- 3 Health Behaviors and Risk Factors Data
- 4 Data on Multiple Health Topics
- 5 Fertility and Mortality Data
- 6 Medicare and Medicaid Data
- 7 Other Sources of Data
- Appendix I Acronyms
- Appendix II Summary of Data Sets and Years Available
- Appendix III Data Import and Transfer
- Bibliography
- Index
Summary
Many of the data sets discussed in this volume are provided in ASCII (plain text) format or another nonspecific format such as comma-separated or tab-delimited values. However, analysis of these data will usually be performed using a proprietary statistical analysis package such as SAS, SPSS, or Stata, which requires that the data be imported into that program and translated to the format it favors. There are several ways to get data from the supplied format to that required by a particular statistical package. One is to use the import facility or “wizard” that many statistical packages now include; this allows the user to import and translate data through an interactive interface. Another way is to use a program written to translate data from one format to another, such as Stat/Transfer, which can read and write data in about thirty different formats. Further information on Stat/Transfer, including a downloadable trial copy, is available from www.stattransfer.com/html/products.html.
A third way to import and translate data is to use syntax (i.e., a computer program), which specifies the commands necessary to read the ASCII or other data set and translate it into a format usable by the statistical analysis package. This method has the advantages that the syntax may be shared among users, may be rerun if a file is lost or damaged, and may often be reused with minor modifications from year to year if a data set is released annually in a consistent format.
- Type
- Chapter
- Information
- Secondary Data Sources for Public HealthA Practical Guide, pp. 123 - 128Publisher: Cambridge University PressPrint publication year: 2007