1. Creating Something from Nothing: Working with Synthetic Files
Bo Wandschneider University of Guelph
DLI Training: April 2004, Kingston
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2. Outline NLSCY background Types of microdata files
Which microdata file to use
Providing services for synthetic files
This presentation is a modification of a workshop that Chuck Humphrey and I presented at the May 2003 National DLI Training and a Presentation Chuck presented at Accoleds – DLI training, 2003.
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3. NLSCY
The National Longitudinal Survey of Children and Youth (NLSCY) is a long-term study of Canadian children that follows their development and well-being from birth to early adulthood. The NLSCY began in 1994 and is jointly conducted by Statistics Canada and Human Resources Development Canada.
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4. NLSCY There are 4 cycles There are 8 different files
2 of these are available as a PUMF
Primary
Self-Reporting
The rest include: secondary and those based on people reporting about child (teacher, principal…)
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5. Types of Microdata Files
Confidential Microdata Products
Master Files
Share Files
Public Access Microdata Products
Public use anonymized microdata (PUMFS)
Synthetic Files
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6. Microdata Products Microdata
raw data organized in a file where the records or lines in the file are observations of a specific unit of analysis and the information on the lines are the values of variables
requires some form of processing or analysis to be used
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7. Microdata Products
NLSCY –cycle 3 - primary
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8. Confidential Microdata
Master Files
These files contain the fullness of detail captured about the unit of observation. The information in these files could identify the individual who provided the original information and, therefore, are considered confidential.
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9. Confidential Microdata
Master File – Example
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10. Confidential Microdata
Master File – detailed identifiers
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11. Confidential Microdata
Master File – geography
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12. Confidential Microdata
Master File - fullness of data
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13. Confidential Microdata
Master File - fullness of data
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14. Confidential Microdata
Master File - fullness of data
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15. Confidential Microdata
Share Files
these are confidential files in which the respondents have signed a consent form permitting Statistics Canada to allow access to their information for approved research.
Used with NPHS and NLSCY
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16. Public Access Microdata
Anonymized Microdata
these microdata are specially prepared to minimize the possibility of disclosing or identifying any of the cases or observations
the original data from the master file are edited to create a public use microdata file
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17. Public Access Microdata
Steps in Anonymizing Microdata
removal of all personal identifiers
include only gross levels of geography
collapse detailed information into fewer general categories or cap values
suppress the values of a variable
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18. Public Access Microdata
Statistics Canada PUMFs
only available for select social surveys that undergo a review of the Data Release Committee, an internal Statistics Canada committee;
no ‘enterprise’ public use microdata;
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19. Public Access Microdata
Statistics Canada PUMFs
almost all are cross-sectional, that is, represent data collected at one point in time;
longitudinal data are difficult to anonymize while maintaining any useful information.
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20. Public Access Microdata
PUMFs – personal identifiers
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21. Public Access Microdata
PUMFs – gross geography
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22. Public Access Microdata
PUMFs – collapsed data
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23. Public Access Microdata
PUMFs – suppressed variables
Note – from the MASTER file – NOT the PUMF
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24. Public Access Microdata
Synthetic Files
These microdata do not contain actual ‘real’ cases but are pseudo-cases that for some surveys, provide aggregate results close to the ‘real’ cases
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25. Public Access Microdata
Synthetic Files
They have been prepared to create analysis runs with the master file without possibly disclosing or identifying any of the cases
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26. Public Access Microdata
Synthetic Files
The results are not to be reported, but are strictly to be used to prepare analyses of master files;
Usually associated with longitudinal files.
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27. Public Access Microdata
Steps in creating Synthetic Files
Observations are transformed
No records actually exist
Keep fullness of variable description
How the files are made is kept confidential
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28. Public Access Microdata
Synthetic Files – NLSCY
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29. Public Access Microdata
Synthetic Files – NPHS 1999 General File
PUMF
Synthetic
Obs
49046
Var
176
400
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30. Implications for Analysis
What are the implications in doing analysis with these different types of microdata files?
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31. Implications for Analysis
Master File
All observations
Has the most variables with the most detail
Lots of geography and personal characteristics
Little grouping or capping of categories
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32. Implications for Analysis
Master File
Restricted access: only available to authorized Statistics Canada employees, which includes ‘deemed employees’;
Use of the analysis is controlled through a contract;
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33. Implications for Analysis
Master File
Includes linkage variables across files within a study, e.g., NLSCY linkage among the files for different units of analysis (kids, parents, teachers…).
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34. Implications for Analysis
Public Use Microdata (PUMF)
Valuable content for a tremendous amount of research;
Suppresed observations
Suppressed variables
Suppresed Content
Gross Geography
Collapsed categories
Capped variables
Where issues arise is when smaller area geography is desired; rare subpopulations are being studied; or the variables that are needed have been used to anonymize respondents;
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35. Implications for Analysis
Public Use Microdata (PUMF)
Licensed product: agree to certain terms of use;
No linkage to multiple units of analysis, except for a few exceptions (e.g., GSS Time Use and Family);
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36. Implications for Analysis
Synthetic Files
“Looks like a duck and quacks like a duck”, but it isn’t a duck or any other type of fowl.
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37. Implications for Analysis
Synthetic Files
Looks like master files
Lots of observations (maybe)
Lots of variables
Little grouping or capping of categories
Lots of geographic detail
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38. Synthetic Files Precautions
Results not authentic – but may be close in the aggregate for some synthetic files;
Use for testing analysis setups only;
Still need the master files for publishable results.
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39. Where do we get Access? Master File
Restricted access governed under the Statistics Act;
Remote Job Submission (a.k.a, RDA)
Research Data Centres
Apply to SSHRC to obtain a peer-reviewed proposal and STC for security clearance.
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40. Where do we get Access? Public Use Microdata Files (PUMF) Get from DLI
Analyze where it is convenient
Can use a variety of analysis software, including SAS, SPSS, Stata, HLM, LISREL, etc.
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41. Where do we get Access? Synthetic Files
Author Divisions ‘may’ create it
Most relevant when dealing with new Panel Data, but not necessarily, e.g., the Census has potential
NLSCY, NPHS & CCHS synthetic files on DLI FTP site
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42. Where do we get Access? Synthetic files Work locally with the file
Build SAS and SPSS setups
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43. Which File is Appropriate?
1st stop is still the PUMF;
This file has the easiest access for us;
Probably meets the needs of most patrons;
Not as administratively burdensome as synthetic or master file;
Perfect for clients just looking for ‘data’ – courses in quantitative analysis;
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44. Which File is Appropriate?
If more detail is needed, refer to the Master File Documentation;
Inform patrons that the cost of use is higher, both in terms of accessibility and analytical requirements;
Interest most likely to come from grad students and ‘experienced’ researchers
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45. Which File is Appropriate?
Download the Synthetic files from DLI
Make them aware of problems with synthetic files – RESULTS ARE NOT PUBLISHABLE
Encourage them to submit an application for RDC access – there is a time lag
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46. Which File is Appropriate?
RDC
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47. Which File is Appropriate?
Some of you may work with patron using synthetic files before passing her/him off to RDC.
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48. Services for Synthetic Files
DLI Contacts can provide four basic services with synthetic files.
Build SPSS and SAS system files from the raw synthetic data files that are distributed through DLI;
Provide information about the use of Remote Job Submission and RDC’s;
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49. Services for Synthetic Files
Assist with finding variables in the synthetic files;
Provide instruction about ways of capturing SPSS or SAS code from “dummy” analysis runs with the synthetic files. It is this code that is submitted to STC through remote job submission.
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50. Services for Synthetic Files
1. Building SPSS and SAS system files for synthetic data
The NLSCY synthetic data are distributed as a raw ASCII file with accompanying command files for SPSS and SAS
Separate synthetic data files exist for each component of the NLSCY – not all components have PUMF’s
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51. Services for Synthetic Files
1. Building SPSS and SAS system files for synthetic data
The synthetic data for the NLSCY – cycle 3 – primary file, has 948 variables and 6,393 fabricated cases. Creating the SPSS and SAS system files from this file is not difficult, but it does take time. DLI Contacts may wish to create these products for their patrons.
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52. Services for Synthetic Files
2. Information about Remote Job Submission (RJS)
The author divisions supporting RJS have established their own guidelines and have different operating procedures. Not all divisions supporting longitudinal surveys currently support RJS (e.g., SLID).
Therefore, there is a need to track down this information for our patrons.
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53. Services for Synthetic Files
2. Information about Remote Job Submission (RJS)
For example, the sources for information about RJS include the Centre for Education Statistics:
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55. Services for Synthetic Files
2. Information about Remote Job Submission (RJS)
Where do you find this information?
Ask the DLI Team via the DLI List
The EAC has asked for a description of RJS on the DLI website, which should be on the DLI Team’s to-do list
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56. Services for Synthetic Files
2. Information about Research Data Centres
The collection of master files available through RDC’s is listed on the STC website for RDC’s
Each RDC has its own website describing its services
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58. Services for Synthetic Files
3. Data Reference for the content of the synthetic files
Helping researchers identify variables over longitudinal files is an important service
Need to keep the unit of analysis straight
Need to understand the mnemonic naming convention for variables over cycles
Develop indexing aids for you and your patrons
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59. Services for Synthetic Files
4. Provide helpful tips for preserving the code from “dummy” analysis runs in SPSS and SAS
Researchers will run analyses on the synthetic file to generate the code that they will subsequently for Remote Job Submission
Providing information about how to do this easily will be helpful to your patrons
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60. Exercises …
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