1. Creating Something from Nothing: Synthetic and Dummy files Bo Wandschneider University of Guelph Chuck Humphrey University of Alberta DLI Training: Ottawa, May, 2003

2. Outline Types of data Files Implications for analysis Where do we get access Which file is appropriate Providing service with synthetic files NPHS: an exercise SLID: an exercise

3. Types of Data Files Microdata Confidential Microdata Products Master Files Share Files Public Access Microdata Products Public Use Anonym zed microdata (PUMFS) Synthetic Files

4. 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

5. Microdata Products Microdata - SCF Example 000011031000+025607+000000+025607+000337+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+025944+0064 81+0194632331000000000090922201200000000000222+0232111000+000000+0000003000000000000000002228233411412190638749500575211004600132 000021031000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+0000 00+0000001663000000000060824432200000000000632+0000000000+000000+0000000000000000000000003116121111435481500777500570033004300110 000031031000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+0000 00+0000001663000000000040521112200000000000432+0206261110+000636+0000003000000000000000002228213411436491600778500570033004200085 000041031000+002080+000000+002080+000000+000575+000522+000000+000000+002574+000000+000000+003671+003149+000522+000000+000000+005751+0000 00+0057514551000000000060824432200000000000532+0220101021+000575+0005223000000000000000002240223411431251000774500571622361600065 000051031000+018050+000000+018050+000000+000288+000261+000000+000000+000000+000000+000000+000549+000288+000261+000000+001179+019778+0024 63+0173152221000000000050522201200000000000432+0000001011+000288+0002611000000000000000001246123411411440748739500575011021600046 000061031000+001500+000000+001500+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+001500+0000 00+0015002551000000000101024501200000000000631+0000000000+000000+0000000000000000000000003123263411431071300773500571612004300094 000071031000+000000+000000+000000+000000+000000+000000+002540+000000+000000+000000+000000+002540+002540+000000+000000+000000+002540+0000 00+0025404152000000000010340201200000000000222+0121134000+000000+0000003000000000000000002269233411436491600778500570033004200041 000081031000+008400+000000+008400+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+008400+0008 58+0075422551000000000080823301200000000000332+0000000000+000000+0000000000000000000000003118133411411210848739500575211004600055 000091031000+026000+000000+026000+000000+000287+000156+000000+000000+000879+000000+000000+001322+001166+000156+000000+000000+027322+0043 35+0229872231000000000070823422200000000000642+0000001012+000287+0001561000000000000000001248113411431400300774500564512071600060 000101031000+000000+000000+000000+000157+000000+000000+005043+000000+000000+000000+000000+005043+002541+002502+000000+000000+005200+0000 00+0052004652000000000040622312200000000000642+0000000000+000000+0000002000000000000000004376213411436491600778500570033004400076 000111031000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+0000 00+0000001663000000000020341213100000000000462+0000000000+000000+0000000000000000000000003119213411435481500777500570033004500040 000121031000+000991+000000+000991+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000000+000991+0000 00+0009912551000000000020343322100000000000433+0000000000+000000+0000000000000000000000003117121311432231400773500571222004300244 000131031000+027716+000000+027716+000000+000288+000000+000000+000000+000000+000000+000000+000288+000288+000000+000000+000000+028004+0062 43+0217612221000000000070722201200000000000331+0034071100+000288+0000001000000000000000001226163411411431138739500575211004600156 000141031000+010000+000000+010000+000000+000600+000000+000000+000000+000000+000000+000000+000600+000600+000000+000000+000000+010600+0006 86+0099142331000000000040422201200000000000433+0077001011+000600+0005221000000000000000001260123411411440636719500573012221600148 000151031000+000750+000000+000750+000000+000000+000370+000000+000000+000000+000000+000000+000370+000000+000370+000000+000000+001120+0000 00+0011202551000000000080823313200000000000633+0323511032+001126+0003703000000000000000002245223411411261318529500575222004600132 000161031000+007012+000000+007012+000165+000000+000000+000000+000000+003082+000000+000000+003082+003082+000000+000000+000000+010259+0013 56+0089032541000000000070824432200000000000531+0000000000+000000+0000000000000000000000003118123411421320320439500573522171600111 000171031000+002027+000000+002027+000000+000000+000000+000000+000000+000000+000000+000000+

6. Confidential Microdata Master Files These files contain the fullness of detail captured about the unit of observation. The information in these files can identify the individual who provided the original information and, therefore, are considered confidential.

7. Confidential Microdata Master File – Example

8. Confidential Microdata Master File - Personal identifiers

9. Confidential Microdata Master File – Geography (SLID)

10. Confidential Microdata Master File - Fullness of Data (NPHS)

11. Confidential Microdata Master File - Fullness of Data

12. Confidential Microdata Master File - Fullness of Data (SLID)

13. Confidential Microdata Master File - Fullness of Data

14. 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

15. 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

16. Public Access Microdata Steps in Anonymizing Microdata removal of all personal identification information (names, addresses, etc) include only gross levels of geography collapse detailed information into a smaller number of general categories suppress the values of a variable

17. 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

18. 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

19. Public Access Microdata PUMFs – personal identifiers

20. Public Access Microdata PUMFs – gross geography

21. Public Access Microdata PUMFs – collapsed data

22. Public Access Microdata PUMFs – suppressed data

23. Public Access Microdata Synthetic Files These microdata do not contain actual ‘real’ cases but are pseudo- cases that provide aggregate results close to the ‘real’ cases

24. 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

25. Public Access Microdata Synthetic Files The results are not to be reported; strictly to be used to prepare analyses of master files Usually associated with longitudinal files

26. Public Access Microdata Steps in creating Synthetic Files Observations are transformed No records actually exist Keep fullness of detail

27. Public Access Microdata Synthetic Files – NPHS example

28. Public Access Microdata Synthetic Files – NPHS 1999 general file PUMFSynthetic Obs49046 Var176400

29. Public Access Microdata Synthetic Files – NPHS 1999

30. Public Access Microdata Synthetic Files – NPHS 1999

31. Implications for Analysis What are the implications in doing analysis with these different types of microdata files?

32. 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

33. Implications for Analysis Master File Restricted access: only available to authorized Statistics Canada employees, which includes ‘deemed employees’

34. 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)

35. Implications for Analysis Public Use Microdata (PUMF) Suppressed observations Suppressed variables: removed from the file Suppressed content Gross geography Collapsed categories Capped values

36. Implications for Analysis Public Use Microdata (PUMF) Licensed product: agree to certain terms of use No linkage to multiple units of analysis, with a few exceptions (GSS Time Use and Family)

37. 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.

38. Implications for Analysis Synthetic Files Looks like master files Lots of observations Lots of variables Little grouping or capping of categories Lots of geographic detail

39. Synthetic Files Precautions Results not authentic – but close in the aggregate Use for testing analysis setups only Still need the master files for publishable results

40. Where do we get Access? Master File Restricted access governed under the Statistics Act Remote Job Submission Research Data Centres Apply to SSHRC to obtain a peer- reviewed proposal and STC for security clearance

41. Where do we get Access? Public Use Microdata Files (PUMF) Get from DLI Analyze where ever is convenient Can use a variety of analysis software, including SAS, SPSS, Stata, HLM, LISREL, etc. Slidret sans data

42. 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 NPHS synthetic files on DLI FTP site

43. Where do we get Access? Synthetic files SLID, WES, YITS coming ???? Do we need to encourage them? Work with locally Build SAS and SPSS setups

44. Which File is Appropriate? 1 st stop is still the PUMF This file has the easiest access for us Probably meets the needs of most clients Not as administratively burdensome as synthetic or master file Perfect for clients just looking for ‘data’ – courses in quantitative analysis

45. Which File is Appropriate? If more detail is needed, refer to the Master File Documentation (similar to Synthetic File Documentation) Make them aware 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

46. 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

47. Which File is Appropriate? RDC

48. Which File is Appropriate? Some of you may work with client using synthetic files before passing her/him off to RDC

49. 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 (a.k.a, Remote Access) and RDC’s; Services for Synthetic Files

50. 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 then submitted to STC through remote job submission. Services for Synthetic Files

51. 1. Building SPSS and SAS system files for synthetic data The NPHS synthetic data are distributed as a raw ASCII file with accompanying command files for SPSS and SAS Separate synthetic data files exist for the master file setup and for bootstrapping analysis Services for Synthetic Files

52. 1. Building SPSS and SAS system files for synthetic data The synthetic data for the 2000-2001 NPHS has 4,138 variables and 17,276 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. Services for Synthetic Files

53. 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. Therefore, there is a need to track down this information for our patrons. Services for Synthetic Files

54. 2. Information about Remote Job Submission (RJS) For example, the sources for information about RJS include the Centre for Education Statistics: http://www.statcan.ca/english/edu/rda/index.htm Services for Synthetic Files

56. 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 Services for Synthetic Files

57. 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 http://www.statcan.ca/english/rdc/index.htm Services for Synthetic Files

59. 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 Services for Synthetic Files

60. 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 email for Remote Job Submission Providing information about how to do this easily will be helpful to your patrons Services for Synthetic Files

61. Let’s look at an example of these four services using the synthetic files from the NPHS, 2000-2001. An Example Using the NPHS

62. Let’s look at an example of a “dummy” file using SLIDRET, a retrieval system developed to extract data from the cycles of the SLID. A “data-less” version of SLIDRET is available through DLI to help identify variables for RJS. An Example Using SLID

63. Location of Slides and Exercices http://drc.uoguelph.ca/DATA/WKSHPS/IASSIST2003