Access to Confidential Data for Statistical Analysis

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Access to Confidential Data for Statistical Analysis

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Title: Access to Confidential Data for Statistical Analysis

1
Access to Confidential Data for Statistical
Analysis
Kenneth Harris, Director of Research Data Center
2
National Center for Health Statistics (NCHS)

Despite the wide dissemination of its data
through publications, CD-ROMs, etc., the
inability to release files with, for instance,
lower levels of geography, severely limits the
utility of some data for research, policy, and
programmatic purposes and sets a boundary on one
of the Centers goals to increase its capacity to
provide state and local area estimates.

3
NCHS (cont.)

In pursuit of this goal and in response to the
research communitys interest in restricted data,
NCHS established the Research Data Center (RDC),
a mechanism whereby researchers can access
detailed data files in a secure environment,
without jeopardizing the confidentiality of the
respondents.

4
Research Data Center

The NCHS Research Data Center, established in
1998, is a facility at the NCHS headquarters in
Hyattsville, Maryland, where researchers are
granted access to restricted data files needed to
complete approved projects. Restricted data
files may contain information, such as lower
levels of geography, but do not contain direct
identifiers (e.g., name or social security
number).

5
Data Restrictions

Section 308 (d) of the Public Health Service Act
and the NCHS Staff Confidentiality Manual do not
permit the release of data that are either
identified or identifiable to persons outside of
NCHS.

6
Data Restrictions (cont.)

Identifiable data include not only direct
identifiers such as name, social security number,
etc., but also data that can serve to allow
inferential identification of either individual
or institutional respondents by a number of means.

7
Data Restrictions (cont.)

Research indicates that identifiability is
greatly enhanced if geographic identifiers for
state, county, census tract, block-group or block
are released on public use files.

8
Key Issues for Research Data Availability

CONFIDENTIALITY
The dissemination of data in a manner that would
allow public identification of the respondent or
would in any way be harmful to him/her is
prohibited and the data are immune from legal
process.

9
Key Issues for Research Data Availability (cont.)

DISCLOSURE
Disclosure relates to inappropriate attribution
of information to a data subject, whether an
individual or an organization. Disclosure occurs
when a data subject is identified from a released
file (identity disclosure), sensitive information
about a data subject is revealed through the
released file (attribute disclosure), or the
released data make it possible to determine the
value of some characteristic of an individual
more accurately than otherwise would have been
possible (inferential disclosure).

10
Appendix I Rules for the Release of Micro Data
Files

The data file must not contain any detailed
information about the subject that could
facilitate identification and that is not
essential for research purposes (e.g., exact date
of the subjects birth).
Geographic places that have fewer than 100,000
people are not to be identified on the data file.
Characteristics of an area are not to appear on
the data file if they would uniquely identify an
area of less than 100,000 people.

11
Appendix I Rules for the Release of Micro Data
Files (cont.)

Information on the drawing of the sample which
might assist in identifying a data subject must
not be released outside the Center. Thus, the
identities of primary sampling units are not to
be made available outside the Center.
Before any new or revised micro data files are
published, they, together with their full
documentation, must be approved for publication
by the NCHS Director or Deputy Director.
A micro data file containing confidential data on
unidentified individuals or facilities may not be
released to any person or organization outside
NCHS until that person, or a responsible
representative of that organization, has first
signed the statement on the Order Form, whereby
he gives assurance that the data provided will be
used only for statistical reporting or research
purposes.

12
Why NCHS Does Not Release Files With Lower Levels
of Geography

Research suggests that in the case of personal
surveys nine commonly collected variables result
in the table below.

Population of Geopolitical Area Percent of Sample Identifiable
25,000 24
50,000 20
100,000 14
200,000 8
300,000 5
400,000 4
500,000 3
13
Why NCHS Does Not Release Files With Lower Levels
of Geography (cont.)

Notes A geopolitical area may be a county,
city, town, or other place with well- defined
boundaries.
In this case, identification refers to
certainty identification.

14
How Does RDC Operate?

On-Site Access
Remote Access
Staff Assisted Analytical Session

15
User Procedures

To gain access to NCHS restricted data through
either method, user must
Submit a research proposal.
An advisory and proposal review committee
receives, reviews, and approves researcher
proposals
Proposals are evaluated primarily on the
confidentiality disclosure risk.
Scientific merit is not an evaluation criteria.
Sign an affidavit of confidentiality and promise
not to use any method to attempt to identify
respondents.

16
User Procedures (cont.)

Not take any materials or equipment into RDC
unless approved by RDC staff.
Submit data files to be merged onto NCHS data
ahead of time all merging is done by RDC staff.
Subject all output and/or materials removed from
the RDC to a disclosure limitation review.
May not remove any NCHS restricted data files nor
linked data files.

17
Researcher Affidavit of Confidentiality

I certify that no confidential data or
information viewed or otherwise obtained while I
am a researcher in the National Center for
Health Statistics (NCHS), Research Data Center
(RDC) will be removed from NCHS. Further, I
understand that NCHS will perform a disclosure
review and must provide approval to me before I
remove any data from the RDC, whether it be in
electronic or paper form. I acknowledge NCHS
Confidentiality Statute, 308(d) of the Public
Health Service Act stated below and fully
understand my legal obligations to NCHS to
protect all confidential data. Further I
understand any violation I may perform is
punishable under 18 United States Code (USC),
1001 which carries a fine of up to 10,000 or up
to 5 years in prison.

18
Researcher Affidavit of Confidentiality (cont.)

NCHS 308(d) Confidentiality Statute - No
information, if an establishment or person
supplying the information or described in it is
identified, obtained in the course of activities
undertaken or supported under section 304, 305,
306, 307, or 309 may be used for any purpose
other than the purpose for which it was supplied
unless such establishment or person has consented
to its use for such other purpose and in the case
of information obtained in the course of health
statistical or epidemiological activities under
section 304 or 306, such information may not be
published or released in other form if the
particular establishment or person supplying the
information or described in it is identifiable
unless such establishment or person has consented
to its publication or release in other form.

19
Researcher Affidavit of Confidentiality (cont.)

18 United States Code, 1001 - Deliberately making
a false statement in any matter within the
jurisdiction of any Department or Agency of the
Federal Government violates 18 USC 1001 and is
punishable by a fine of up to 10,000 or up to 5
years in prison.
____________________ _______________
Researchers Signature Date
____________________ _______________
NCHS Witness Date

20
Can Researcher Merge his/her Data with NCHS ?

Must Interact with RDC staff to ensure
that their data can be merged with the
NCHS data.
User-supplied data will be merged with
NCHS data by RDC staff only.
The NCHS RDC policy states that merged
and user-supplied data will not be made
available for analysis to anyone without
the written consent of the user.

21
The Cost per Project

On Site
200 per day (2 day minimum)
Remote Access
NSFG-CDF 500/ year
NHIS-polio 500/ year
NHIS Linked Mort. File 250/Month
NHANES Linked Mort. File 250/Month

22
The Cost per Project (cont.)

Files lt 130k records 500 per month
Files gt 130k records 1000 per month
Staff Assisted Variable
File Construction and Setup
For Mortality Files 250 per day
For all Other Files 500 per day

23
Do Doctors perform defensive Cesareans?

Overview This topic re-examined the issues of
defensive medicine and state reforms designed
to limit malpractice risk on the use of cesarean
section delivery.
NCHS Data Used National Hospital Discharge
Survey (NHDS)
Years of Data Used 1980 through 1992,
inclusive.
Users Data Merged with NCHS? Yes
Method of Access to NCHS Data Remote and
On-site Access
Statistical Software Used SAS

24
Economic Model to Explain the Incidence of Sexual
Activity, Contraceptive Use, STD, and Pregnancy
Among Teenage Girls.

Overview National Survey of Family Growth Data
provide extensive socio-demographic information
and reports of the sexual histories of these
women. Researcher focused on the effects of a
number of policies measured at the state-level.
These included
Parental notification of consent laws.
Medicaid funding of abortions.
Welfare generosity.
NCHS Data Used National Survey of Family Growth
(NSFG)
Users Data Merged with NCHS? Yes
Method of Access to NCHS Data Remote Access
Statistical Software Used SAS

25
Nursing Home Admission and Payment Source?

Overview This project tested if patients with
Medicare were being discriminated against because
their reimbursement rate was significantly below
the private pay rate for nursing homes.
NCHS Data Used National Nursing Home Survey
(NNHS)
Years of Data Used 1985, 1995, and 1997
Users Data Merged with NCHS? No
Method of Access to NCHS Data Remote Access
Statistical Software Used SAS

26
Hardware and Software

All RDC hardware and software are standard.
Hardware
Pentium IV computers with Windows 2000
Software
SAS (only language on ANDRE)
Sudaan
Fortran
HLM
Stata
Limdep
text editors/viewers
Onsite workstations do NOT have email or internet
access
Only access to printer is through RDC staff

27
Record Linkage for Epidemiologic Research
Accessing Linked data at the NCHS Research Data
Center
Christine S. Cox NCHS Data Users Conference July
12, 2006
28
What is Record Linkage?
Administrative records
NCHS Surveys
Linked Data File
29
NCHS Linked Data Major Activities

Mortality
National Death Index
Health Care Utilization and Costs
Medicare Data
Retirement and Disability
Social Security Data

30
NCHS Linked Data Mortality

Eligibility status
Assigned vital status
Date of death
Age at death
Underlying and multiple causes of death
Adjusted sample weights

31
Research Potential of Linked Mortality Data
The Income-Associated Burden of Disease in the
United States P Muennig, P Franks, H Jia, E
Lubetkin and MR Gold
Excess Deaths Associated with Underweight,
Overweight, and ObesityKM Flegal, BI Graubard,
DF Williamson MH GailJAMA. 20052931861-1867.
Living and Dying in the USA Behavioral, Health,
and Social Differentials of Adult Mortality RG
Rogers, CB Nam, RA Hummer
A Semiparametric Analysis of the Body Mass
Indexs Relationship to Mortality JT Gronniger
32
NCHS Linked Data Medicare

Medicare entitlement and health care utilization
and payment data for 1991-2000
Denominator file
MEDPAR Inpatient hospitalization
MEDPAR Skilled nursing facility
Hospital outpatient
Home Health Care
Hospice
Carrier (physician/supplier Part B file)
Durable Medical Equipment

33
Research Potential ofLinked Medicare Data

Examine risk factors for health conditions
Examine reliability of survey data
Examine survey report of disability with program
participation eligibility criteria
Compare survey reported health conditions to
claims records
Examine disparities in Medicare service
utilization

34
NCHS Linked Data Retirement/Disability

Social Security data from Retirement, Survivors,
and Disability Insurance (RSDI) and Supplemental
Security Insurance (SSI) programs
Master Beneficiary Record (MBR)
1962-2003
Payment History Update System (PHUS)
1984-2003
Supplemental Security Record (SSR)
1974-2003

35
Research Potential of Linked Social Security Data

Examine reliability of survey information for SSA
program participation and benefits
Compare the health characteristics of those who
take early (age 62) Social Security benefits to
those who postpone benefits
Policy analysis using validated survey data
Predicting the number of people who will become
disabled based upon survey reported health
conditions
Determining whether current disability
entitlement funding levels will be adequate as
the population ages

36
Summary NCHS Data Linkage
37
www.cdc.gov/nchs/rd/nchs_datalinkage/data_linkage
_activities.htm
38
Why cant you just give me the data?

NCHS does not own the linked administrative
data
NCHS data confidentiality rules prohibit the
release of potentially identifiable data
special considerations concerning the protection
of linked data
The RDC is the only option for access for now.

39
Overview Data Access Procedures

Proposal Requirements
Access Methods
Helpful Tips
Where to get help?

40
Proposal Requirements

Proposal is evaluated by review committee
Review criteria
Scientific and technical feasibility
Availability of RDC resources
Disclosure risk for restricted information
The extent to which project is in accordance with
the mission of NCHS
Special note NCHS does not try to determine if
proposals are duplicative

41
Proposal Requirements

Cover letter
Project title
Abstract (maximum 300 words summarizing project)
Full contact information
Institutional affiliation
Mail address, phone, email
Dates of proposed time at RDC (or indication of
using remote access)
Source of funding for proposed research

42
Proposal Requirements

Study background
Key study questions or hypotheses
Public health benefits
Methods
Analytic approach and statistical methods
Statistical software requirements
Description of intended output for nondisclosure
review, e.g.
Table shells
Model equations
Test statistics that researcher plans to remove
from RDC

43
Proposal Requirements

Explanation of why restricted data are needed,
e.g. describe why publicly available data are
insufficient
Summary of data requirements to be included in
analytic file
Identification of sample
Identification of variables
Description of additional data to be supplied by
researcher to be merged with NCHS or other data
source (must clearly identify source of other
data)

44
Proposal Requirements Appendices

Current Curriculum Vitae or resume for each
investigator
Data dictionary complete listing of specific
data requested and its source(s) and indicate if
public use or restricted access variables
specific files and years
sample
variables (dependent, independent,
matching/linking)

45
Proposal Requirements Appendices

For remote-access applicants
Description of the computer and email system to
be used to receive output
Security provisions for the computer and email
systems
For students
Letter from department chair or academic advisor
stating that student is working under the
direction of the department

46
Overview RDC Data Access Procedures

Proposal Requirements
Access Methods
Helpful Tips
Where to get help?

47
Access Methods

Once approved, three methods to access restricted
data
on-site - use local computing resources in the
NCHS RDC, Hyattsville, MD
remote submit programs electronically to be
executed in the RDC with output returned by email
staff assisted RDC staff provide on-site
programming for off-site approved researchers
For all methods of access, restricted data files
remain in RDC and output is inspected for
disclosure violations

48
On-Site Access

RDC staff constructs necessary data files,
including merged user data
Most statistical packages available with
sufficient lead time
Output subject to disclosure review
Open only during normal working hours

49
Remote Access Method

RDC staff constructs necessary data files,
including merged user data
SAS programs only (certain procedures and
functions not allowed) additional software
options expected
Both submitted programs and output undergo a
programmed disclosure limitation review

50
RDC Staff-assisted Programming Method

Subcontract with the RDC staff to perform
programming tasks
Useful for those planning to use statistical
software not available for the remote system and
who are not able to travel to the RDC facility
Cost is estimated for each research project

51
Overview RDC Data Access Procedures

Proposal Requirements
Access Methods
Helpful Tips
Where to get help?

52
RDC Helpful Tips

Be clear about research and data requirements
(helps to determine feasibility of project)
Clearly identify the sample to be included in the
analytic file
Provide data dictionaries for both
Public use data
Restricted data
Provide examples of expected output

53
Overview RDC Data Access Procedures

Proposal Requirements
Access Methods
Helpful Tips
Where to get help?

54
Visit the RDC at www.cdc.gov/nchs/rd/rdc.htm
or email rdca_at_cdc.gov
55
LINKED DATA, CONTEXTUAL DATA, and
GEO-CODINGON-SITE and STAFF-ASSISTED DATA ACCESS
Christopher Rogers Research Data
Center cor2_at_cdc.gov
56
Why Link Data Sets?

Improve modeling and make use of existing data.
Compensate for increased difficulties taking
surveys.
Open your mind.
Common Example
Economic variables versus Ethnic variables

57
Historical Trends

More linking of scientific data sets between
government agencies. Confidential Information
Protection and Statistical Efficiency Act of 2002
(CIPSEA.)
Confused political and social situation in US.

58
Quality NCHS Resources

Linked Birth and Infant Death Data with Fetal
Death Data.
Geo-coded NHIS 1986-2003 (2004-2005).
Geo-coded NHANES III.
Cycles 4, 5, and 6 NSFG Contextual Data.
Linked Data Sets described earlier.

59
Linked Birth and Infant Death

Designed to study factors in infant death.
Links birth and death certificates for deaths
under one year of age. Includes fetal deaths for
1995-1997
Years 1983-1991 and 1995-1997
Numerator File (for deceased children) Parental
information and behavior, prenatal care, infant
health variables, demographics, cause of death.
Denominator File (for control group) Parental
information and behavior, prenatal heath, infant
health, demographics.
Fetal Death Data 1995-1997
Restricted Data County/City of mothers
residence or County of childs birth or death
when under 250,000. 100,000 starting 1989.

60
Data Example

From the Division of Vital Statistics. Proposals
or questions can go either to the RDC or the DVS.
Fetal Death Data portion. Given 1989-1999.
Linked to county level contextual data.
Goal to model fetal death with emphasis on ground
water quality. Estimates death rates for each
county.

61
Geo-Coded NHIS

National Health Interview Survey. RDC has access
to files from 1963 to present. Previously
geo-coded households for 1986-1994. Recently
geo-coded by RDC from 1995-2003. 2004-2005
coding in progress.
State (2 digits), County (3 digits), Tract (6
digits), Block Group (1 digit), and Block (3-4
digits) levels. Households coded to 1990 and
2000 Censuses.

62
Geo-Coded NHANES III

NHANES III is also linked to NDI Mortality data.
NHANES III has been geo-coded twice. The RDC has
done it at the same level of detail as NHIS.
Continuous NHANES has not been geo-coded yet.
Example Large project with neighborhood,
economic, ethnic, and individual medical and
behavioral variables. Multi-level models.

63
NSFG Contextual Data

Contextual variables available with Cycles 4, 5,
and 6. Supplied for each individual in sample.
Cycle 6 1054 contextual variables at the state,
county, tract, and block group levels. For
respondent addresses in 2000 and 2002.
Contextual data include both economic and
demographic characteristics of locations. Easily
merged by case ID to individual characteristics,
behaviors, and histories.

64
Simple NSFG Example

A simple example relating economics on state
level, ethnicity, and behavior, but not using
contextual variables.
Treatment States given waiver to offer more
family planning services (FPS).
Questions
FPS effects on behavior
FPS effect on pregnancy rates
Differential impacts across demographic subgroups?

65
Change of Topic Accessing Data

On-site access to data at the RDC in Hyattsville.
Staff-assisted remote access to data via e-mail.
Researchers often use both types of access.
Potential Designated Agent status. (CIPSEA)
The RDC has put many resources into automated
remote access.

66
On-Site Access

Rules in 24 page file GuidelinesRDC11-8-05.pdf
available on-line.
The RDC and NCHS surveys have knowledgeable
professional staffs that review proposals
carefully. Clients can only remove what has been
approved. Checked by staff.
Exploratory Data Analysis. If needed, ask.
Recent example Checking general shapes of
variables for model validity. OKed by survey.
Modeling needs. Recent example Nested
randomized geo-codes.
Estimation problems. Example Single PSU in a
Stratum.

67
Staff-Assisted Remote Access

Analysis done through a particular staff member.
Usually efficient, but could be very busy.
Staff member determines costs based on time.
Staff usually not asked to do much programming.
Staff creates data, runs e-mailed programs,
checks, and returns output to researcher.
Staff can do exploratory analysis, if needed.
Staff can help check modeling problems.
Commonly done after on-site visit.

68
Our Mission

The RDC has a professional staff dedicated to
helping researchers uncover knowledge and advance
understanding.

69
Remote Access System
Vijay Gambhir
70
Remote Access System

Envisioned as an integral Part of RDC
Pre onsite usage
Post onsite usage
Super store/ Convenience store

71
Basics of Remote Access System

Object oriented, event driven system based upon
the principles of distributed computing
About two years of development efforts
Set of applications called in service by resident
component
Advanced pattern recognition techniques

72
Analytic Data Research by Email (ANDRE)

NCHS has been providing remote data access to
researchers through ANDRE since April 1998.
In the past five years, ANDRE has served 45
different data analysts and executed over 9,500
SAS programs for their research programs.

73
Main Features of ANDRE

Completely automated system
Operates round the clock
without any human intervention
Registered subscribers only
Proposals already reviewed and approved
Have an agreement with NCHS/RDC
Unlimited Access during the subscription period

74
Data Requests

Registered user can submit data requests by email
from anywhere and at any time.
Results of the data request released to a
specified email address that has been certified
as secure by the subscriber and approved by
NCHS/RDC.

75
Authentication

Multi-levels of system security
Submission syntax
User id
Password
Email/code word
Package
Path info

76
Data Request Analysis

Compliance with the disclosure limitation
constraints of NCHS
Integrity of the system
Resource constraints (CPU time Storage
requirements)
Protection of ANDREs work environment

77
Prevention of Direct Disclosure

Cleaning up of the Log File
Categorization of SAS commands/words
Forbidden Commands
Modifications to the Commands
Output suppression

78
Sample Original Log

1 options nocenter
2 Data one
3 Infile 'd\nchs\respnd95.dat' lrecl13064
4 Input
5 TODAYSPG 6847-6847
6 CONSTAT1 11934-11935
7 CONSTAT2 11936-11937
8 CONSTAT3 11938-11939
9 CONSTAT4 11940-11941
10 SEX1MTHD 11945-11946
11 POST_WT 12350-12359
12 if constat1 'ab' then vjvar1 else vjvar
2
13 WGT1000POST_WT/1000
14 title 'NSFG cycle 1995'
NOTE Character values have been converted to
numeric values at the places given by
(Line)(Column).
1215
NOTE The infile 'd\nchs\respnd95.dat' is
File Named\nchs\respnd95.dat,

79
Sample Original Log (cont.)

12901 11232521101 0526721310303392181193101
1103 01030000000321120000392702210611511200403
1344 1316
13001 622501001006034
TODAYSPG1 CONSTAT15 CONSTAT288 CONSTAT388
CONSTAT488 SEX1MTHD1 POST_WT2545.7569 vjvar2
WGT10002.5457569 _ERROR_1
_N_20
NOTE 10847 records were read from the infile
'd\nchs\respnd95.dat'.
The minimum record length was 13064.
The maximum record length was 13064.
NOTE The data set WORK.ONE has 10847
observations and 9 variables.
NOTE DATA statement used
real time 39.88 seconds
cpu time 12.10 seconds
15 proc freq
16 tables CONSTAT1 vjvar
17 run

80
Sample Cleaned Log

1 options nocenter
2 Data one
3 Infile 'd\nchs\respnd95.dat' lrecl13064
4 Input
5 TODAYSPG 6847-6847
6 CONSTAT1 11934-11935
7 CONSTAT2 11936-11937
8 CONSTAT3 11938-11939
9 CONSTAT4 11940-11941
10 SEX1MTHD 11945-11946
11 POST_WT 12350-12359
12 if constat1 'ab' then vjvar1 else vjvar
2
13 WGT1000POST_WT/1000
14 title 'NSFG cycle 1995'
NOTE Character values have been converted to
numeric values at the places given by
(Line)(Column).
1215
NOTE The infile 'd\nchs\respnd95.dat' is
File Named\nchs\respnd95.dat,

81
Sample Cleaned Log (cont.)

NOTE 10847 records were read from the infile
'd\nchs\respnd95.dat'.
The minimum record length was 13064.
The maximum record length was 13064.
NOTE The data set WORK.ONE has 10847
observations and 9 variables.
NOTE DATA statement used
real time 39.88 seconds
cpu time 12.10 seconds
15 proc freq
16 tables CONSTAT1 vjvar
17 run
NOTE There were 10847 observations read from the
data set WORK.ONE.
NOTE PROCEDURE FREQ used
real time 0.49 seconds
cpu time 0.04 seconds

82
Forbidden Commands

Commands That Pose Unacceptable Disclosure
Risks
OR
Disallowed to Protect Integrity/Internal
Environment of ANDRE
Add firstobs report iml
Print first. Pctn nofreq
Obs last. Pctsum nocum
Firstobs nocol tabulate editor
Browse summary list put

83
Commands Modification

Modify users program to enforce restrictions on
options allowed with certain SAS procedures to
prevent objectionable info appearing in the
output
PROC MEANS n mean std

84
Output Suppression

Wiping out of extreme values from the output of
Proc Univariate.
Suppressing complete output line (Procs Means,
corr, Univariate, etc) where sample size less
than the minimum acceptable value.

85
Proc Means Suppression

The MEANS Procedure
Variable Label
N Mean Std Dev
--------------------------------------------------
------------------------------------------
EXPEND_R Current expend/pupil in public
schl/1000 5424 5.0830820 1.3958710
Values Suppressed
RPUB87 exp. for contr. serv. and supplies
1997 5424 23472052.60 18806802.86
RPUB92 exp. for contr. serv. and supplies
1997 5424 34800922.98 30481634.59
PRGPRO Coordinated Pregnancy Prevention
Program 1708 0.0679157 0.2516749
HIVED HIV/AIDS Education
1708 3.5146370 0.8044378
Values Suppressed
PRGPRO87 Coordinated Pregnancy Prevention
Program 5424 0.0540192 0.2260764
HIVED87 HIV/AIDS Education
5424 3.4968658 0.8008324
WT_PER15 Wt females aged 15-19/total 15-19
5424 0.7279681 0.1265796
BK_PER15 Bk females aged 15-19/total 15-19
5424 0.1409869 0.0932332
HS_PER15 Hs females aged 15-19/total 15-19
5424 0.0962413 0.1055191
TEENMMC2 Teenmom by cohort (1,2,3r)
1201 1.7119067 0.7715351
C18_2_1S R in C2 (vs 1) at 18-19 endpt (1,2)
1770 1.5248588 0.4995228
TM2_1S18 R tnmm in Coh 2 (vs 1)-age 18 _at_ ext
358 1.4804469 0.5003168

86
Proc Univariate OutputUnsuppressed

The SAS System
9
1409 Sunday, October 24, 1999
Univariate
Procedure
VariableAVHRATET
Moments
Quantiles(Def5)
N 2283 Sum Wgts 2283
100 Max -0.25314 99 -1.62008
Mean -4.66219 Sum -10643.8
75 Q3 -3.56179 95 -2.37588
Std Dev 1.892017 Variance 3.57973
50 Med -4.50491 90 -2.79152
Skewness -2.11919 Kurtosis 6.892929
25 Q1 -5.30374 10 -6.07639
USS 57792.36 CSS 8168.944
0 Min -13.5463 5 -7.19645
CV -40.5821 Std Mean 0.039598
1 -12.7402
TMean0 -117.738 PrgtT 0.0001
Range 13.29321
Num 0 2283 Num gt 0 0
Q3-Q1 1.741949
M(Sign) -1141.5 PrgtM 0.0001
Mode -13.5463
Sgn Rank -1303593 PrgtS 0.0001
Extremes
Lowest Obs
Highest Obs
-13.5463( 1547)
-0.90519( 649)
-13.5397( 1836)
-0.81756( 1094)

87
Proc Univariate OutputSuppressed

The SAS System
9
1409 Sunday, October 24, 1999
Univariate
Procedure
VariableAVHRATET
Moments
Quantiles(Def5)
N 2283 Sum Wgts 2283
100 Max -0.25314 99 -1.62008
Mean -4.66219 Sum -10643.8
75 Q3 -3.56179 95 -2.37588
Std Dev 1.892017 Variance 3.57973
50 Med -4.50491 90 -2.79152
Skewness -2.11919 Kurtosis 6.892929
25 Q1 -5.30374 10 -6.07639
USS 57792.36 CSS 8168.944
0 Min -13.5463 5 -7.19645
CV -40.5821 Std Mean 0.039598
1 -12.7402
TMean0 -117.738 PrgtT 0.0001
Range 13.29321
Num 0 2283 Num gt 0 0
Q3-Q1 1.741949
M(Sign) -1141.5 PrgtM 0.0001
Mode -13.5463
Sgn Rank -1303593 PrgtS 0.0001

88
Proc Univariate OutputSuppressed (sample size
1)

Univariate
Procedure
VariableFREQ (sum) freq
Moments
Quantiles(Def5)
Serious Disclosure limitation Violations
Values too low to release
Output of Proc Univariate withheld

89
Proc Freq Suppression (One-Way Tables)

Suppress at least two consecutive rows to prevent
derivation of suppressed values from cumulative
totals.
Disallow single row output.

90
One-Way Freq TableSuppressed

Cumulative Cumulative
LOGRNTOPAT Frequency Percent
Frequency Percent
--------------------------------------------------
---------------
0.2277839309 ????? ?????
????? ?????
0.2277839309 ????? ?????
????? ?????
0.2305236586 5 0.08
6429 97.99
0.231111721 5 0.08
6434 98.06
0.232058915 ????? ?????
????? ?????
0.232058915 ????? ?????
????? ?????
0.2436220827 ????? ?????
????? ?????
0.2436220827 ????? ?????
????? ?????
0.2498117984 6 0.09
6456 98.40
0.2504106777 6 0.09
6462 98.49
0.2513144283 18 0.27
6480 98.77
0.2595111955 6 0.09
6486 98.86
0.2670627852 ????? ?????
????? ?????
0.2670627852 ????? ?????
????? ?????
0.2736958305 5 0.08
6500 99.07
0.2814124594 5 0.08
6505 99.15

91
One-Way Freq Tablesuppressed (cont.)

Cumulative Cumulative
LOGRNTOPAT Frequency Percent
Frequency Percent
--------------------------------------------------
---------------
0.3403258059 ????? ?????
????? ?????
0.3403258059 ????? ?????
????? ?????
0.3715635564 6 0.09
6537 99.63
0.3856624808 ????? ?????
????? ?????
0.3856624808 ????? ?????
????? ?????
0.6931471806 6 0.09
6550 99.83
1.2527629685 ????? ?????
????? ?????
1.2527629685 ????? ?????
????? ?????
1.2527629685 ????? ?????
????? ?????

92
Proc Freq Suppression (Two-way Tables)

Rows and columns totals preserved
Cells with values less than the acceptable
minimum are suppressed
Additional suppressions to ensure that no row and
no column has single suppression.
Logical stitching of horizontal and vertical
splits.

93
Proc Freq Two-way Tables Suppression