Although there are significant limitations in the utilization
of national data to obtain State-specific information, there are
methods to enhance the data to obtain more accurate State-specific estimates.
James Verdier suggests two methods
for statistically enhancing Current Population Survey (CPS) data in order to increase the reliability
of State-level estimates:
- Reduce the margin of error by increasing sample sizes.
Utilizing 3-year averages can help to smooth out year-to-year variations
in annual survey results, but significant margins of error may remain.
For example, based on 3-year averages from the October 1997 CPS data,
the total number of uninsured in California ranged from 1,466,000 to
1,886,000 and the total number in Delaware ranged from 12,000 to 32,000.
- Pat Purcell (1997) utilizes the 3-year average
technique - Purcell, Patrick. "Health Insurance: Uninsured
Children by State, 1994-1996." October 3, 1997. Congressional
Research Service.
- Increase the sample size in one State by "borrowing" similar
households from other States to increase the reliability of
information regarding subpopulations within the national sample.
Several rules should be followed when employing this method:
- Borrowed households must be similar with respect to age, race,
income, family type, and employment status.
- Relationships between employment characteristics and insurance
coverage must be similar in the borrowing and lending States. For
example, insurance coverage in a State with small employers and
non-unionized employees is very different from coverage in a State
that has mostly large heavily unionized employers.
Mr. Verdier cautioned that while statistical enhancements
of the CPS can provide better information for program planning and design,
and provide better estimates of year-to-year changes in number of low-income
uninsured children than unenhanced data, it involves complex analyses and
the large margins of error and methodological limitations of the CPS will
remain.
Conclusions Regarding the Use of CPS
- State-specific surveys may be more reliable
than CPS, but will not be comparable across all States.
- Statistically enhancing CPS data can
produce more reliable State estimates, but probably not reliable enough
to track the impact of SCHIP on the number of uninsured children. The
precise State-by-State impact of SCHIP on the number of uninsured
children will likely remain unknown.
- Implications for States
- Review and utilize CPS, Urban Institute,
the Community Tracking Survey, and other surveys.
- Carefully consider what accountability
requirements exist Federally and within your own State when planning
for data collection.
Related
Questions
Show me
other SCHIP Workshop presenter-suggested strategies
What other
issues are talked about in this section?
What led
to this?
What other
methodological issues are discussed?
Who presented this
material?
[Top of Page]