Analyzing MEPS Survey Data in
STATA
Question: One
analyst examines MEPS data on total health expenditures by taking the mean of
all observations without considering any differences across observations in the
sample. A second analyst uses a
statistical procedure, which incorporates information on the MEPs sample.
The MEPS survey includes stratification,
clustering, multiple stages of selection, disproportionate sampling, and
reflects both adjustments for survey nonresponse and controls from the Current
Population Survey.
Present the code the two analysts used to
estimate means of key expenditure and key health care utilization variables
using STATA.
How do point estimates of the mean expenditure
and mean utilization variables differ for the two procedures?
How do standard error estimates differ for the
two procedures?
Discuss implication on the choice of procedures.
Code for
two procedures:
The STATA code used to estimate simple averages
for the expenditure variables is presented below.
mean TOTEXP15 ERTEXP15 IPTEXP15 RXEXP15 DVTEXP15
The STATA code needed for the complex survey
design involves a statement declaring the survey design and a statement invoking
the procedure.
svyset varpsu [pweight=PERWT15F], strata(varstr)
vce(linearized) singleunit(missing)
svy linearized : mean TOTEXP15 ERTEXP15 IPTEXP15
RXEXP15 DVTEXP15
Results
for Expenditures and Utilization Variables:
Impact of MEPS Survey Design on Expenditure and Utilization
Estimates


Expenditure Variables


Random Unweighted Sample

MEPS Survey Design


Mean

Std. Err.

Mean

Std. Err.


Total

4171.1

74.6

4977.6

134.4

ER

190.7

6.6

212.2

12.6

In Patient

1146.9

49.9

1326.0

79.1

RX

965.7

24.7

1160.5

48.4

Dentist

241.2

4.7

298.4

7.6

Utilization (Number of Visits)


Random Unweighted Sample

MEPS Survey Design


Mean

Std. Err.

Mean

Std. Err.


ER

0.202

0.0033

0.203

0.0055

In Patient

0.082

0.0021

0.091

0.0035

RX

9.328

0.1078

10.611

0.2112

Dentist

0.793

0.0080

0.952

0.0166

A second table comparing random unweighted means
to survey means for all variables and random unweighted standard errors to
survey standard errors for all expenditure and utilization variables was
created to facilitate analysis.
Comparisons of Random Unweighted Statistics to
MEPS Survey Design Statistics


Random Mean to Survey Mean

Random Standard Error to Survey Standard Error


Total

1.19

1.80

ER

1.11

1.91

In Patient

1.16

1.58

RX

1.20

1.96

Dentist

1.24

1.63

Utilization Variables


Random Mean to Survey Mean

Random Standard Error to Survey Standard Error


ER

1.00

1.67

In Patient

1.10

1.69

RX

1.14

1.96

Dentist

1.20

2.07

Observations:
The
expenditure and utilization means are larger when the survey design information
is included. The range of difference is
11 to 24 percent for expenditure variables and 0 to 20 percent for utilization variables.
The
standard error of all estimates is much larger when the MEPS survey design
procedure is used. The differences range
from 58 percent to 96 percent for expenditure variables and from 67 to 107
percent for utilization variables.
Concluding Thought: Analysts who use simple averages
rather than averages that incorporate information in the MEPS survey design
will understate health care expenditure and utilization. More importantly, the simple averages
understate the standard error or overstate the precision of their
estimates. This could lead analysts to
incorrectly reject a null hypothesis.
Authors Note: I am using the MEPS databases
to analyze health care trends and provide insight into different policy
proposals. The following post looks at
data from both the 2005 and 2015 MEPS surveys.
The
statistics show that growth in RX expenditures have outpaced growth in total
health care expenditures. Interestingly,
there was little increase in the utilization of prescription drugs.
This
analysis leads me to the conclusion that it will be hard to control health care
costs and fix insurance markets without restraining growth in drug prices.
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