The Utility of the Integrated Design of the Medical Expenditure 

Panel Survey (MEPS) to Inform Trends in Nonresponse1 

Frances M. Chevarley, Ph.D. 

Karen E. Davis, M.A. 

Agency for Healthcare Research and Quality 

Department of Health and Human Services 

540 Gaither Road, Rockville, MD 20850 

Proceedings ofthe 2013 Federal Committee on Statistical Methodology (FCSM) Research Conference 

Abstract 

This paper analyzes estimates from the Medical Expenditure Panel Survey (MEPS) matched with the National 

Health Interview Survey (NHIS) and uses practical tools to inform MEPS nonresponse estimates. MEPS is a 

nationally representative panel survey studying health care use, access, expenditures, source of payment, insurance 

coverage, and qua I ity of care. Each year a new panel begins and each panel has 5 rounds ofdata collection over 2 Yi 

years that cover a two-year period. 

The goal ofthis paper is to infonn trends in MEPS nonresponse. Because MEPS uses the NHIS, conducted by the 

National Center for Health Statistics as its sampling frame, estimates are produced using variables from both the 

NHIS and MEPS across different categories ofthe MEPS response categories. Data used are from the 2009-20 lO 

NH IS data matched with the 20l0-2011 MEPS files along with additional paradata. Non-response rates are analyzed 

by standard demographic categories and MEPS response categories. 

Key Words: MEPS, NJHS, nonresponse 

1. Introduction 

Because nonresponse rates were increasing for the MEPS Household component (MEPS-HC), an incentive 

experiment was conducted with the MEPS panel that began in 2008 (Panel 13) for the entire 5 rounds ofMEPS. 

Incentives of$30, $50, and $70 were tested. Because of favorable results, OMB approved an increase in the 

incentive from $30 that MEPS had been using to $50 starting with the Panel that began in 2011(Panel16). 

For this paper we compare the MEPS-HC nonresponse rates for the Panel that began in 2011 (Panel 16) that had the 

increased incentives, with the panel that began in 20 I 0 before the incentive increase. We analyze characteristics of 

people who could be affected by the increased incentive using NHIS variables. Since NHIS is a sampling frame for 

MEPS, there is a wealth of information about the sampling frame for both MEPS responders and nonresponders. 

Our research questions are: did nonresponse rates change from 20 I 0 to 2011 overall and for subgroups; and did the 

significance of predictive variables for nonresponse vs. a reference group change from 20 I 0 to 2011. 

2. Background 

The Medical Expenditure Panel Survey (MEPS) is a nationally representative longitudinal survey that collects 

detailed information on health care utilization and expenditures, health insurance, and health status, as well as on a 

wide variety ofsocial, demographic, and economic characteristics for the U.S. civilian noninstitutionalized 

population. MEPS's main sponsor is the Agency for Healthcare Research and Quality. The MEPS has three 

1 The views in this paper are those of the authors and no official endorsement by the Department of Health and 

Human Services or the Agency for Healthcare Research and Quality (AHRQ) is intended or should be inferred. 
components: the Household component, the Medical Provider component, and the Insurance component. The 

MEPS-HC collects medical expenditure data at both the person and family levels. The MEPS-HC uses an 

overlapping panel design in which, for each panel, data are collected covering a two year period by a series of five 

in-person interviews over the course oftwo-and-a-half years. Full year public use files are based on Rounds 1-3 data 

for that year's panel and rounds 3-5 ofthe previous year's panel. 

The MEPS-HC panels of households (Panels 15 and 16, respectively) are subsamples ofresponding households 

from the prior year of another large ongoing U.S. health survey, the National Health Interview Survey (NHTS) 

conducted by the National Center for Health Statistics. The NHIS sampling frame provides a nationally 

representative sample of the U.S. civilian non-institutional population and reflects an over sampling of Hispanics, 

Blacks and Asians. rn addition in 20 I 0 and 2011 MEPS oversampled Asians, Hispanics, and Blacks. 

Figure !demonstrates MEPS overlapping panel design for MEPS Panels 15 that began in 2010 that had an incentive 

of$30 and Panel 16 that began in 2011 and with an incentive of$50. The 2010 MEPS uses the 2009 NHIS as its 

sampling frame. The 2009 NHIS is fielded in 2009 and the 2010 MEPS is fielded in 20 I 0, 20 I I and part of 2012. 

The 5 interviews in MEPS cover the 2-year reference period of20 I 0 and 20 I I. The overlapping panel design 

demonstrates that the second year of the 20 I 0 MEPS panel and the first year ofthe 201 I MEPS panel both cover the 

2011 period. 

Figure 1: MEPS-HC Overlapping Panel 

Design with NHIS 

M E P S Panel 15 

2 010-20 11 

NHIS R ound 1 2 

2009 

NHIS 

2010 

1/:::-------___ 

Rou d 3 Round 4 Round 5 

R o und 1 R o und 2 R o u d 3 Round 4 Round 5 

-------------- M E P S Pan--------

el 16 

2 0 11- 20 12 

3. Methods/Data 

The MEPS sampling frame is based on NHIS responding households (Figure 2). The MEPS sample is selected from 

its sampling frame, and the remaining households in the MEPS sampling frame are not in the MEPS sample. Once 

MBPS has its sampled households, then there are the MEPS Round 1 responding households versus the MEPS 

Round 1 nonresponding households. For our study we focused on Round 1 nonresponse and measured Round 1 

nonresponse at a person level to be sampled persons who were in round 1 ofthe current year and did not have a 

positive weight on the MEPS-HC point-in-time file (PIT) for that year. The MEPS- HC PIT for a given year includes 

data for Round 1 of that year's panel and data for Round 3 of the previous year's panel. We are using round I 

persons with a positive weight. 
Figure 2: MEPS Survey Frame from NHIS 

Frnme from 

NHIS 

On Mf: PS 

Survey Frame 

Not in MEPS 

Sample 

Not on MEPS 

Survey 

Frame 

MEPS 

Round I 

Res1..ond.eut 

MEPS 

Round l 

Nonrespondent 

The sizes for the 20 I 0 MEPS-HC cases included in our study are as follows. Ofthe 88,446 persons on the 2009 

NHJS file, 32, 171 persons were on the MEPS sampling frame (leaving 56,275 not on the MEPS sampling frame). Of 

the 32, 171 persons on the MEPS sampling frame, 22,906 persons were sampled (and 9,265 were not sampled). Of 

the 22,906 persons that were sampled, we didn't have complete linkage information for 30 which were excluded. An 

additional 4,774 persons in Primary Sampling Units (PSUs) that were involved in another MEPS study were also 

excluded. This resulted in 18, 102 sampled persons for the 2010 MEPS-HC used in our analyses, ofwhich 13,201 

persons were responding persons, and 4,901 persons were nonreponding. 

The sizes for the 2011 MEPS-HC cases included in our study are as follows. Of the 89,976 persons on the 2010 

NHIS file, 3 1,282 persons were on the MEPS sampling frame (leaving 58,694 not on the MBPS sampling frame). A 

sample of26,640 persons were selected from the 31,282 persons on the MEPS sampling frame (4,642 were not 

sampled). Of the 26,640 persons that were sampled, we didn't have complete linkage information for 23 which were 

excluded. An addition 5,708 persons in PSUs that were involved in another study were excluded. This resulted in 

20,909 persons for our study of which 16,380 were responding persons and 4,529 were nonresponding persons. 

For our study the 2009 and 2010 NHIS public use files were merged with the MEPS 2010 and 2011 point in time 

(PIT) files and with the NHIS and MEPS paradata files. The MEPS PIT file has round 1 data for the current panel 

and round 3 data of the previous panel. We are using the round I data ofthe current panel in both the 2010 and 2011 

PIT files. We defined Round 1 nonresponse at a person level to be sampled cases who were not MEPS PIT Round I 

responders. Our estimates are weighted estimates where we start with the NHIS weights and multiply them by the 

inverse ofthe M EPS probability ofsample selection. 

We have three separate analyses in our study. First we calculated and compared person-level nonresponse rates by 

standard demographic and socioeconomic groups using 20 I 0 and 20 I 1 MEPS linked to the NHIS data. 

Next we modelled (again using 2010 and 2011 MEPS linked to the NHIS data) nonresponse as the outcome variable 

based on a logistic regression model for binary outcomes. The model says that P, the probability of response is 

related to the covariates X by a logistic regression equation: 
where P = prob(Y= l lX) = E(YIX). The regression coefficient estimates ("betas") model effect of covariates on logodds that Y= I (Nonrespone). 

For the second analyses we modeled nonresponse for each of demographic/socioeconomic variables separately 

(single predictors ofnonresponse); models were run for 2010 and 2011. For our third analyses we modeled 

nonresponse with all ofthe socioeconomic variables in the model together (multiple predictors of nonresponse); 

models were run for 2010 and 2011. Our nonresponse analyses is at the person level. This is a little different from 

usual nonresponse models that are at the household responding unit level. The demographic, socioeconomic status 

and paradata variables used are shown in Figure 3. 

Fi2ure 3: Research Variables Used 

Demogr aphic SES 

Age Poverty Rate 

Paradata 

NHIS completeness 

status 

Sex Health insurance 

coverage 

Region Family health care 

spending 

Race/Ethnicity 

# kids in RU 

# Adults in RU 

Born in US 

U.S. Citizenshio 

Health Status 

Important demographic NHIS variables we used include Age, Sex, Region, Race/Ethnicity (Hispanic, non-Hispanic 

Black, non-Hispanic White, Other), Number of children (0 versus at least I child), Number of adults (I adult versus 

2 or more adults), whether born in the U.S., whether a U.S. citizen, and reported health status where the responses 

were combined into the two categories excellent/very good/good and fair/poor health. In addition we included 

poverty rate using 4 categories of percents ofthe federal poverty level ([0,200), [200,300), [300,400), and 400+); 

health insurance coverage using 4 categories (Any private, Public only, Other, and Uninsured); and family health 

care spending using 4 categories (zero, (0,$2000), [$2000, $3000), $3000+). The NHIS paradata variable ofwhether 

or not the NHlS completed interview was partially complete versus fully complete was also included in our model. 

4. Results 

First analyses: From 2010 to 2011 the MEPS overall nonresponse rate had a relative percent decrease of 17.4 

percent from 29.4 percent for 20 I 0 to 24.3 percent for 2011 . As shown in Table I, nonresponse decreased across alI 

subcategories ofour variables with only the following exceptions: ages 65-84; ages 85 and over; the Midwest; nonHispanic other; non-citizens, those in the [200,300) poverty category; and those whose health care spending was 

greater than zero to $ J',999, or went from $2,000 to $2,999. 

Second and third analyses: Our second analyses involved modeling nonresponse for each ofthe variables separately 

(single predictors ofnonresponse) for both 20 10 and 2011. Our third analyses modeled nonresponse with the 

variables combined into the same model (multiple predictors ofnonresponse). 

Figures 4 and 5 include summaries ofthe single predictor of nonresponse and the multiple predictor of nonresponse 

models. One research question was to determine the variable categories whose significance ofthe odds ratios (ORs) 

(versus the reference group) changed from 20 I 0 to 2011. These tables only provide those variables in which the 

significance ofthe ORs versus the reference group changed from 2010 (before the increased incentive) to 2011 (the 

first year ofthe increased incentive) for one ofits categories. The ORs comparing a category with the reference 

group and 95 percent confidence intervals for the ORs are shown. ORs significantly different than 1 :00 in a given 

year are indicated with an asterisk; highlighting indicates the categories in which the ORs' significance level 

changed from 2011 to 2012. 
Fie:urc 4: Odds Ratios and 95 Percent Confidence Intervals for the Single Predictors of Nonresponse 

Variable 2010 2011 Variable 2010 2011 

Age Poverty Rate 

0-17 0.82*(0.74,0.91) 0.77*(0.68),0.86 10.200) 0.59*(0.50,0. 71) 0.54*(0.46,0.62) 

18-24 1.05(0.89,1.23) 1.09 (0.96,1.24) 1200,300) 0.60*(0.48,0. 75) 0.66*(0.55,0.80) 

25-64 1.00 1.00 1300,400) 0.84 (0.68,1.02) 0.73*(0.59)>.92) 

65-84 0.93 (0.79,1.09) 1.03 (0.90,1.18) 400+ 1.00 1.00 

85+ 1.29(0.94, 1.78) l.45*(1.13,1.86) 

Health Ins Cov 

Any Private 1.00 1.00 

U.S. Citizenship 

Yes l.00 1.00 Public Only 0.68*(0.57,0.81) 0.55*(0.47,0.65) 

No 0.80*(0.66,0.97) 0.84 (0.70,l.Ol) Other 0.89 (0.69, l.14) 0.69*(0.53,0.90) 

Not Covered 0.81 *(0.70,0.94) 0.68*(0.57,0.80) 

Health Status 

E,VG,G 1.00 1.00 

Fair/Poor 0.84(70,1.00) 0.79*(0.68,0,93) 

*Indicates significance at 0.05. Highlighting indicates changes in significance from 20 I 0 to 2011 . 

As shown in Figure 4, the age, U.S. Citizenship, Health Status, Poverty Rate, and Health Insurance Coverage had 

categories whose significance with respect to the reference group for the single predictors of nonresponse models 

changed from 2010 to 2011. In 2010, persons ages 85 and over were not significantly different than those ages 25-64 

(the reference group) in being a nonresponder. In 2011, however, those ages 85 and over were more likely to be a 

nonresponder than those ages 25-64. 

In 2010 Noncitizens were less likely than Citizens (the reference group) to be nonresponders, but in 2011 they are 

not significantly different than Citizens in being nonresponders. 

In 20 I 0 those reported to be in fair or poor (F/P) health were not significantly different than those reported to be in 

Excellent/Very Good/Good (E/VG/G) health. Th.is changed in 2011 where those in F/P health were less likely to be 

a nonresponder than those in E/VG/G health. 

In 20 I 0, those in the category 300 to less than 400 percent of the federal poverty level were not significantly 

different than those in the highest level (the reference group) in being a nonresponder, but in 2011 they are less 

likely than those in the highest level to be a nonresponder. 

Persons with Other insurance changed from being not significantly different than those with Any Private (the 

reference group) in 2010 to in 2011 being less likely to be a nonresponder than those with Any Private. 

Figure 5 below provides the summary ofresults for the multiple predictors model. As shown in Figure 5, Age, 

Region, Health Insurance Coverage, and Health Care Spending had categories whose significance with respect to the 

reference group changed from 20 I 0 to 2011 after adj usting for the other variables in the model. 

Fhmre 5: Odds Ratios and 95 Percent Confidence Intervals for the Multiple Predictors of Nonresoonse 

Variable 2010 2011 Variable 2010 2011 

Age Health Ins Cov 

0-17 1.02 (0.93,1.12) 1.04(0.93, 1.15) Any Private 1.00 1.00 

18-24 U1 (I.00,1.36) 1.22*( 1.06, 1.41) Public Only 0.89(0)2,1.lO) 0.67*(0.55,0.8 1) 

25-64 1.00 1.00 Other 1.21 (0.90, 1.63) 0.86(0.63,1.17) 

65-84 0.93 (0.78,1.12) 1.05(0.89,1.25) Not Covered l.05 (0.89, 1.23) 0.83 (0.68, 1.02) 

85+ 1.23 (0.85,1.78) l .56*(1.18,2.08) 
Region 

Northeast 1.08 (0.81, 1.45) 1.11 (0.83,1.47) 

Health Care 

Spending 

Zero 1.19(0.93,1 .52) 1.04(0.83,1 .30) 

Midwest 0.86(0.65,1.14) 1.08 (0.81,1.44) (0,$2000) 1.03 (0.77,1.39) 1.23 (0.92, 1.66) 

South 1.19 (0.96,1.48) 

1.00 

1.35*( 1.06, l.70) 

1.00 

J$2000,$3000) 

$3000+ 

1.00 1.00 

West 2.04*(1.36,3.06) 1.27 (0.84,1.91) 

*Indicates significance at 0.05. Highlighting indicates changes in significance from 2010 to 2011. 

After adjusting for the other variables in the model, the odds ratio for persons ages 18-24 and ages 85 and over 

versus those ages 25-64 (the reference group) went from being not significant in 20 I 0 to having odds ratio in 20 l I 

significantly greater than one. That is, in 2011, persons ages 18-24 and ages 85 and over were more likely to be 

nonresponders than those ages 25-64. None of the other regions were significantly different than the West (the 

reference group) in being a nonresponder in 2010. However, the South, which was not significantly different than 

the West in being a nonresponder in 2010, was more likely to be a nonresponder than the West in 2011. 

In 2010, none ofthe other health insurance categories were sign ificantly different than those with Any private 

insurance coverage (the reference group). But in 20 I I, those with Public only were less likely than those with Any 

private to be a nonresponder. In 20 I 0, those with family health care spending of$3,000 or more were more likely 

than those with health care spending from $2,000 to less than $3,000 (the reference group) to be a nonresponder. But 

with the increased incentive in 2011 , persons with family spending of$3,000 or more were not significantly 

different in being a non-responder than those with health care spending from $2,000 to less than $3,000. 

5. Summary 

Our first analyses determined whether nonresponse rates decreased between 20 l 0 (the year before the incentive 

increase) and 2011 (the year in which incentives increased.) With the increased incentives in 201 I, nonresponse 

rates had a relative percent decrease of 17.4 percent and decreased for almost all ofthe subcategories of Age, Sex, 

Region, Race/Ethnicity, # Kids in the responding unit,# of adults in the responding unit, whether born in the United 

States, U.S. Citizenship status, Health Status, Poverty Rate, Health insurance coverage, Family Health Spending, 

and whether or not the NHIS completed interview was a partially complete versus fully complete (there wete only 8 

exceptions). The nonresponse rates did not decrease significantly from 20 l 0 to 2011 for those ages 65-84; those 

ages 85 and over; those living in the Midwest, those in the non-Hispanic other category, those who were not citizens 

ofthe United States, those whose family income was 200 percent to Jess than 300 percent ofthe poverty rate, those 

whose yearly health care spending was greater than zero and less than $2000, and those whose health care spending 

was $2000 or more but Jess than $3000. 

Our second and third analyses involved modeling nonresponse for each of variables separately (single predictors of 

nonresponse) for both 2010 and 2011 and then modeling nonresponse with the variables combined into the same 

model controlling for the other variables (multiple predictors of nonresponse) for both 20 10 and 2011. 

Figure 6: Summary of Single Predictors of Nonresponse Models 2010 to 

2011 

Categories 2010 2011 

25-64 (ref grp) vs. 85+ n.s. lower 

US citizens (ref grp) vs. 

non-citizens higher n.s. 

Fair/poor health vs. El VG 

I G (ref 2:rp) n.s. lower 

1300,400) vs. 400+ (ref grp) n.s. lower 

Other HI vs. Any private 

(ref grp) n.s. lower 
When the variables were modelled separately we found 5 categories whose significance with respect to the reference 

group changed from 20 10 to 2011 (Figure 6). Those ages 25-64 versus those ages 85 and over were not significantly 

different in being nonresponders in 2010, but in 2011 they were less likely to be nonresponders. United States 

'citizens were more likely than non-citizens to be nonresponders in 2010 but were not significantly different than 

non-citizens in 2011. Those with fair or poor health were not significantly different in being a nonresponder in 20 I 0 

than those in excellent/very good/ good health status but were less likely to be nonresponsers in 2011. Those with 

federal poverty level of 300 percent to less than 400 percent of the federal poverty level were not significantly 

different in being a nonrespondcr in 20 I 0 than those in the highest group of 400 percent or more of the federal 

poverty level; in 2011 those in the [300,400) federal poverty level group were less likely than those in the highest 

group of 400 percent or more of the federal poverty level. Those with Other health insurance versus Any private 

insurance were not significantly different in being nonresponders in 2010, but in 2011 they were less likely to be 

nonresponders. 

Figure 7: Summary of Multiple Predictors of Nonresponse Models 2010 

to 2011 

Categories 2010 2011 

25-64 (refgro) vs. 18-24 n.s. Lower 

25-64 (refgrp) vs. 85+ n.s. Lower 

West (ref2ro) vs. South n.s. Lower 

Public only vs. Any private 

(ref !!ro) n.s. Lower 

$3000+ vs. f$2000,$3000) Higher n.s. 

After controlling for the other variables the significance of the predictive variable categories changed between 20 I 0 

and 2011 for five groups from our multiple predictor model. Persons ages 25-64 were not significantly different 

than those ages 18-24 years and those ages 85 and over in being a nonresponder in 2010, but in 2011 there were less 

likely than those ages 85 and over in being a nonresponder. Persons in the West were not significantly different 

from persons in the South in being a nonresponder in 20 I 0, but in 2011 they were less likely to be a nonresponder 

than those in the South. Persons with Public only health insurance were not significantly different than those with 

Any private health insurance in being a nonresponder in 20 I 0 but in 2011 they were less likely to be a nonresponder 

than those with Any private insurance. People whose health care spending was $3000 or more were more likely to 

be a nonresponder than those with health care spending of $2000 to less than $3000 in 20 I 0, but in 2011 there was 

no significant difference in their likelihood of nonresponse. 

In conclusion we observed relative percent decreases in nonresponse rates overall and for almost all of the 

subgroups. We also observed changes in significance of predictive variables for nonresponse versus a reference 

group from 20 I 0 to 20 I I. These are preliminary analyses. Additional analyses exploring the effects ofthe increased 

incentive on the different dimensions of nonresponse can be further investigated. These dimensions could include 

levels of cooperation, refusal rates, level of effort as well as possible changes in the quality of the collected data. 

Although the incentive increase between 20 lO and 2011 more than likely explains most of these changes in 

nonresponse rates, there may be other documented and undocumented changes in field procedures or in the survey 

climate between 2010 and 2011 that may explain some of these changes. For example in 201 l in another effort to 

increase the response rates, the round I field period was lengthened and this could partly explain some of the 

observed changes. 
Table 1: Estimated weighted nonresponse rates for the Medical Expenditure Panel Survey by demographic characteristics, 

U.S. 2010-2011 2i.

2010 2011 

2009 to 

2010 NR 

Non-responders Non-responders z-test 

var_item resplvl colper_ secol_2 LB95 UB95 colper_2 secol_2 LB95 UB95 

Age TOTAL 29.4 0.86 27.8 :H.1 24.3 0.72 22.9 25.7 -4.59 

0-17 years 26.3 1.32 23.8 28.9 20.3 1.10 18.2 22.5 -3.50 

18-24 years 31.4 1.80 27.9 34.9 26.7 1.43 23.9 29.5 -2.05 

25-64 years 30.4 0.92 28.5 32.2 25.0 0.79 23.4 26.5 -4.43 

65-84 years 28.9 1.57 25.8 31.9 25.6 1.27 23.1 28.1 -1.63 

years and older 3.68 28.8 43.3 32.6 2.74 27.2 37.9 --0.76 

Sex male 0.96 28.5 32.3 25.0 0.83 23.4 26.7 -4.23 

female 0.87 26.8 30.2 23.6 0.70 22.3 25.0 -4.36 

Region Northeast 2.37 28.3 24.6 1.89 20.9 28.3 -2.73 

·Midwest 1.92 22.2 23.2 1.60 20.1 26.4 -1.10 

South 1.28 28.4 33.4 26:0 1.02 24.0 28.0 -3.01 

West 28.1 1.58 25.0 31.2 22.2 1.64 18.9 25.4 -2.60 

Race/Ethnicity 1: Hispan 24.3 1.56 21.3 27.4 18.0 0.91 16.2 19.7 -3.53 

2: NHwhi 32.1 1.11 29.9 34.3 26.8 0.91 25.0 28.6 -3.66 

3: NH Bia 20.3 1.39 17.5 23.0 16.5 1.24 14.l 19.0 -2.00 

4: NH 0th 27.8 2.38 23.2 32.5 26.2 2.39 21.5 30.8 --0.50 

Number of children None 32.3 1.00 30.4 34.3 27.7 0.92 25.9 29.5 -3.39 

One or more 27.0 1.14 24.7 29.2 21.4 0.99 19.5 23.4 -3.65 

Number of adults One 27.0 1.33 24.4 29.6 22.7 1.07 20.6 24.8 -2.51 

Two or more 30.0 1.00 28.1 32.0 24.7 0.84 23.1 26.4 -4.08 

U.S. Born Yes 29.6 0.90 27.8 31.3 24.3 0.77 22.8 25.8 -4.45 

No 27.8 1.33 25.2 30.4 23.4 1.13 21.2 25.6 -2.51 

Citizenship Yes 29.6 0.87 27.9 31.3 24.3 0.74 22.9 25.8 -4.60 

No 25.1 1.86 21.4 28.8 21.3 1.53 18.3 24.2 -1.59 

Poverty level GE 0 and LT 200 24.5 1.29 22.0 27.0 19.2 0.88 17.4 20.9 -3.44 

GE 200 and LT 300 24.7 1.82 21.2 28.3 22.6 1.54 19.5 25.6 --0.91 

GE 300 and LT 400 31.4 2.02 27.4 35.3 24.5 1.85 20.9 28.1 -2.52 

GE 400 35.4 1.34 32.8 38.0 30.7 1.24 28.2 33.1 -2.59 

Health care 

spending/year Zero 29.5 1.01 27.5 31.5 23.4 0.80 21.9 25.0 -4.72 

Gt Oto less than $2,000 . 27.4 2.33 22.8 32.0 27:4 2.33 22.8 32.0 0.00 

GE $2,000 to than $3,000 26.4 2.15 22.2 30.6 24.1 1.93 20.3 .P..

-0.79 

GE $3,000 47.8 4.00 40.0 55.6 36.4 4.09 28.4 44.4 -2.00 

Health status 1: Exe, VG, G 29.7 0.91 28.0 31.S 24.7 0.76 23.2 26.2 -4.28 

2: Fair, Poor 26.3 1.65 23.0 29.5 20.6 1.21 18.3 23.0 -2.75 

Fully vs Partially 

completed NHIS 

interview Fully completed NHIS int- 26.2 0.89 24.5 28.0 20.3 0.70 18.9 21.7 -S.25 

Partlally completed NHIS int. 40.9 1.69 37.6 44.2 33.4 1.56 30.3 36.4 -3.27 

Health insurance 

coverage Any private 31.4 0.96 29.5 33.3 27.5 0.92 25.7 29.3 -2.89 

Public only 23.7 1.63 20.5 26.9 17.3 1.07 15.2 19.4 -3.25 

Other 28.9 2.59 23.9 34.0 20.7 2.07 ll6.7 24.8 -2.47 

Uninsured 27.1 1.49 24.19 30.04 20.4 1.31 17.86 23.00 -3.36 

1Nonresponse is round 1 nonresponse at the person level and is defined as MEPS sampled persons who do not have a positive 

weight on the MEPS -HC point-in-time (PIT) file for that year. A30 

2For the 2010 file, 30 persons were excluded because of matching issues and 4,774 persons were excluded because they were in 

Primary Sampling Units were involved in another MEPS study resulting in 18,102 persons on this file. For the 2011 file, 23 

persons were excluded because of matching issues and 5,708 persons were excluded because they were in Primary Sampling 

Units that were involved in another MEPS study resulting in 20,909 persons on this file.