Sunghee Lee

Exploring nonresponse bias in a health survey using neighborhood characteristics.

OBJECTIVES We examined potential nonresponse bias in a large-scale, population-based, random-digit-dialed telephone survey in California and its association with the response rate. METHODS We used California Health Interview Survey (CHIS) data and US Census data and linked the two data sets at the census tract level. We compared a broad range of neighborhood characteristics of respondents and nonrespondents to CHIS. We projected individual-level nonresponse bias using the neighborhood characteristics. RESULTS We found little to no substantial difference in neighborhood characteristics between respondents and nonrespondents. The response propensity of the CHIS sample was similarly distributed across these characteristics. The projected nonresponse bias appeared very small. CONCLUSIONS The response rate in CHIS did not result in significant nonresponse bias and did not substantially affect the level of data representativeness, and it is not valid to focus on response rates alone in determining the quality of survey data.

Estimation for Volunteer Panel Web Surveys Using Propensity Score Adjustment and Calibration Adjustment

A combination of propensity score and calibration adjustment is shown to reduce bias in volunteer panel Web surveys. In this combination, the design weights are adjusted by propensity scores to correct for selection bias due to nonrandomized sampling. These adjusted weights are then calibrated to control totals for the target population and correct for coverage bias. The final set of weights is comprised of multiple components, and the estimator of a total no longer takes a linear form. Therefore, approximate methods are needed to derive variance estimates. This study compares three variance estimation methods through simulation. The first method resembles what is used in commercial statistical software based on squared residuals. The second approach uses a variance estimator originally derived for the generalized regression estimator. The third method uses jackknife replication. Results indicate bias reduction is crucial for valid variance estimation and favor the replication method over the other approaches.

Interview language: a proxy measure for acculturation among Asian Americans in a population-based survey.

We examined health status and access to care among Asian Americans by the following acculturation indicators: nativity, percent lifetime in the US, self-rated English proficiency, and interview language, to assess whether any measure better distinguishes acculturation. Data from the 2003 California Health Interview Survey were used to study the sample of 4,170 US-born and foreign-born Asians by acculturation indicators. We performed t-tests to compare differences in demographics, health status and behaviors, and access to care between the foreign-born and US-born Asians, and between various classifications within foreign-born and the US-born Asian group. Our results showed that foreign-born Asians who interviewed in English more closely resembled US-born Asians than foreign-born Asians who interviewed in languages other than English. Compared to interview language, dichotomizing the sample by other acculturation indicators showed smaller differences between the divided groups. Interview language may serve as a better measure for acculturation especially among foreign-born populations with a high proportion of limited English proficiency. In immigrant public health research studies, interview language may be used as an important covariate for health disparities.

Growing Cell‐Phone Population and Noncoverage Bias in Traditional Random Digit Dial Telephone Health Surveys

OBJECTIVE Examine the effect of including cell-phone numbers in a traditional landline random digit dial (RDD) telephone survey. DATA SOURCES The 2007 California Health Interview Survey (CHIS). DATA COLLECTION METHODS CHIS 2007 is an RDD telephone survey supplementing a landline sample in California with a sample of cell-only (CO) adults. STUDY DESIGN We examined the degree of bias due to exclusion of CO populations and compared a series of demographic and health-related characteristics by telephone usage. PRINCIPAL FINDINGS When adjusted for noncoverage in the landline sample through weighting, the potential noncoverage bias due to excluding CO adults in landline telephone surveys is diminished. Both CO adults and adults who have both landline and cell phones but mostly use cell phones appear different from other telephone usage groups. Controlling for demographic differences did not attenuate the significant distinctiveness of cell-mostly adults. CONCLUSIONS While careful weighting can mitigate noncoverage bias in landline telephone surveys, the rapid growth of cell-phone population and their distinctive characteristics suggest it is important to include a cell-phone sample. Moreover, the threat of noncoverage bias in telephone health survey estimates could mislead policy makers with possibly serious consequences for their ability to address important health policy issues.

Increasing Cell Phone Usage Among Hispanics: Implications for Telephone Surveys

OBJECTIVES We examined whether the widespread assumption that Hispanics are subject to greater noncoverage bias in landline telephone surveys because they are more likely than other ethnic groups to use cell phones exclusively was supported by data. METHODS Data came from the 2010 National Health Interview Survey and the 2009 California Health Interview Survey. We considered estimates derived from surveys of adults with landline telephones biased and compared them with findings for all adults. Noncoverage bias was the difference between them, examined separately for Hispanics and non-Hispanic Whites. RESULTS Differences in demographic and health characteristics between cell-only and landline users were larger for non-Hispanic Whites than Hispanics; cell usage was much higher for Hispanics than non-Hispanic Whites. The existence, pattern, and magnitude of noncoverage bias were comparable between the groups. CONCLUSIONS We found no evidence to support a larger noncoverage bias for Hispanics than non-Hispanic Whites in landline telephone surveys. This finding should be considered in the design and interpretation of telephone surveys.

Question Context and Priming Meaning of Health: Effect on Differences in Self-Rated Health Between Hispanics and Non-Hispanic Whites

OBJECTIVES We examined the implications of the current recommended data collection practice of placing self-rated health (SRH) before specific health-related questions (hence, without a health context) to remove potential context effects, between Hispanics and non-Hispanics. METHODS We used 2 methodologically comparable surveys conducted in English and Spanish that asked SRH in different contexts: before and after specific health questions. Focusing on the elderly, we compared the influence of question contexts on SRH between Hispanics and non-Hispanics and between Spanish and English speakers. RESULTS The question context influenced SRH reports of Spanish speakers (and Hispanics) significantly but not of English speakers (and non-Hispanics). Specifically, on SRH within a health context, Hispanics reported more positive health, decreasing the gap with non-Hispanic Whites by two thirds, and the measurement utility of SRH was improved through more consistent mortality prediction across ethnic and linguistic groups. CONCLUSIONS Contrary to the current recommendation, asking SRH within a health context enhanced measurement utility. Studies using SRH may result in erroneous conclusions when one does not consider its question context.

Culture-Sensitive Question Order Effects of Self-Rated Health Between Older Hispanic and Non-Hispanic Adults in the United States.

Objective: The aim of this study is to examine context effects created by the question order for self-rated health (SRH) by race/ethnicity and language. Method: Differences in SRH estimates for non-Hispanic Whites and Hispanics were first examined with multiple observational data that asked SRH in different contexts. To examine context effects by socio-demographics and health-related characteristics, we conducted experiments on SRH question order. Results: While Hispanics reported poorer health than non-Hispanic Whites, this difference, in part, depended on question contexts. With SRH asked after rather than before specific health questions, Hispanics, especially Spanish-speaking Hispanics, reported better health, while non-Hispanic Whites’ reports remained consistent. Among Spanish-speaking Hispanics, the context effect was larger for unmarried and less educated persons and those with comorbidities. Discussion: Question contexts influence SRH reports by Spanish-speaking older adults. Cross-cultural inquiries on the meaning of health and its dynamics with question contexts may explain what SRH measures for increasingly diverse populations.

Efficient Use of Commercial Lists in U.S. Household Sampling

Sampling households using commercial lists has the potential to reduce costs and to efficiently identify some subgroups for which target sample sizes are desired. However, the information on the lists for demographics like age is usually incomplete and inaccurate. We demonstrate that this inexact information can still be used to improve the efficiency with which some, but not all, demographic subgroups can be located during sampling. The paper also illustrates the use of nonlinear programming as a means for finding sample allocations that are subject to a variety of practical constraints. A commercial address list and data from the National Survey of Family Growth and the Health and Retirement Study are used to illustrate the calculation of allocations to strata of housing units defined by information on the list.

Estimating Nonresponse Bias in a Telephone-based Health Surveillance Survey in New York City

Despite concerns about nonresponse bias due to decreasing response rates, telephone surveys remain a viable option for conducting local population-based surveillance. However, this becomes problematic for urban populations, which typically have higher nonresponse rates. Unfortunately, traditional methods of evaluating nonresponse bias pose challenges for public health practitioners due to high costs. In this study, we sought to increase understanding of survey nonresponse at the zip code level in an urban area and to demonstrate the use of a practical tool for assessing nonresponse bias. Data from the 2008 New York City Community Health Survey, a landline telephone survey of residential households in New York, New York, were matched with zip-code-level data from the 2000 US Census. Although response rates varied across zip codes and zip-code-level sociodemographic characteristics, estimated nonresponse bias for the 5 health measures (general health status, current health insurance coverage, asthma, binge drinking, and physical activity) was not substantial (ranging from -3.8% to 2.4%). Findings confirmed previous research that survey participation rates can vary a great deal across small areas and that there is no direct relationship between response rates and nonresponse bias. This study highlights the importance of assessing nonresponse bias for local urban surveys and demonstrates a workable assessment tool.

Relationship Between Future Time Orientation and Item Nonresponse on Subjective Probability Questions: A Cross-Cultural Analysis:

Time orientation is an unconscious yet fundamental cognitive process that provides a framework for organizing personal experiences in temporal categories of past, present, and future, reflecting the relative emphasis given to these categories. Culture lies central to individuals’ time orientation, leading to cultural variations in time orientation. For example, people from future-oriented cultures tend to emphasize the future and store information relevant for the future more than those from present- or past-oriented cultures. For survey questions that ask respondents to report expected probabilities of future events, this may translate into culture-specific question difficulties, manifested through systematically varying “I don’t know” item nonresponse rates. This study drew on the time orientation theory and examined culture-specific nonresponse patterns on subjective probability questions using methodologically comparable population-based surveys from multiple countries. The results supported our hypothesis. Item nonresponse rates on these questions varied significantly in the way that future orientation at the group as well as individual level was associated with lower nonresponse rates. This pattern did not apply to nonprobability questions. Our study also suggested potential nonresponse bias. Examining culture-specific constructs, such as time orientation, as a framework for measurement mechanisms may contribute to improving cross-cultural research.