Volume 35 (2019): Edition 4 (December 2019)
Special Edition on Measuring LGBT Populations

As a stigmatized and vulnerable population, sexual minorities are often assumed to also be a hard-to-survey population. Despite this implicit assumption, there is little empirical evidence on the topic. Using a nationally representative survey that included sexual orientation (the Census Barriers, Attitudes, and Motivators Survey), we examine level of effort, the Census Bureau’s Low Response Score (LRS), and stated intent to respond to the 2020 Census as proxy measures to explore this assumption. We found no evidence that sexual minorities required higher levels of effort to secure participation in the survey. Additionally, we found that compared to straight respondents, lesbians, gays, and bisexuals had a higher intent to respond to the 2020 Census. We surmise the current social climate in the United States may be a contributing factor to these findings.

This article presents the results of a pilot feasibility study comparing two alternative recruitment approaches based on Respondent Driven Sampling using initial seeds selected from a US nationally representative panel, AmeriSpeak, to augment the number of lesbian, gay, bisexual, and transgender (LGBT) respondents to a short web survey on smoking, discrimination, and health. In the nomination condition after completing the survey both LGBT and non-LGBT seeds were invited to share the names and email address of up to four LGBT persons they knew. In the recruitment condition, seeds were given four unique PINs and links to the survey to distribute to LGBT persons. Both conditions were successful in producing new LGBT respondents. The recruitment condition was much more productive. LGBT seeds (and their recruits) were much connected to and willing to contact other LGBT people they knew to participate in a survey. Comparisons of characteristics and responses from the initial samples and the LGBT referrals as well as comparisons to LGB samples from a large national survey are presented. Results demonstrate the promise of this hybrid technique for increasing the number of LGBT respondents through referrals from an initial probability based sample.

In the last decade, the call for improved estimates of lesbians, gay men and bisexual (LGB) populations has grown steadily. This is related to the increasing visibility of same-sex unions and the rapidly evolving changes in the legal and normative institutional frameworks regarding same-sex relationships in Western countries. The aim of this article is to present the sampling strategy and discuss the quality of a recently conducted probability-based survey in the Netherlands that targeted mixed-sex and same-sex couples with and without children. The core questions addressed are (1) whether the sampling strategy paid off in terms of identifying same-sex households and (2) whether the collected sample is representative of the target population. While the sampling strategy has success in identifying same-sex households, the question of representativeness remains a challenging task in surveying LGB populations and couples in particular. Especially, aspects related to the sampling strategy, the survey mode and the covered topic of the research are central to understanding observed selection patterns in the examined mixed- and same-sex samples.

Research comparing heterosexuals with bisexuals and homosexuals in economics and the social sciences typically relies on two strategies to identify sexual orientation in existing survey data of general populations. Probing respondents to self-report their sexual orientation is generally considered the preferred option. Since self-reports are unavailable in most large multidisciplinary surveys, often researchers infer sexual orientation from the gender-constellation of a respondent’s partnership instead. Based on German Socio-Economic Panel (SOEP) data, this article reviews both strategies empirically in the context of a household panel survey. The analysis shows that self-reported and partnership-inferred sexual orientation are not mutual substitutes, instead leading to substantively different conclusions about differences between heterosexuals and LGBs (Lesbian, Gays, and Bisexuals). The article discusses problems of non-coverage in partnership-inferred sexual orientation and also investigates measurement error in self-reported sexual orientation, finding notable mode and interviewer effects.

Privacy, achieved through self-administered modes of interviewing, has long been assumed to be a necessary prerequisite for obtaining unbiased responses to sexual identity questions due to their potentially sensitive nature. This study uses data collected as part of a split-ballot field test embedded in the National Health Interview Survey (NHIS) to examine the association between survey mode (computer-assisted personal interviewing (CAPI) versus audio computer-assisted self-interviewing (ACASI)) and sexual minority identity reporting. Bivariate and multivariate quantitative analyses tested for differences in sexual minority identity reporting and non-response by survey mode, as well as for moderation of such differences by sociodemographic characteristics and interviewing environment. No significant main effects of interview mode on sexual minority identity reporting or nonresponse were found. Two significant mode effects emerged in subgroup analyses of sexual minority status out of 35 comparisons, and one significant mode effect emerged in subgroup analyses of item nonresponse. We conclude that asking the NHIS sexual identity question using CAPI does not result in estimates that differ systematically and meaningfully from those produced using ACASI.

The National Crime Victimization Survey (NCVS) collects information on nonfatal personal and property crimes both reported and not reported to police. As part of the ongoing redesign efforts for the NCVS, the Bureau of Justice Statistics (BJS) added sexual orientation and gender identity (SOGI) questions to the survey’s demographic section in July 2016. The inclusion of these measures will provide important national-level estimates of victimization among lesbian, gay, bisexual, and transgender (LGBT) people and allow researchers to understand victimization risk and access to victim services. This article includes a discussion of the sexual orientation and gender identity measures that were added to the NCVS, and findings from the monitoring activities conducted during the first six months of data collection. In addition, population counts by sexual orientation and gender identity are estimated using July through December 2016 NCVS data.

Social scientists struggle on how to best operationalize and measure sexual orientation. Depending on the survey, researchers can use self-reports of lesbian, gay, or bisexual (LGB) identity, same-sex partner cohabitation, same-sex sexual attraction, or same-sex sexual behavior. All measures come with their own limitations. To illuminate differences in these measures, this study examines the intersections between self-reported sexual identity, attraction, and behavior among a nationally representative sample of US men and women aged 15–45. I explore how and when the three measures align, examine the determinants of self-identifying as gay or bisexual based on sexual behavior and attraction, and assess gender differences in the patterns. I find that about 20% of women and 10% of men aged 15–45 would comprise the LGB community if it were defined to include those who report at least one of the following: gay or bisexual identity, any same-sex attraction, or same-sex sex in the last year. This is much higher than the 6.4% of women and 3.6% of men aged 15–45 who self-identify as LGB. I conclude with recommendations that can aid in measurement of the LGB population, and discuss implications for using certain measures over others when conducting research on the LGB community.

Within the United States Federal Statistical System, there has been interest in capturing sexual orientation (SO) and gender identity (GI), collectively known as SOGI, on surveys to allow researchers to estimate the size and distribution of sexual and gender minority populations. SOGI measurement in federal surveys may also help to identify disparities between people who identify as lesbian, gay, bisexual, and transgender (LGBT) and those who do not in domains such as health, crime, or employment. Although research has been conducted on best practices for SOGI measurement in surveys, it has largely been limited to examination of self-reports. Many federal surveys use proxy reports, when one person generally responds for all household members. This research used cognitive interviews and focus groups to explore proxy response to SOGI questions. We explored potential sources of measurement error in proxy responses to SOGI questions, including sensitivity, difficulty, as well as the willingness and ability of respondents to answer SOGI questions about other household members. We also conducted paired interviews with members of the same household to assess level of agreement for SOGI questions. Findings suggest that measuring SOGI by proxy may be feasible in federal large-scale, general population surveys.