This article introduces the contributions to the PS Spotlight: The Collaborative Multiracial Post-Election Survey (CMPS) Oversamples. Each feature in this issue uses data from the 2020 CMPS to help us understand the strengths and limitations of survey oversamples and to discuss best practices for users of these data. The CMPS has changed the way data are collected and shared in the social sciences. It is a nonpartisan, cooperative, multiracial/ethnic, multilingual, post-presidential election online survey conducted in the United States. It was developed by political scientists in 2008. Beginning in 2016, these co-principal investigators (PIs) led an innovative cooperative funding strategy that broadened the scope of access to high-quality national survey data with large samples of racial/ethnic and underrepresented groups in the United States. See Barreto et al. (Reference Barreto, Frasure-Yokley, Vargas and Wong2018) for a comprehensive description of the CMPS survey design and methodology.

The 2020 CMPS featured six unique oversamples of minoritized populations in the United States. For many reasons, the need to oversample minoritized populations is more pressing than ever. Nevertheless, the experiences of these groups often are understudied and underexplored in social science research because traditional sampling methods cannot yield sufficient data for statistical analyses. The CMPS’s oversampling approach provides scholars with the sample size needed to conduct in-depth analyses. This can result in more comprehensive and inclusive findings, allowing researchers to understand more fully the attitudes, behaviors, and needs of underrepresented communities.

For the 2020 CMPS, we invited nine scholars to serve as Oversample Directors. They are experts in race, ethnicity, identity, and politics for the six unique oversamples, and include the following:

• • Afro-Latinos: Danielle Pilar Clealand (University of Texas at Austin)

• • Black Immigrants: Christina Greer (Fordham University) and Candis Watts Smith (Duke University)

• • LGBTQ+: Andrew Flores (American University)

• • Middle Eastern and North African (MENA)/Muslim Americans: Karam Dana (University of Washington Bothell) and Nazita Lajevardi (Michigan State University)

• • Native Americans: Raymond Foxworth (University of Colorado Boulder) and Laura Evans (University of California, Riverside)

• • Native Hawaiians: Ngoc Phan (Hawai‘i Pacific University)

Random probability sampling techniques of relatively small racial, ethnic, and other identity groups may not yield a sufficient sample size to allow researchers to conduct in-depth analysis of those groups. Survey oversamples allow researchers to select respondents so that some groups comprise a larger share of the survey sample than in the overall population (Mercer Reference Mercer2016). After data collection is complete, sampling weights are applied to the data to align the population with their actual proportion. The larger sample allows researchers to conduct more in-depth analysis of an individual group (Mercer Reference Mercer2016). The practice of oversampling groups that comprise a small proportion of the general population is expensive. Researchers often cannot afford the costs to carry out this sampling technique. Therefore, cooperative funding strategies remain important in building partnerships for scholars to collect survey oversamples.

This cooperative research model is user-content driven, whereas survey items included on the CMPS are generated through survey-question contributions from a national consortium called the CMPS Scholars Research Network. To date, this consortium includes almost 250 researchers from almost 100 accredited colleges and universities, across multiple academic disciplines, including the social sciences, psychology, public policy, public health, education, law, and other fields. With support from the National Science Foundation, the 2020 CMPS expanded in both size and content. It included a total of 14,977 completed interviews in the primary sample of Asian American, Black, Latinx, and White respondents. Table 1 presents the overall sample sizes of additional completed interviews with adults across various oversample groups from hard-to-reach populations. This includes Afro-Latinos, Black Immigrants, Native Americans, Native Hawaiians, Muslims (including MENA), and people who identify as LGBTQ+. The full dataset included 17,545 adult interviews. The invitation and the survey were available to respondents in English, Spanish, Chinese (simplified and traditional), Korean, Vietnamese, Arabic, Urdu, Farsi, and Haitian Creole.

Table 1

Overall Sample Sizes of the Adult Oversample

Source: 2020 Collaborative Multiracial Post-Election Survey Oversamples.

Because of the primary interest in the 2020 election, the project began with a large sample of registered voters from online sources that were pre-matched to the voter file. In addition, the data included a sample of nonregistered adults, including noncitizens. It is important to note that the 2020 CMPS also included a pilot sample of 16- and 17-year-old youth (N=1,457). The combined dataset was collected online in a respondent self-administered format from April 2 to October 4, 2021.