Collaborative Multi-racial Post-election Survey (CMPS), United States, 2016 (ICPSR 38040)

Version Date: Jun 30, 2021

Principal Investigator(s):
Lorrie Frasure, University of California, Los Angeles; Janelle Wong, University of Maryland, College Park; Edward Vargas, Arizona State University; Matt Bareto, University of California, Los Angeles

Series:

https://doi.org/10.3886/ICPSR38040.v1

Version V1 ()

  • V2 [2022-05-03]
  • V1 [2021-06-30] unpublished

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Additional information about this collection can be found in Version History.

2021-06-30 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Summary

In spring 2016, scholars were invited to collaborate on the 2016 Collaborative Multi-Racial Post-election Survey (CMPS). The goal of the project was to create the first cooperative, 100% user content driven, multi-racial, multiethnic, multi-lingual, post-election online survey in race, ethnicity and politics (REP) in the United States. The survey's main focus is on attitudes about the 2016 election and candidates, debates over immigration, policing, and racial equality, and experiences with racial discrimination across many facets of American life.

Questions were user-generated from a team of 86 social scientists across 55 different universities who placed questions on the survey. Users could submit questions for just one single racial group, or common questions across all four racial groups, depending on their interest. In cases where two different users submitted very similar questions the PIs worked to create a single common question. Overall, the survey contains 394 questions.

The restricted-use dataset contains geographical information which has been masked in the public-use dataset along with adjustments to date information. Please refer to the Collection Notes in the SCOPE OF PROJECT section for more information.

Citation

Frasure, Lorrie, Wong, Janelle, Vargas, Edward, and Bareto, Matt. Collaborative Multi-racial Post-election Survey (CMPS), United States, 2016. Inter-university Consortium for Political and Social Research [distributor], 2021-06-30. https://doi.org/10.3886/ICPSR38040.v1

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Subject Terms

Geographic Coverage

Smallest Geographic Unit

Zip code

Restrictions

This data collection may not be used for any purpose other than statistical reporting and analysis. Use of these data to learn the identity of any person or establishment is prohibited. To obtain the restricted file, researchers must agree to the terms and conditions of a Restricted Data Use Agreement.

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2016

Date of Collection

2016-12 -- 2017-02

Data Collection Notes

  1. ETHNIC_QUOTA was a variable used in the data collection only, so that the data collection vendor could assign cases towards the quota targets of each racial group towards the counts. The Principal Investigators do not necessarily recommend using this variable for analysis, rather they recommend scholars use the self-reported race and ethnicity of respondents to create their own estimates for race. However, the ethnic quota variable can be used, but this variable assigns each respondent a primary race/ethnicity group, again, just for the purposes of the quota count.

  2. The restricted-use dataset contains geographical information which has been masked in the public-use dataset. The variables ZIPCODE and C342 contain zip codes, and CITY_NAME and C347_CITY contain the name of cities.

    The day-in-date for INTERVIEW_START, INTERVIEW_END, and TIME_304 has been recoded to the first of the month in the public-use dataset but is preserved in the restricted-use dataset.

  3. For additional information on the Collaborative Multi-racial Post-election Survey, please visit the CMPS website.
  4. This collection is related to the following studies:
    • Collaborative Multi-racial Post-election Survey (CMPS), 2012, ICPSR 37132
    • Collaborative Multi-racial Post-election Survey (CMPS), 2008, ICPSR 35163
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Study Purpose

The goal of the project was to create the first cooperative, 100% user content driven, multi-racial, multi-ethnic, multi-lingual, post-election online survey in race, ethnicity and politics (REP) in the United States.

Sample

Data for registered voters comes from the national voter registration database email sample, and respondents were randomly selected to participate in the study, and confirmed they were registered to vote before starting the survey. For the non-registered sample, emails addresses were randomly selected from various online panel vendors. In total, 298,159 email addresses were selected and sent invitations to participate in the survey and 29,489 people accepted the invitation and started the survey, for an effective response rate of 9.9%. Among the 29,489 people who started the survey, 11,868 potential respondents were terminated due to quotas being full, which resulted in 17,621 who were eligible to take the survey of which 10,145 completed the full questionnaire for a cooperation rate of 57.6%. Respondents were given a $10 or $20 gift card as compensation for their participation. Non-registered voters were randomly selected from one of six online panels of respondents from Federated, Poder, Research Now, Netquest, SSI, and Prodege, and confirmed that they were not registered to vote before starting the survey. Programming and data collection for the full project were overseen by Pacific Market Research in Renton, WA

Time Method

Cross-sectional

Universe

Residents of the United States

Unit(s) of Observation

Individuals

Data Type(s)

Mode of Data Collection

Description of Variables

Variables include demographic variables, approval and disapproval of many U.S. politicians, participation in the political process, and a great number of variables on participants' opinions on political issues.

Questions were user-generated from a team of 86 social scientists across 55 different universities who placed questions on the survey. Users could submit questions for just one single racial group, or common questions across all four racial groups, depending on their interest. In cases where two different users submitted very similar questions the PIs worked to create a single common question.

Response Rates

57.6 percent

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Original Release Date

2021-06-30

Version History

2021-06-30 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.
Hide

Weight

The data are weighted within each racial group to match the adult population in the 2015 Census American Community Survey (ACS) 1-year data file for age, gender, education, nativity, ancestry, and voter registration status. A post-stratification raking algorithm was used to balance each category within +/- 1% of the ACS estimates. Data are not weighted to their national combined racial average. That is, Whites account for 10% of all cases, and each racial group roughly 30%.

There are two weighting variables (WEIGHT and NAT_WEIGHT).

WEIGHT is the variable to be used for analysis of a single, or multiple racial groups. The weight variable NAT_WEIGHT is for national analysis that approximates the US population - that is - each group is weighted to their share, such as Whites are 65%, Blacks are 13%, Latinos are 15% and so on. With the first weight simply called weight, each group is as large as their sample size, so each minority group is about 30% of the sample. The PI's advise the use of the weight variable in most instances, unless the researcher is attempting to analyze the overall US population and is not concerned about breakouts by racial group.

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