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Sample matching is a methodology for selection of “representative” samples from non-randomly selected pools of respondents. These panelists cover a wide range of demographic characteristics. The YouGov panel currently has over 20,000 active panelists who are residents of Texas. After a double opt-in procedure, where respondents must confirm their consent by responding to an email, the database checks to ensure the newly recruited panelist is in fact new and that the address information provided is valid. At the conclusion of the short survey respondents are invited to join the YouGov panel in order to receive and participate in additional surveys. In practice, a search in Google may prompt an active YouGov advertisement soliciting opinion on the search topic. The primary method of recruitment for the YouGov Panel is Web advertising campaigns that appear based on keyword searches.
Axios codebook registration#
Recruiting methods include Web advertising campaigns (public surveys), permission-based email campaigns, partner sponsored solicitations, telephone-to-Web recruitment (RDD based sampling), and mail-to-Web recruitment (Voter Registration Based Sampling). Panel members are recruited by a number of methods and on a variety of topics to help ensure diversity in the panel population.
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At any given time, YouGov maintains a minimum of five recruitment campaigns based on salient current events. residents who have agreed to participate in YouGov Web surveys. The YouGov panel, a proprietary opt-in survey panel, is comprised of 1.5 million U.S. The margin of error of the weighted data for registered voters is 2.83% for registered voters and 3.3% for the weighted data. The weights were trimmed at 7 and normalized to sum to the sample size.
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Axios codebook full#
These weights were then post-stratified on baseline party identification, the 20 presidential vote, ideology, and a full stratification of four-category age, four-category race, gender, and four-category education. The propensity scores were grouped into deciles of the estimated propensity score in the frame and post-stratified according to these deciles. The propensity score function included age, gender, race/ethnicity, and years of education.
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The matched cases and the frame were combined and a logistic regression was estimated for inclusion in the frame. For the main sample, the matched cases were weighted to the sampling frame using propensity scores. The frame was constructed by stratified sampling from the full 2020 Current Population Survey (CPS) voter registration supplement with selection within strata by weighted sampling with replacements (using the person weights on the public use file). The respondents were matched to a sampling frame on gender, age, race, and education. YouGov then weighted the matched set of survey respondents to known characteristics of registered voters of Texas from the 2020 Current Population survey and 2014 Pew Religious Landscape Survey. The respondents were matched on gender, age, race, and education.
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Sampling and Weighting Methodology for the June 2022 Texas Statewide Studyįor the survey, YouGov interviewed 1,359 Texas registered voters between June 16 - 24, 2022 who were then matched down to a sample of 1,200 to produce the final dataset.
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