Toplines: October 2024 Times/Siena Poll of Registered Voters in Texas
How These Polls Were Conducted
Here are the key things to know about these polls from The New York Times and Siena College:
• Interviewers spoke with 1,194 voters in Nebraska, including 500 voters in Nebraska’s Second Congressional District, and with 1,180 voters in Texas from Oct. 23 to 26, 2024
• Times/Siena polls are conducted by telephone, using live interviewers, in both English and Spanish. Overall, more than 97 percent of respondents were contacted on a cellphone for these polls.
• Voters are selected for the survey from a list of registered voters. The list contains information on the demographic characteristics of every registered voter, allowing us to ensure we reach the right number of voters of each party, race and region. For these polls, interviewers placed about 210,000 calls to about 75,000 voters.
• To further ensure that the results reflect the entire voting population, not just those willing to take a poll, we give more weight to respondents from demographic groups that are underrepresented among survey respondents, like people without a college degree. You can see more information about the characteristics of our respondents and the weighted sample at the bottom of the page, under “Composition of the Sample.”
• The margin of sampling error among likely voters for each poll is about plus or minus three percentage points. In theory, this means that the results should reflect the views of the overall population most of the time, though many other challenges create additional sources of error. When the difference between two values is computed — such as a candidate’s lead in a race — the margin of error is twice as large.
If you want to read more about how and why the Times/Siena Poll is conducted, you can see answers to frequently asked questions and submit your own questions here.
Full Methodology
The New York Times/Siena College polls of 1,194 voters in Nebraska, including a poll of 500 voters in Nebraska’s Second Congressional District, and 1,180 voters in Texas were conducted in English and Spanish on cellular and landline telephones from Oct. 23 to 26.
The margin of sampling error among the likely electorate is plus or minus 3.2 percentage points in Nebraska, plus or minus 4.8 points in Nebraska’s Second Congressional District, and plus or minus 3.3 percentage points in Texas.
Sample
The survey is a response-rate-adjusted, stratified sample of registered voters taken from the voter file maintained by L2, a nonpartisan voter-file vendor, and supplemented with additional voter-file-matched cellular telephone numbers from Marketing Systems Group. The sample was selected by The New York Times in multiple steps to account for differential telephone coverage, nonresponse and significant variation in the productivity of telephone numbers by state.
In Nebraska, records were selected separately for the polls of Nebraska’s Second Congressional District and of the rest of the state. To adjust for noncoverage bias, the L2 voter file for each state was stratified by statehouse district, party, race, gender, marital status, household size, turnout history, age and homeownership. The proportion of registrants with a telephone number and the mean expected response rate were calculated for each stratum. The mean expected response rate was based on a model of unit nonresponse in prior Times/Siena surveys. The initial selection weight was equal to the reciprocal of a stratum’s mean telephone coverage and modeled response rate. For respondents with multiple telephone numbers on the L2 file, or with differing numbers from L2 and Marketing Systems Group, the number with the highest modeled response rate was selected.
Fielding
The sample was stratified according to political party, race and region. Marketing Systems Group screened the sample to ensure that the cellular telephone numbers were active, and the Siena College Research Institute fielded the poll, with additional fieldwork by ReconMR, the Public Opinion Research Lab at the University of North Florida, the Institute for Policy and Opinion Research at Roanoke College, the Center for Public Opinion and Policy Research at Winthrop University in South Carolina and the University of New Hampshire Survey Center. Interviewers asked for the person named on the voter file and ended the interview if the intended respondent was not available. Overall, more than 97 percent of respondents were reached on a cellular telephone.
The questions were translated into Spanish by ReconMR. Bilingual interviewers began the interview in English and were instructed to follow the lead of the respondent in determining whether to conduct the survey in English or Spanish. Monolingual Spanish-speaking respondents who were initially contacted by English-speaking interviewers were recontacted by Spanish-speaking interviewers. In Nebraska, 14 percent of interviews (15 percent of the weighted sample) among self-reported Latinos were conducted in Spanish, and 12 percent of the interviews (20 percent of the weighted sample) were conducted in Spanish among self-reported Latinos in Texas.
An interview was determined to be complete for the purposes of inclusion in the questions about whom the respondent would vote for if the respondent did not drop out of the survey after being asked the two self-reported variables used in weighting — age and education — and answered at least one of the questions about age, education or presidential-election candidate preference.
Weighting (registered voters)
The survey was weighted by The Times using the survey package in R in multiple steps.
First, the sample was adjusted for unequal probability of selection by stratum.
Second, each poll was weighted to match voter-file-based parameters for the characteristics of registered voters.
The following targets were used:
• Party (classification based on participation in partisan primaries) by race (L2 model), in Texas
• Party (party registration) by a classification of how strongly partisan the respondent is based on a model of vote choice in prior Times/Siena polls, in Nebraska’s Second Congressional District
• Party (party registration), in the rest of Nebraska
• Race or ethnicity (L2 model)
• Age (self-reported age, or voter-file age if the respondent refused) by gender (L2 data)
• Education (four categories of self-reported education level, weighted to match Times-generated targets derived from Times/Siena polls, census data and the L2 voter file)
• White/nonwhite race by college or noncollege educational attainment (L2 model of race weighted to match Times-generated targets for self-reported education in Nebraska’s Second Congressional District; L2 model of race weighted to match Times-generated targets derived from census data in Texas)
• Marital status (L2 model)
• Homeownership (L2 model)
• Turnout history (Times classifications based on L2 data)
• Method of voting in the 2020 elections (Times classifications based on L2 data)
• State region (Times classifications)
• Census block group density (American Community Survey five-year census block group data), in Texas and the rest of Nebraska
• Census tract educational attainment, in Texas
Third, in Nebraska, the sums of the weights of the polls were balanced so that respondents in Nebraska’s Second Congressional District represented the proper proportion of the Nebraska poll.
Finally, the sample of respondents who completed all questions in the survey was weighted identically as well as to the result for the general-election horse-race question (including voters leaning a certain way) on the full sample.
Weighting (likely electorate)
The survey was weighted by The Times using the R survey package in multiple steps.
First, the samples were adjusted for unequal probability of selection by stratum.
Second, the first-stage weight was adjusted to account for the probability that a registrant would vote in the 2024 election, based on a model of turnout in the 2020 election.
Third, the sample was weighted to match targets for the composition of the likely electorate. The targets for the composition of the likely electorate were derived by aggregating the individual-level turnout estimates described in the previous step for registrants on the L2 voter file. The categories used in weighting were the same as those previously mentioned for registered voters.
Fourth, the initial likely electorate weight was adjusted to incorporate self-reported intention to vote. Four-fifths of the final probability that a registrant would vote in the 2024 election was based on the registrant’s ex ante modeled turnout score, and one-fifth was based on self-reported intentions, based on prior Times/Siena polls, including a penalty to account for the tendency of survey respondents to turn out at higher rates than nonrespondents. The final likely electorate weight was equal to the modeled electorate rake weight, multiplied by the final turnout probability and divided by the ex ante modeled turnout probability.
Finally, the sample of respondents who completed all questions in the survey was weighted identically as well as to the result for the general election horse-race question (including leaners) on the full sample.
The margin of error accounts for the survey’s design effect, a measure of the loss of statistical power due to survey design and weighting.
The design effect for the full sample is 1.27 for the likely electorate in Nebraska, 1.18 in Nebraska’s Second Congressional District and 1.32 for the likely electorate in Texas.
Among registered voters, the margin of sampling error is plus or minus 3.1 points in Nebraska, including a design effect of 1.23; plus or minus 4.8 points in Nebraska’s Second Congressional District, including a design effect of 1.21, and plus or minus 3.1 points in Texas, including a design effect of 1.19.
For the sample of completed interviews, among the likely electorate, the margin of sampling error is plus or minus 3.3 points in Nebraska, including a design effect of 1.29; and plus or minus 3.4 points in Texas, including a design effect of 1.35.
Historically, The Times/Siena Poll’s error at the 95th percentile has been plus or minus 5.1 percentage points in surveys taken over the final three weeks before an election. Real-world error includes sources of error beyond sampling error, such as nonresponse bias, coverage error, late shifts among undecided voters and error in estimating the composition of the electorate.