Toplines: June 2026 Times/Press Herald/Siena Poll of the Likely Electorate in Maine

Full Methodology

The New York Times/Portland Press Herald/Siena poll of 608 likely voters in Maine was conducted on cellular and landline telephones from June 19 to 26, 2026.The margin of sampling error is plus or minus 4.8 percentage points.

The Times/Siena Poll is a collaboration between The New York Times and Siena Research Institute, part of ReconMR. The poll of Maine was sponsored in part by the Maine Trust for Local News.

Sample

The survey is a response rate-adjusted, stratified, probability-proportional-to-size sample of the likely 2026 electorate 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.

To adjust for noncoverage bias, the L2 voter file 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.

Second, the probability of selection was weighted by the likelihood that a respondent would vote in the 2026 election, based on a model of validated turnout in 2022 and 2018 as a function of the respondent’s political and demographic characteristics and participation in other elections.

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. The Siena Research Institute at Siena University and Reconnaissance Market Research (ReconMR) fielded the poll, with additional fieldwork by the Public Opinion Research Lab at the University of North Florida. Interviewers asked for the person named on the voter file and ended the interview if the intended respondent was not available. Overall, more than 93 percent of respondents were reached on cellular telephones.

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 three self-reported variables used in weighting — age, education and recalled 2024 vote — and answered at least one of the questions about age, education or 2026 general election vote intent.

Weighting

The survey was weighted in multiple steps by The Times using the WeightIt package in R.

First, the sample was adjusted for unequal probability of selection by stratum.

Second, the sample was weighted using energy balancing, which finds weights by minimizing the energy distance — a statistical measure of the difference between two multivariate distributions — between the survey and the target population.

The target population was a stratified sample (n=40,000) of the likely electorate, drawn from the L2 voter file’s list of active registered voters. The probability that an active registered voter will turn out in the 2026 midterm election is based on a model of validated turnout in the 2022 and 2018 midterm elections.

The survey was weighted to balance the joint distribution of the following characteristics:

• Party (Party registration if available in the state, else classification based on participation in partisan primaries if available in the state, else classification based on a model of vote choice in prior Times/Siena polls)
• Education (four categories of self-reported education level, based on a model of self-reported education in Times/Siena polls, adjusted to match census-based targets for the registered voter population)
• Age (self-reported age, or voter file age if the respondent refused)
• Gender (L2 data)
• Turnout history (NYT classifications based on L2 data)
• State region (NYT classifications)
• Synthetic 2024 past vote (for the respondent, synthetic 2024 past vote is self-reported recall vote among validated voters, with major party vote imputed among validated voters who do not report supporting a major party candidate. For the target population, synthetic 2024 past vote is the simulated binomial outcome of major party vote choice in the 2024 election among validated voters, based on a model of vote choice in past Times/Siena polls. Vote choice was modeled as a function of information available on the L2 voter file and self-reported education, adjusted to match precinct-level election results)
• Modeled probability of presidential vote choice in the 2024 election (NYT model of vote choice in past Times/Siena polls based on information available on the L2 voter file and adjusted to precinct-level election results)

Third, the weights were adjusted to incorporate self-reported intention to vote. Four-fifths of the final probability that a registrant would vote in the 2026 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. Respondents with a higher likelihood to vote than their initial modeled turnout probability receive more weight, with the final weight equal to the initial 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 using energy balancing to match the joint distribution of the aforementioned characteristics of the full sample of the survey, as well as the results of the race for U.S. Senate.

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 1.48.

For the sample of completed interviews the margin of sampling error is plus or minus 5.4 points, including a design effect of 1.45.

From 2016 to 2024, The Times/Siena Poll’s error at the 95th percentile was plus or minus 5.6 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.