Weighting — registered voters
The survey was weighted by The Times using the R survey package in multiple steps to account for the oversample of Republican voters.
First, the samples were adjusted for unequal probability of selection by stratum.
Second, the six state samples were weighted separately to match voter file-based parameters for the characteristics of registered voters by state.
The following targets were used:
- Party (party registration if available, else classification based on a model of vote choice in prior Times/Siena polls)
- Age (Self-reported age, or voter file age if the respondent refuses)
- Gender (L2 data)
- Race or ethnicity (L2 model)
- Education (four categories of self-reported education, weighted to match NYT-based targets derived from Times/Siena polls, census data and the L2 voter file)
- Marital status (L2 model)
- Home ownership (L2 model)
- State regions (NYT classifications by county or city)
- Turnout history (NYT classifications based on L2 data)
- Vote method in the 2020 elections (NYT classifications based on L2 data)
- Census block group density (A.C.S. 5‑Year Census Block Group data)
- City type (Nevada only, added based on a post-hoc analysis of the difference between the weighted sample and voter file parameters. The weight had no meaningful effect on the topline result.)
- Census tract educational attainment (Georgia only, added based on a post-hoc analysis of the difference between the weighted sample and voter file parameters. The weight had no meaningful effect on the topline result.)
Finally, the six state samples were balanced to each represent one-sixth of the sum of the weights.
Weighting — likely electorate
The survey was weighted by The Times using the R survey package in multiple steps to account for the oversample of Republican voters.
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 six state samples were weighted separately 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 vote intention. The final probability that a registrant would vote in the 2024 election was four-fifths based on their ex ante modeled turnout score and one-fifth based on their self-reported intention, 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 six state samples were balanced to each represent one-sixth of the sum of the weights.
