Persona profiles of 100 respondents to the ANES 2024 Time Series Study

A data frame describing 100 respondents to the American National Election Studies (ANES) 2024 Time Series Study by their demographics and their political attitudes, written as text a language model can read. It serves as ready-made persona material: panel_from_personas() turns its rows into a panel of language-model personas. FocusGroup ships an identical copy.

Usage

anes_2024_personas

Format

A data frame with 100 rows and 123 columns. Each row is one respondent; no ANES case identifier is kept. Column names are handles whose prefix names a block, so startsWith(names(x), "att_iss_") selects the issue positions:

demo_: 17 demographic fields: age band, sex, education, race/ethnicity, marital status, household income, religion and its importance, religious attendance, census region, rural-urban self-identification, employment status, home ownership, children in the household, union household, military service, and attention to politics.
att_id_: 9 fields of party identification, ideology, and vote choice.
att_aff_: 18 feeling thermometers toward candidates, parties, institutions, and groups.
att_eval_: 14 evaluations: approval of the President, Congress, and the Supreme Court, the economy, personal finances, feelings about the country, and which party would better handle the economy and immigration.
att_iss_: 47 issue positions, among them taxes and spending, immigration, guns, climate, health care, abortion, policing, race, and foreign policy.
att_val_: 17 fields of trust, values, and views of democracy.
ideology_score: A number placing the respondent on one liberal-conservative dimension (see Details); the rows are sorted by it.

Every column but ideology_score holds character values:

An answer with a value label is written as that label without its code ("Strong Democrat", "Favor a great deal"). Parenthetical qualifiers are kept, the interviewer notes "{VOL}" and "{SPECIFY}" are removed, and the four labels of the immigration policy item (V241386) that the Stata file cuts at 80 characters are restored in full from the codebook.
The six 7-point scales that ANES labels only at their ends are written as sentences, endpoints included: "5 on a scale from 1 (Government should provide many fewer services) to 7 (Government should provide many more services)".
Feeling thermometers are written as "70 on a 0-100 feeling thermometer".
"Haven't thought much about this" is kept as an answer where ANES offered it.
Age is given in six bands and children in the household as "Yes" or "No". Employment status is written from the full ANES labels without their "R " prefix ("Retired (if also working, working < 20 hrs/wk)"). Religious attendance is "Never" for respondents who said they never attend services (V241439 = 2), who were not asked how often (V241440).
NA marks a missing-data code: refused, don't know, inapplicable, no post-election interview, and so on, and a thermometer rating outside 0-100 ("don't know where to rate", "don't recognize"). The 100 rows hold 246 such cells, most of them in the vote items, which do not apply to everyone.

The data frame carries these attributes:

dictionary: A data frame with one row per column except ideology_score: handle; question, the short phrase shown with an answer ("Abortion position"); anes_variable, the ANES variable; domain, "demographic" or the attitude block; wording, the question as printed in the ANES codebook; wording_variable and wording_page, the variable whose question that is and the codebook page where it begins; and wording_status. A status of "verbatim" means the wording is the variable's own question; "from_source_item" means the variable is a summary without a question of its own and the wording is that of the item it summarizes (for party identification, V241221); "stem_only" means the codebook prints only a shared stem ("Where would you place yourself on this scale, or haven't you thought much about this?") and the subject of the scale is in its end labels; "none" means no single question exists (census region, age), and wording is NA.
demographic_fields: The handles of the demographic columns.
n_demographics, n_attitudes: 17 and 105.
source, citation: The citation of the ANES release.
build: The R and package versions, the md5 sums of the two ANES files, the seed, and the label overrides used to build the data.
build_audit: For each column, the number of NA cells and the number of missing-data codes in the raw file for the same respondents; the two are equal.

Source

American National Election Studies. 2026. ANES 2024 Time Series Study Full Release [dataset and documentation]. May 19, 2026 version. www.electionstudies.org. Work that uses these profiles should cite ANES. ANES bears no responsibility for the analyses or interpretations presented here.

Details

The respondents were drawn from the 4,710 of 5,521 who completed both the pre-election and the post-election interview, neither of them on paper, and answered at least 75 percent of the 122 fields. For each code of party identification, race/ethnicity, and liberal-conservative self-placement not yet covered, one respondent with that code was drawn at random (seed 110); the remaining places were filled by greedy maximin selection, each time adding the respondent farthest from those already chosen, under a Gower distance in which the demographic, identity, thermometer, evaluation, issue, and value blocks carry weights 0.25, 0.25, 0.20, 0.15, 0.15, and 0.15. Each respondent's answers are kept together.

The sample spans unusual combinations of answers and does not reproduce population proportions. It carries no survey weights and supports no population inference. Maximin selection over-represents people with no 2024 presidential vote recorded (38 of the 100, against 18.5 percent of the eligible respondents), and within each party it favors members whose other answers depart from the party's usual positions.

ideology_score comes from a one-dimensional graded-response item response model fitted to 89 attitude items over the 4,710 eligible respondents. Categories enter in the order of their ANES codes (thermometers grouped into five bands, off-scale answers such as "Haven't thought much about this" left out), and items are reversed where they correlate negatively with party identification and ideology. The expected a posteriori scores are standardized over the eligible respondents and oriented so that low is liberal and high is conservative. They correlate 0.89 with party identification and ideology among the eligible respondents and 0.58 among the 100, whose scores have a standard deviation of 0.55.

Items on sexual orientation and gender identity are excluded by design, as are restricted-use variables, geography below the census region, open-ended answers, and items asked only of the spouse/partner sample, only on paper, or only of the GSS re-interview sample, which this release does not include.

Examples

dim(anes_2024_personas)
dictionary <- attr(anes_2024_personas, "dictionary")
dictionary[dictionary$handle == "att_iss_abortion_position",
           c("question", "wording", "wording_status")]
table(anes_2024_personas$att_id_party_identification)
issues <- anes_2024_personas[, startsWith(names(anes_2024_personas), "att_iss_")]
ncol(issues)