Nationscape Wave 1: July 18, 2019 — ns

The first weekly wave of the Democracy Fund + UCLA Nationscape survey, fielded July 18–24, 2019. Approximately 6,250 completed online interviews drawn from the Lucid respondent exchange platform using a non-probability quota design, with raking weights calibrated to ACS demographic targets and 2016 presidential vote choice.

Usage

ns_wave1

Format

A data frame with approximately 6,250 rows and 171 columns (170 survey variables plus wave_id added by the prepare script). Run names(ns_wave1) for the complete column list. Key columns:

response_id — Unique respondent ID (integer)
start_date — Interview date (character, "YYYY-MM-DD" format)
wave_id — Wave identifier: "ns20190718" for all rows in this dataset
weight — Raking weight calibrated to ACS demographic targets and 2016 presidential vote choice; use for all population-level estimates
right_track — Country direction: 1 = Right direction, 2 = Wrong track, 3 = Not sure
economy_better — Economy outlook: 1 = Better, 2 = Worse, 3 = Same, 4 = Not sure
interest — Political interest (4-pt): 1 = Very interested, 4 = Not at all interested
registration — Voter registration: 1 = Registered, 2 = Not registered, 3 = Not eligible
pres_approval — Trump presidential approval: 1 = Strongly approve, 2 = Somewhat approve, 3 = Somewhat disapprove, 4 = Strongly disapprove
vote_intention — 2020 vote intention: 1 = Trump, 2 = Democratic candidate, 3 = Other, 4 = Don't plan to vote, 5 = Not sure
vote_2016 — 2016 presidential vote (see labels)
pid3 — 3-category party ID: 1 = Democrat, 2 = Republican, 3 = Independent, 4 = Something else
pid7_legacy — 7-point party ID (legacy coding; see labels)
ideo5 — 5-point ideological self-placement: 1 = Very liberal, 5 = Very conservative
age — Respondent age in years
gender — Gender: 1 = Male, 2 = Female, 3 = Other
census_region — Census region: 1 = Northeast, 2 = Midwest, 3 = South, 4 = West
hispanic — Hispanic or Latino origin: 1 = Yes, 2 = No
race_ethnicity — Race/ethnicity (6 categories; see labels)
household_income — Household income (7 brackets; see labels)
education — Educational attainment (6 categories; see labels)
state — U.S. state of residence (2-letter abbreviation)

Source

Democracy Fund Voter Study Group / UCLA. Nationscape Data Set, version December 2021. https://www.voterstudygroup.org/data/nationscape (free download; academic research use). Prepared by data-raw/prepare-nationscape-phase1.R.

For full methodology, see the Nationscape User Guide and the Representative Assessment report in data-raw/nationscape/phase_1_v20210301/ns20190718/.

Details

This dataset is the first of 77 weekly waves collected from July 2019 through January 2021. The full survey ran in three phases:

Phase	Weeks	Dates	Approx. N
Phase 1	1–24	Jul 18, 2019 – Dec 26, 2019	150,000
Phase 2	25–50	Jan 2, 2020 – Jun 25, 2020	162,500
Phase 3	51–77	Jul 2, 2020 – Jan 12, 2021	168,750

Only Wave 1 is bundled in the package because 77 waves × ~6,250 rows would be prohibitively large. To obtain the full dataset by phase, use the prepare scripts in data-raw/ (see the Source section).

Survey design: The Nationscape is a calibrated non-probability sample (quota design with raking weights). Use surveycore::as_survey_nonprob() — it is designed specifically for this use case:

svy <- surveycore::as_survey_nonprob(ns_wave1, weights = weight)

Metadata: All substantive columns carry variable labels ("label" attribute) set during data preparation. Battery items additionally carry a "question_preface" attribute with the shared question stem. Value labels ("labels" attribute) are present for all coded response items.

Battery structure: Most multi-item question groups follow a {battery}_{item} naming convention. All items within a battery share an identical "question_preface" attribute:

Battery prefix	Preface summary	N items
`news_sources_*`	News sources used in past week	13
`group_favorability_*`	Favorability toward named groups	13
`cand_favorability_*`	Favorability toward named candidates	9
`trump_*`	Trump head-to-head matchups	10
`pence_*`	Pence head-to-head matchups	5
`cand_truth_*`	Whether each candidate tells the truth	6
`cand_facts_*`	Whether each candidate relies on facts	6
`racial_attitudes_*`	Agree/disagree racial attitude items	4
`gender_attitudes_*`	Agree/disagree gender attitude items	4
`discrimination_*`	Perceived discrimination by group	6

References

Tausanovitch, Chris and Lynn Vavreck. 2021. Democracy Fund + UCLA Nationscape, October 10–17, 2019 (version 20210301). Retrieved from voterstudygroup.org/data/nationscape.

Examples

# Design variables
head(ns_wave1[, c("response_id", "weight", "age", "gender")])
#> # A tibble: 6 × 4
#>   response_id weight   age gender
#>   <chr>        <dbl> <dbl>  <dbl>
#> 1 00100002    1.75      37      1
#> 2 00100003    0.144     45      2
#> 3 00100004    0.213     24      1
#> 4 00100005    0.0506    26      1
#> 5 00100007    0.137     60      1
#> 6 00100008    0.0653    55      2

# Inspect a battery item's metadata
attr(ns_wave1$group_favorability_blacks, "label")
#> [1] "Blacks"
attr(ns_wave1$group_favorability_blacks, "question_preface")
#> [1] "Here are the names of some groups that are in the news from time to time. How favorable is your impression of each?"
attr(ns_wave1$news_sources_cnn, "labels")
#> Yes  No 
#>   1   2 

# Create a calibrated survey design
svy <- surveycore::as_survey_nonprob(ns_wave1, weights = weight)

# Party identification distribution
table(ns_wave1$pid3)
#> 
#>    1    2    3    4 
#> 2291 1819 1868  437