% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ns_wave1}
\alias{ns_wave1}
\title{Nationscape Wave 1: July 18, 2019}
\format{
A data frame with approximately 6,250 rows and 171 variables
(170 survey variables plus \code{wave_id} added by the prepare script).
\describe{
\item{response_id}{Unique respondent ID (integer).}
\item{start_date}{Interview date (character, \code{"YYYY-MM-DD"} format).}
\item{wave_id}{Wave identifier: \code{"ns20190718"} for all rows in this
dataset.}
\item{weight}{Raking weight calibrated to ACS demographic targets and
2016 presidential vote choice. Use for all population-level estimates.}
\item{right_track}{Country direction: \code{1} = Right direction,
\code{2} = Wrong track, \code{3} = Not sure.}
\item{economy_better}{Economy outlook: \code{1} = Better, \code{2} = Worse,
\code{3} = Same, \code{4} = Not sure.}
\item{interest}{Political interest (4-pt): \code{1} = Very interested,
\code{4} = Not at all interested.}
\item{registration}{Voter registration: \code{1} = Registered,
\code{2} = Not registered, \code{3} = Not eligible.}
\item{pres_approval}{Trump presidential approval: \code{1} = Strongly approve,
\code{2} = Somewhat approve, \code{3} = Somewhat disapprove,
\code{4} = Strongly disapprove.}
\item{vote_intention}{2020 vote intention: \code{1} = Trump,
\code{2} = Democratic candidate, \code{3} = Other, \code{4} = Don't plan to vote,
\code{5} = Not sure.}
\item{vote_2016}{2016 presidential vote. See labels.}
\item{vote_2016_other_text}{Write-in for \code{vote_2016} "other" choice.}
\item{consider_trump}{Would consider voting for Trump: \code{1} = Yes,
\code{2} = No.}
\item{not_trump}{Reason for not considering Trump (open text).}
\item{primary_party}{Primary vote party: \code{1} = Democratic,
\code{2} = Republican, \code{3} = Other.}
\item{dem_vote_intent}{Democratic primary vote intention. See labels.}
\item{dem_vote_intent_TEXT}{Write-in for \code{dem_vote_intent} "other".}
\item{rank_dems_1}{Top-ranked Democratic presidential candidate.
See labels.}
\item{rank_dems_2}{Second-ranked Democratic candidate. See labels.}
\item{rank_dems_3}{Third-ranked Democratic candidate. See labels.}
\item{replace_trump}{Wants non-Trump Republican nominee: \code{1} = Yes,
\code{2} = No, \code{3} = Not sure.}
\item{house_intent}{U.S. House vote intention: \code{1} = Democrat,
\code{2} = Republican, \code{3} = Other, \code{4} = Won't vote, \code{5} = Not sure.}
\item{senate_intent}{U.S. Senate vote intention. Same codes as
\code{house_intent}.}
\item{governor_intent}{Governor vote intention. Same codes as
\code{house_intent}.}
\item{news_sources_facebook}{Used social media for political news in past
week: \code{1} = Selected, \code{2} = Not selected. See \code{"question_preface"}
attribute for shared question stem. Same coding for all \verb{news_sources_*}
variables.}
\item{news_sources_cnn}{Used CNN for political news.}
\item{news_sources_msnbc}{Used MSNBC for political news.}
\item{news_sources_fox}{Used Fox News for political news.}
\item{news_sources_network}{Used network news (ABC/CBS/NBC/PBS).}
\item{news_sources_localtv}{Used local TV news.}
\item{news_sources_telemundo}{Used Telemundo or Univision.}
\item{news_sources_npr}{Used NPR.}
\item{news_sources_amtalk}{Used AM talk radio.}
\item{news_sources_new_york_times}{Used a national newspaper.}
\item{news_sources_local_newspaper}{Used a local newspaper.}
\item{news_sources_other}{Used another news source: \code{1} = Selected,
\code{2} = Not selected.}
\item{news_sources_other_TEXT}{Write-in for \code{news_sources_other}.}
\item{group_favorability_whites}{Favorability toward Whites: \code{1} = Very
favorable, \code{2} = Somewhat favorable, \code{3} = Somewhat unfavorable,
\code{4} = Very unfavorable, \code{5} = Not sure. Same coding for all
\verb{group_favorability_*} variables.}
\item{group_favorability_blacks}{Favorability toward Blacks.}
\item{group_favorability_latinos}{Favorability toward Latinos.}
\item{group_favorability_asians}{Favorability toward Asians.}
\item{group_favorability_christians}{Favorability toward Christians.}
\item{group_favorability_socialists}{Favorability toward Socialists.}
\item{group_favorability_muslims}{Favorability toward Muslims.}
\item{group_favorability_labor_unions}{Favorability toward labor unions.}
\item{group_favorability_the_police}{Favorability toward the police.}
\item{group_favorability_undocumented}{Favorability toward undocumented
immigrants.}
\item{group_favorability_lgbt}{Favorability toward gays and lesbians.}
\item{group_favorability_republicans}{Favorability toward Republicans.}
\item{group_favorability_democrats}{Favorability toward Democrats.}
\item{cand_favorability_trump}{Favorability toward Donald Trump. Same
5-point scale as \verb{group_favorability_*} variables.}
\item{cand_favorability_obama}{Favorability toward Barack Obama.}
\item{cand_favorability_cortez}{Favorability toward Alexandria
Ocasio-Cortez.}
\item{cand_favorability_biden}{Favorability toward Joe Biden.}
\item{cand_favorability_harris}{Favorability toward Kamala Harris.}
\item{cand_favorability_buttigieg}{Favorability toward Pete Buttigieg.}
\item{cand_favorability_warren}{Favorability toward Elizabeth Warren.}
\item{cand_favorability_sanders}{Favorability toward Bernie Sanders.}
\item{cand_favorability_pence}{Favorability toward Mike Pence.}
\item{trump_biden}{Trump vs. Biden head-to-head: \code{1} = Trump, \code{2} = Biden,
\code{3} = Not sure. Same coding for all \verb{trump_*} matchup variables.}
\item{trump_sanders}{Trump vs. Sanders.}
\item{trump_harris}{Trump vs. Harris.}
\item{trump_warren}{Trump vs. Warren.}
\item{trump_buttigieg}{Trump vs. Buttigieg.}
\item{trump_booker}{Trump vs. Cory Booker.}
\item{trump_castro}{Trump vs. Julian Castro.}
\item{trump_gabbard}{Trump vs. Tulsi Gabbard.}
\item{trump_gillibrand}{Trump vs. Kirsten Gillibrand.}
\item{trump_orourke}{Trump vs. Beto O'Rourke.}
\item{pence_biden}{Pence vs. Biden head-to-head: \code{1} = Pence, \code{2} = Biden,
\code{3} = Not sure. Same coding for all \verb{pence_*} matchup variables.}
\item{pence_buttigieg}{Pence vs. Buttigieg.}
\item{pence_harris}{Pence vs. Harris.}
\item{pence_sanders}{Pence vs. Sanders.}
\item{pence_warren}{Pence vs. Warren.}
\item{cand_truth_donald_trump}{Whether Donald Trump cares about telling
the truth: \code{1} = Yes, \code{2} = No, \code{3} = Not sure. Same coding for all
\verb{cand_truth_*} variables.}
\item{cand_truth_elizabeth_warren}{Whether Elizabeth Warren cares about
the truth.}
\item{cand_truth_joe_biden}{Whether Joe Biden cares about the truth.}
\item{cand_truth_bernie_sanders}{Whether Bernie Sanders cares about
the truth.}
\item{cand_truth_pete_buttigieg}{Whether Pete Buttigieg cares about
the truth.}
\item{cand_truth_kamala_harris}{Whether Kamala Harris cares about
the truth.}
\item{cand_facts_donald_trump}{Whether Donald Trump relies on facts vs.
hunches: \code{1} = Facts and evidence, \code{2} = Hunches, \code{3} = Not sure. Same
coding for all \verb{cand_facts_*} variables.}
\item{cand_facts_elizabeth_warren}{Whether Elizabeth Warren relies on
facts.}
\item{cand_facts_joe_biden}{Whether Joe Biden relies on facts.}
\item{cand_facts_bernie_sanders}{Whether Bernie Sanders relies on facts.}
\item{cand_facts_pete_buttigieg}{Whether Pete Buttigieg relies on facts.}
\item{cand_facts_kamala_harris}{Whether Kamala Harris relies on facts.}
\item{racial_attitudes_tryhard}{Agree/disagree: minorities should work
their way up without special favors. \code{1} = Strongly agree, \code{2} = Agree,
\code{3} = Neither, \code{4} = Disagree, \code{5} = Strongly disagree. Same scale for
all \verb{racial_attitudes_*} and \verb{gender_attitudes_*} variables.}
\item{racial_attitudes_generations}{Agree/disagree: generations of slavery
make it difficult for Blacks to work out of the lower class.}
\item{racial_attitudes_marry}{Agree/disagree: I prefer close relatives
marry someone from the same race.}
\item{racial_attitudes_date}{Agree/disagree: it's alright for Blacks and
Whites to date.}
\item{gender_attitudes_maleboss}{Agree/disagree: more comfortable with a
male boss than female boss.}
\item{gender_attitudes_logical}{Agree/disagree: women are just as capable
of thinking logically as men.}
\item{gender_attitudes_opportunity}{Agree/disagree: increased opportunities
for women have improved quality of life.}
\item{gender_attitudes_complain}{Agree/disagree: women who complain about
harassment cause more problems than they solve.}
\item{discrimination_blacks}{Perceived discrimination against Blacks:
\code{1} = A great deal, \code{2} = A lot, \code{3} = A little, \code{4} = None at all,
\code{5} = Not sure. Same scale for all \verb{discrimination_*} variables.}
\item{discrimination_whites}{Perceived discrimination against Whites.}
\item{discrimination_muslims}{Perceived discrimination against Muslims.}
\item{discrimination_christians}{Perceived discrimination against
Christians.}
\item{discrimination_women}{Perceived discrimination against Women.}
\item{discrimination_men}{Perceived discrimination against Men.}
\item{sen_knowledge}{U.S. Senate knowledge question. See labels.}
\item{sc_knowledge}{U.S. Supreme Court knowledge question. See labels.}
\item{pid3}{3-category party ID: \code{1} = Democrat, \code{2} = Republican,
\code{3} = Independent, \code{4} = Something else.}
\item{pid7_legacy}{7-point party ID (legacy coding). See labels.}
\item{strength_democrat}{Strength of Democratic ID (conditional on
\code{pid3 == 1}). See labels.}
\item{strength_republican}{Strength of Republican ID (conditional on
\code{pid3 == 2}). See labels.}
\item{lean_independent}{Partisan lean of Independents (conditional on
\code{pid3 == 3}). See labels.}
\item{ideo5}{5-point ideological self-placement: \code{1} = Very liberal,
\code{5} = Very conservative.}
\item{employment}{Employment status (selected choice). See labels.}
\item{employment_other_text}{Write-in for \code{employment} "other".}
\item{foreign_born}{Born outside the U.S.: \code{1} = Yes, \code{2} = No.}
\item{language}{Primary language at home. See labels.}
\item{religion}{Religious affiliation (selected choice). See labels.}
\item{religion_other_text}{Write-in for \code{religion} "other".}
\item{is_evangelical}{Born-again or evangelical Christian: \code{1} = Yes,
\code{2} = No.}
\item{orientation_group}{Sexual orientation. See labels.}
\item{in_union}{Labor union membership: \code{1} = Yes, \code{2} = No,
\code{3} = Non-union household, \code{4} = Not sure.}
\item{household_gun_owner}{Household gun ownership: \code{1} = Yes, \code{2} = No,
\code{3} = Not sure.}
\item{wall}{Support building a wall on the southern U.S. border:
\code{1} = Strongly support, \code{2} = Somewhat support, \code{3} = Somewhat oppose,
\code{4} = Strongly oppose, \code{5} = Not sure. Same scale for all policy items
through \code{limit_magazines}. See \code{"question_preface"} attribute on each
variable for the exact shared question stem.}
\item{cap_carbon}{Support capping carbon emissions.}
\item{environment}{Support large-scale government investment in
environmental technology.}
\item{guns_bg}{Support requiring background checks for all gun purchases.}
\item{mctaxes}{Support cutting taxes for families making < $100K/year.}
\item{estate_tax}{Support eliminating the estate tax.}
\item{raise_upper_tax}{Support raising taxes on families making > $600K.}
\item{college}{Support ensuring all students can graduate from state
colleges debt-free.}
\item{abortion_waiting}{Support requiring a waiting period and ultrasound
before an abortion.}
\item{abortion_never}{Support never permitting abortion.}
\item{abortion_conditions}{Support permitting abortion in cases other than
rape/incest/life at risk.}
\item{late_term_abortion}{Support permitting late-term abortion.}
\item{abortion_insurance}{Support allowing employers to decline abortion
coverage.}
\item{guaranteed_jobs}{Support guaranteeing jobs for all Americans.}
\item{green_new_deal}{Support enacting a Green New Deal.}
\item{gun_registry}{Support creating a public registry of gun ownership.}
\item{immigration_separation}{Support separating children from parents
prosecuted for illegal border crossing.}
\item{immigration_system}{Support shifting to a merit-based immigration
system.}
\item{immigration_wire}{Support requiring proof of citizenship to wire
money internationally.}
\item{impeach_trump}{Support impeaching President Trump.}
\item{israel}{Support withdrawing military support for Israel.}
\item{marijuana}{Support legalizing marijuana.}
\item{maternityleave}{Support requiring 12 weeks of paid maternity leave.}
\item{medicare_for_all}{Support Medicare-for-All.}
\item{military_size}{Support reducing the size of the U.S. military.}
\item{minwage}{Support raising the minimum wage to $15/hour.}
\item{muslimban}{Support banning people from predominantly Muslim
countries.}
\item{oil_and_gas}{Support removing barriers to domestic oil and gas
drilling.}
\item{reparations}{Support granting reparations to descendants of slaves.}
\item{right_to_work}{Support allowing people to work in unionized
workplaces without paying union dues.}
\item{ten_commandments}{Support displaying the Ten Commandments in public
schools and courthouses.}
\item{trade}{Support limiting trade with other countries.}
\item{trans_military}{Support allowing transgender people to serve in the
military.}
\item{uctaxes2}{Support raising taxes on families making > $250K.}
\item{vouchers}{Support providing tax-funded vouchers for private or
religious schools.}
\item{gov_insurance}{Support providing government-run health insurance to
all Americans.}
\item{public_option}{Support providing the option to purchase
government-run insurance.}
\item{health_subsidies}{Support subsidizing health insurance for lower
income people not on Medicaid.}
\item{path_to_citizenship}{Support creating a path to citizenship for
all undocumented immigrants.}
\item{dreamers}{Support a path to citizenship for DREAMers.}
\item{deportation}{Support deporting all undocumented immigrants.}
\item{ban_guns}{Support banning all guns.}
\item{ban_assault_rifles}{Support banning assault rifles.}
\item{limit_magazines}{Support limiting gun magazines to 10 bullets.}
\item{age}{Respondent age in years.}
\item{gender}{Gender: \code{1} = Male, \code{2} = Female, \code{3} = Other.}
\item{census_region}{Census region: \code{1} = Northeast, \code{2} = Midwest,
\code{3} = South, \code{4} = West.}
\item{hispanic}{Hispanic or Latino origin: \code{1} = Yes, \code{2} = No.}
\item{race_ethnicity}{Race/ethnicity (6 categories). See labels.}
\item{household_income}{Household income (7 brackets). See labels.}
\item{education}{Educational attainment (6 categories). See labels.}
\item{state}{U.S. state of residence (2-letter abbreviation).}
\item{congress_district}{Congressional district.}
}
}
\source{
Democracy Fund Voter Study Group / UCLA. Nationscape Data Set, version
December 2021. \url{https://www.voterstudygroup.org/data/nationscape}
(free download; academic research use). Prepared by
\code{data-raw/prepare-nationscape-phase1.R}.

For full methodology, see the Nationscape User Guide and the
Representative Assessment report in
\verb{data-raw/nationscape/Nationscape-User-Guide-2021Dec.pdf}.
}
\usage{
ns_wave1
}
\description{
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.
}
\details{
This dataset is the first of 77 weekly waves collected from July 2019
through January 2021. The full survey ran in three phases:\tabular{llll}{
   Phase \tab Weeks \tab Dates \tab Approx. N \cr
   Phase 1 \tab 1–24 \tab Jul 18, 2019 – Dec 26, 2019 \tab 150,000 \cr
   Phase 2 \tab 25–50 \tab Jan 2, 2020 – Jun 25, 2020 \tab 162,500 \cr
   Phase 3 \tab 51–77 \tab Jul 2, 2020 – Jan 12, 2021 \tab 168,750 \cr
}


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 \verb{data-raw/} (see the Source section).

\strong{Survey design:}
The Nationscape is a calibrated non-probability sample (quota design with
raking weights). Use \code{\link[=as_survey_nonprob]{as_survey_nonprob()}} — it is designed specifically
for this use case and will gain bootstrap re-calibration variance in Phase
2.5:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{svy <- as_survey_nonprob(ns_wave1, weights = weight)
}\if{html}{\out{</div>}}

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

\strong{Battery structure:}
Most multi-item question groups follow a \verb{\{battery\}_\{item\}} naming
convention. All items within a battery share an identical
\code{"question_preface"} attribute:\tabular{lll}{
   Battery prefix \tab Preface summary \tab N items \cr
   \verb{news_sources_*} \tab News sources used in past week \tab 13 \cr
   \verb{group_favorability_*} \tab Favorability toward named groups \tab 13 \cr
   \verb{cand_favorability_*} \tab Favorability toward named candidates \tab 9 \cr
   \verb{trump_*} \tab Trump head-to-head matchups \tab 10 \cr
   \verb{pence_*} \tab Pence head-to-head matchups \tab 5 \cr
   \verb{cand_truth_*} \tab Whether each candidate tells the truth \tab 6 \cr
   \verb{cand_facts_*} \tab Whether each candidate relies on facts \tab 6 \cr
   \verb{racial_attitudes_*} \tab Agree/disagree racial attitude items \tab 4 \cr
   \verb{gender_attitudes_*} \tab Agree/disagree gender attitude items \tab 4 \cr
   \verb{discrimination_*} \tab Perceived discrimination by group \tab 6 \cr
}


Three policy batteries share the same Agree/Disagree/Neither scale:
\code{wall}, \code{cap_carbon}, \code{environment}, \code{guns_bg}, \code{mctaxes}, \code{estate_tax},
\code{raise_upper_tax}, \code{college}, \code{abortion_waiting}, \code{abortion_never},
\code{abortion_conditions}, \code{late_term_abortion}, \code{abortion_insurance},
\code{guaranteed_jobs}, \code{green_new_deal}, \code{gun_registry},
\code{immigration_separation}, \code{immigration_system}, \code{immigration_wire},
\code{impeach_trump}, \code{israel}, \code{marijuana}, \code{maternityleave},
\code{medicare_for_all}, \code{military_size}, \code{minwage}, \code{muslimban},
\code{oil_and_gas}, \code{reparations}, \code{right_to_work}, \code{ten_commandments},
\code{trade}, \code{trans_military}, \code{uctaxes2}, \code{vouchers}, \code{gov_insurance},
\code{public_option}, \code{health_subsidies}, \code{path_to_citizenship}, \code{dreamers},
\code{deportation}, \code{ban_guns}, \code{ban_assault_rifles}, \code{limit_magazines}.
}
\examples{
# Design variables
head(ns_wave1[, c("response_id", "weight", "age", "gender")])

# Inspect a battery item's metadata
attr(ns_wave1$group_favorability_blacks, "label")
attr(ns_wave1$group_favorability_blacks, "question_preface")
attr(ns_wave1$news_sources_cnn, "labels")

# Create a calibrated survey design (correct approach for raked
# non-prob samples)
svy <- as_survey_nonprob(ns_wave1, weights = weight)
get_freqs(svy, pres_approval)

# Party identification distribution
table(ns_wave1$pid3)
}
\references{
Tausanovitch, Chris and Lynn Vavreck. 2021. Democracy Fund + UCLA
Nationscape, October 10–17, 2019 (version 20210301). Retrieved from
voterstudygroup.org/data/nationscape.

Rivers, Douglas and Delia Bailey. 2009. "Inference from matched samples in
the 2008 U.S. national elections." Proceedings of the Joint Statistical
Meetings, Social Statistics Section.
}
\keyword{datasets}
