Package index • surveycore

Survey design constructors

Create survey design objects from a data frame. All use a tidy-select interface — bare column names, no formula syntax.

as_survey(): Create a Taylor Series Linearization Survey Design
as_survey_replicate(): Create a Replicate Weights Survey Design
as_survey_twophase(): Create a Two-Phase Survey Design
as_survey_nonprob() experimental: Create a Calibrated / Non-Probability Survey Design
update_design(): Update Design Variables on an Existing Survey Object

Estimation

Compute weighted estimates with design-correct standard errors.

meta(): Extract Metadata from a Survey Result
get_freqs(): Weighted Frequency Tables for Categorical Survey Variables
get_means(): Weighted Mean for a Survey Design
get_totals(): Weighted Total for a Survey Design
get_corr(): Survey-Weighted Pearson Correlation
get_quantiles(): Survey-Weighted Quantiles
get_ratios(): Survey-Weighted Ratio Estimation
get_diffs(): Treatment Effect Estimation for Survey Designs

Regression

Survey-weighted generalised linear models with Binder (1983) sandwich variance estimation.

survey_glm(): Fit a Survey-Weighted Generalised Linear Model
survey_glm_fit(): Survey-Weighted GLM Fit Object
clean(): Tidy a Survey GLM Fit

Metadata — setters

Assign variable labels, value labels, question prefaces, notes, universe strings, and missing codes. All setters accept the three-convention API: named ..., a single named vector/list, or variable + content argument.

set_var_label(): Set Variable Label(s)
set_val_labels(): Set Value Labels
set_question_preface(): Set Question Preface(s)
set_var_note(): Set Analyst Note(s)
set_universe(): Set Universe Description(s)
set_missing_codes(): Set Missing Code(s)
infer_question_prefaces(): Infer Question Prefaces from Variable Labels

Metadata — extractors

Retrieve metadata for one or more variables.

extract_var_label(): Extract Variable Labels
extract_val_labels(): Extract Value Labels
extract_question_preface(): Extract Question Prefaces
extract_var_note(): Extract Analyst Notes
extract_universe(): Extract Universe Descriptions
extract_missing_codes(): Extract Missing Value Codes
extract_metadata(): Extract All Metadata for Variables
survey_weighting_history(): Extract the Weighting History from a Survey Object

Conversion

Convert between surveycore objects, survey::svydesign, and srvyr::tbl_svy.

as_svydesign(): Convert a surveycore Design Object to a survey Package Design
from_svydesign(): Convert a survey Package Design to a surveycore Design Object
as_tbl_svy(): Convert a surveycore Design Object to an srvyr tbl_svy
from_tbl_svy(): Convert an srvyr tbl_svy to a surveycore Design Object

S7 class objects

S7 classes exported for use in downstream packages and extension code. Use S7::S7_inherits(x, survey_taylor) for class testing.

survey_base(): Abstract Base Survey Design Class
survey_taylor(): Taylor Series Linearization Survey Design
survey_replicate(): Replicate Weights Survey Design
survey_twophase(): Two-Phase Survey Design
survey_nonprob(): Calibrated / Non-Probability Survey Design
survey_metadata(): Survey Metadata Container

Utilities

Internal helpers exported for use in extension packages.

survey_data(): Access the Data Component of a Survey Design Object
SURVEYCORE_DOMAIN_COL: Internal Domain Column Name Constant
.get_design_vars_flat(): Get design variable column names

Example datasets

Real-world survey datasets included for testing and illustration.

nhanes_2017: NHANES 2017-2018: Demographics and Blood Pressure
acs_pums_wy: ACS PUMS 2022 1-Year: Wyoming Persons
anes_2024: ANES 2024: American National Election Studies Time Series
gss_2024: GSS 2024: General Social Survey
pew_jewish_2020: Pew Jewish Americans 2020
pew_npors_2025: Pew NPORS 2025: National Public Opinion Reference Survey
ns_wave1: Nationscape Wave 1: July 18, 2019