surveycore — Modern Survey Analysis Infrastructure • surveycore

surveycore is the foundation of the surveyverse ecosystem — a modern, tidyverse-compatible replacement for the survey and srvyr packages in R.

It provides S7-based survey design objects with:

A tidy-select interface (ids = c(psu, ssu), no formula syntax)
Automatic preservation of haven-style variable labels and value labels
Exact variance estimation (Taylor linearization, replicate weights, two-phase designs)
Seamless conversion to and from survey::svydesign and srvyr::tbl_svy

Installation

# From CRAN:
install.packages("surveycore")

# Development version from GitHub:
# install.packages("pak")
pak::pak("JDenn0514/surveycore")

What surveycore provides

S7 survey objects: survey_taylor, survey_replicate, survey_twophase
Constructors: as_survey(), as_survey_rep(), as_survey_twophase()
Metadata system: set_var_label(), set_val_labels(), extract_var_label(), extract_val_labels() — with automatic haven attribute import
Analysis functions: get_freqs(), get_means(), get_totals(), get_corr(), get_quantiles(), get_ratios()
Design utilities: update_design(), as_svydesign(), from_svydesign(), as_tbl_svy(), from_tbl_svy()

Basic usage

library(surveycore)

# ── Simple SRS design ──────────────────────────────────────────────────────────
set.seed(42)
df <- data.frame(
  psu     = rep(1:10, each = 10),
  strata  = rep(c("A", "B"), each = 50),
  weight  = runif(100, 0.5, 2),
  income  = rnorm(100, 50000, 10000),
  age     = sample(18:80, 100, replace = TRUE)
)

d <- as_survey(df, ids = psu, weights = weight, strata = strata, nest = TRUE)
d
#> 
#> ── Survey Design ───────────────────────────────────────────────────────────────
#> <survey_taylor> (Taylor series linearization)
#> Sample size: 100
#> 
#> # A tibble: 100 × 5
#>      psu strata weight income   age
#>    <int> <chr>   <dbl>  <dbl> <int>
#>  1     1 A       1.87  53219.    42
#>  2     1 A       1.91  42162.    33
#>  3     1 A       0.929 65757.    71
#>  4     1 A       1.75  56429.    41
#>  5     1 A       1.46  50898.    50
#>  6     1 A       1.28  52766.    78
#>  7     1 A       1.60  56793.    55
#>  8     1 A       0.702 50898.    60
#>  9     1 A       1.49  20069.    58
#> 10     1 A       1.56  52849.    39
#> # ℹ 90 more rows

# ── Weighted mean and total ────────────────────────────────────────────────────
get_means(d, income)
#> # A tibble: 1 × 4
#>     mean ci_low ci_high     n
#>    <dbl>  <dbl>   <dbl> <int>
#> 1 50206. 47921.  52490.   100
get_totals(d, income)
#> # A tibble: 1 × 4
#>      total   ci_low  ci_high     n
#>      <dbl>    <dbl>    <dbl> <int>
#> 1 6460063. 5906356. 7013770.   100

Complex survey designs

# ── Replicate weights (BRR) ───────────────────────────────────────────────────
df_rep <- data.frame(
  y    = rnorm(20),
  wt   = runif(20, 1, 3),
  rep1 = runif(20, 0.5, 2),
  rep2 = runif(20, 0.5, 2),
  rep3 = runif(20, 0.5, 2),
  rep4 = runif(20, 0.5, 2)
)

d_rep <- as_survey_rep(
  df_rep,
  weights    = wt,
  repweights = starts_with("rep"),
  type       = "BRR"
)
d_rep
#> 
#> ── Survey Design ───────────────────────────────────────────────────────────────
#> <survey_replicate> (BRR, 4 replicates)
#> Sample size: 20
#> 
#> # A tibble: 20 × 6
#>         y    wt  rep1  rep2  rep3  rep4
#>     <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 -2.00   2.30 1.09  0.849 0.705 1.71 
#>  2  0.334  2.84 0.619 1.37  0.766 1.90 
#>  3  1.17   1.73 1.74  1.76  1.28  1.75 
#>  4  2.06   2.71 0.609 0.698 1.72  0.691
#>  5 -1.38   1.60 0.672 1.84  0.673 1.47 
#>  6 -1.15   1.93 1.46  1.18  1.84  1.54 
#>  7 -0.706  1.29 0.981 1.84  1.36  0.548
#>  8 -1.05   2.62 0.783 0.873 0.720 1.88 
#>  9 -0.646  2.33 1.09  0.626 1.85  1.22 
#> 10 -0.185  1.12 1.79  0.573 0.880 0.900
#> # ℹ 10 more rows

Variable labels

surveycore preserves haven-style labels automatically when reading .xpt or .sav files. You can also set labels manually:

d2 <- set_var_label(d, income, "Annual household income (USD)")
d2 <- set_var_label(d2, age, "Respondent age in years")

extract_var_label(d2, income)
#> [1] "Annual household income (USD)"
extract_var_label(d2, age)
#> [1] "Respondent age in years"

Conversion to/from survey and srvyr

# To survey::svydesign
svy <- as_svydesign(d)
class(svy)
#> [1] "survey.design2" "survey.design"

# Back to surveycore
d_rt <- from_svydesign(svy)
d_rt

The surveyverse ecosystem

surveycore is the foundation of the surveyverse — a family of packages built around it:

surveytidy — dplyr verbs (filter(), select(), mutate(), group_by()) that respect survey design structure, so grouped summaries and subsetting always propagate weights and strata correctly.
surveyweights — calibration and post-stratification for survey weights. Coming soon.

License

GPL-3. Variance estimation code vendored from the survey package (Thomas Lumley, GPL-2/GPL-3) — see VENDORED.md for full attribution.