svySE

Sampling Error Estimation for Complex Surveys

svySE is an R package designed to estimate sampling errors and produce indicator tables from complex survey designs.

The package provides a reproducible workflow for calculating weighted totals, proportions, standard errors, confidence intervals, coefficients of variation (CV), design effects (DEFF), unweighted sample sizes, grouped estimates, domain estimates, and customizable Excel reports.

Built on top of the survey package, svySE simplifies the routine production of official survey indicators while preserving the methodological principles of design-based estimation.

Why svySE?

Many organizations repeatedly implement similar survey estimation procedures using custom scripts.

svySE was developed to standardize these procedures into a single workflow that is:

Reproducible
Flexible
Easy to configure
Methodologically consistent
Suitable for official statistics
Suitable for academic research

Although initially developed from practical experience in official statistics, the package is intended for any researcher or institution working with complex survey data.

Main Features

✔ Complex survey estimation using the survey package

✔ Weighted totals

✔ Weighted proportions

✔ Standard errors

✔ Confidence intervals

✔ Coefficients of variation (CV)

✔ Design effects (DEFF)

✔ Unweighted sample sizes

✔ Domain estimation

✔ Grouped estimation

✔ Configurable survey settings

✔ Customizable Excel exports

Workflow

The typical workflow consists of only three steps.

Configure survey estimation
        │
        ▼
   svySE_cfg()
        │
        ▼
Calculate sampling errors
        │
        ▼
  svySE_calc()
        │
        ▼
Export results
        │
        ▼
  svySE_xlsx()

Installation

Development version

install.packages("remotes")

remotes::install_github("lburgoss/svySE")

Basic Example

library(svySE)

set.seed(123)

df <- data.frame(
  dept = rep(c("A", "B", "C"), each = 50),
  strata = rep(c("A", "B", "C"), each = 50),
  weight = runif(150, 10, 50),
  ind_1 = sample(c(0, 1), 150, replace = TRUE)
)

cfg <- svySE_cfg(
  estimator = "prop",
  target = 1,
  valid_values = c(0,1),
  lonely_psu = "adjust"
)

res <- svySE_calc(
  data = df,
  indicators = "ind_1",
  group_vars = "dept",
  group_labels = "Department",
  strata = "strata",
  weight = "weight",
  cfg = cfg
)

print(res)

Export Results

tmp_err <- tempfile(fileext = ".xlsx")
tmp_tab <- tempfile(fileext = ".xlsx")

svySE_xlsx(
    x = res,
    file_err = tmp_err,
    file_tab = tmp_tab,
    cols_err = svySE_cols_err("full"),
    cols_tab = svySE_cols_tab("full")
)

Main Functions

Function	Description
`svySE_cfg()`	Configure survey estimation settings
`svySE_calc()`	Calculate sampling errors
`svySE_xlsx()`	Export results to Excel
`svySE_cols_err()`	Select error table columns
`svySE_cols_tab()`	Select simple table columns

Documentation

The package includes:

Reference manual
Package vignettes
Function documentation
Examples
Unit tests

Complete documentation is available directly in R:

help(package = "svySE")

browseVignettes("svySE")

Development Status

svySE is under active development.

Future releases will incorporate additional estimators for complex survey analysis while maintaining compatibility with the survey package.

Author

Luis Burgos

Statistician • RENACYT Researcher (Peru)

Sampling Specialist

National Institute of Statistics and Informatics (INEI)

ENCAL — Public Expenditure Quality Monitoring Survey

The package was developed independently based on professional experience in complex survey sampling, official statistics, and statistical programming.

📧 lburgoss1996@gmail.com

Suggestions, bug reports, and feature requests are welcome through the GitHub issue tracker.

License

MIT License