Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation.

Implements different kinds of bootstraps
    to estimate sampling variation from survey data with 
    complex designs. Includes the rescaled bootstrap
    described in Rust and Rao (1996) <doi:10.1177/096228029600500305> and
    Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>.

Performs canonical correlation for survey data, including 
  multiple tests of significance for secondary canonical correlations. 
  A key feature of this package is that it incorporates survey data structure 
  directly in a novel test of significance via a sequence of simple linear 
  regression models on the canonical variates. See reference - Cruz-Cano, 
  Cohen, and Mead-Morse (2024) "Canonical Correlation Analysis of Survey data: the SurveyCC R package" 
  The R Journal under review.

Functions to generate K-fold cross validation (CV) folds
    and CV test error estimates that take into account
    how a survey dataset's sampling design was constructed
    (SRS, clustering, stratification, and/or unequal sampling weights).
    You can input linear and logistic regression models, along with data and a 
    type of survey design in order to get an output that can help you determine
    which model best fits the data using K-fold cross validation.
    Our paper on "K-Fold Cross-Validation for Complex Sample Surveys"
    by Wieczorek, Guerin, and McMahon (2022)
    <doi:10.1002/sta4.454>
    explains why differing how we take folds based on survey design is useful.

Data obtained from surveys contains information not only about the
    survey responses, but also the survey metadata, e.g. the original survey
    questions and the answer options. The 'surveydata' package makes it easy to
    keep track of this metadata, and to easily extract columns with
    specific questions.