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.

This tool is designed to analyze up to 5 Fraud Detection Questions integrated into a survey, focusing on potential fraudulent participants to clean the survey dataset from potential fraud. Fraud Detection Questions and further information available at <https://surveydefense.org>.

Generate programmable surveys using markdown and R code chunks. Surveys
    are composed of two files: a survey.qmd 'Quarto' file defining the
    survey content (pages, questions, etc), and an app.R file defining a
    'shiny' app with global settings (libraries, database configuration,
    etc.) and server configuration options (e.g., conditional skipping /
    display, etc.). Survey data collected from respondents is stored in a
    'PostgreSQL' database. Features include controls for conditional skip
    logic (skip to a page based on an answer to a question), conditional
    display logic (display a question based on an answer to a question), a
    customizable progress bar, and a wide variety of question types,
    including multiple choice (single choice and multiple choices),
    select, text, numeric, multiple choice buttons, text area, and dates.
    Because the surveys render into a 'shiny' app, designers can also
    leverage the reactive capabilities of 'shiny' to create dynamic and
    interactive surveys.