Offers several functions for Configural Frequencies Analysis (CFA), which is a useful statistical tool for the analysis of multiway contingency tables. CFA was introduced by G. A. Lienert as 'Konfigurations Frequenz Analyse - KFA'. Lienert, G. A. (1971). Die Konfigurationsfrequenzanalyse: I. Ein neuer Weg zu Typen und Syndromen. Zeitschrift für Klinische Psychologie und Psychotherapie, 19(2), 99–115.

For multiple testing.
    Computes estimates and confidence bounds for the
    False Discovery Proportion (FDP), the fraction of false positives among
    all rejected hypotheses.
    The methods in the package use permutations of the data. Doing so, they
    take into account the dependence structure in the data.

Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists.
    The intended usage is to allow the tool to work with the outputs of machine learning classification models. 
    This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs.
    This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time.
    Traditionally, this approach has been used for highlighting model representation and feature slippage.

Download and read data on United States congressional proceedings. 
    Data is read from the Library of Congress's Congress.gov Application Programming 
    Interface (<https://github.com/LibraryOfCongress/api.congress.gov/>). Functions
    exist for all version 3 endpoints, including for bills, amendments, congresses, 
    summaries, members, reports, communications, nominations, and treaties.

A tool that imports, subsets, and exports the 'CongressData' dataset. 'CongressData' contains approximately 800 variables concerning all US congressional districts with data back to 1789. The dataset tracks district characteristics, members of Congress, and the political behavior of those members. Users with only a basic understanding of R can subset this data across multiple dimensions, export their search results, identify the citations associated with their searches, and more.