A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.

Classical Test and Item analysis, 
  Item Response analysis and data management for educational and psychological tests.

The 'df2yaml' aims to simplify the process of converting 'dataframe' to 'YAML' <https://yaml.org/>. 
    The 'dataframe' with multiple key columns and one value column will be converted to the multi-level hierarchy.

Containing the Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), Detrended Cross-Correlation Coefficient (rhoDCCA), Delta Amplitude Detrended Cross-Correlation Coefficient (DeltarhoDCCA), log amplitude Detrended Fluctuation Analysis (DeltalogDFA), and the Activity Balance Index, it also includes two DFA automatic methods for identifying crossover points and a Deltalog automatic method for identifying reference channels.

Produces SPSS- and SAS-like output for linear discriminant 
  function analysis and canonical correlation analysis. The methods are described in
  Manly & Alberto (2017, ISBN:9781498728966),
  Rencher (2002, ISBN:0-471-41889-7), and
  Tabachnik & Fidell (2019, ISBN:9780134790541).

Computes small-sample degrees of freedom adjustment for
    heteroskedasticity robust standard errors, and for clustered standard errors
    in linear regression. See Imbens and Kolesár (2016)
    <doi:10.1162/REST_a_00552> for a discussion of these adjustments.

A set of functions to perform distribution-free Bayesian analyses. 
             Included are Bayesian analogues to the frequentist Mann-Whitney U 
             test, the Wilcoxon Signed-Ranks test, Kendall's Tau Rank 
             Correlation Coefficient, Goodman and Kruskal's Gamma, McNemar's
             Test, the binomial test, the sign test, the median test, as well as 
             distribution-free methods for testing contrasts among condition and 
             for computing Bayes factors for hypotheses. The package also
             includes procedures to estimate the power of distribution-free
             Bayesian tests based on data simulations using various probability 
             models for the data. The set of functions provide data analysts 
             with a set of Bayesian procedures that avoids requiring parametric 
             assumptions about measurement error and is robust to problem of 
             extreme outlier scores.