Provides test statistics, p-value, and confidence intervals based on 9 hypothesis tests for dependence.

Test functions are often used to test computer code.
  They are used in optimization to test algorithms and in
  metamodeling to evaluate model predictions. This package provides
  test functions that can be used for any purpose.

Develop, evaluate, and score multiple choice examinations, 
 psychological scales, questionnaires, and similar types of data involving
 sequences of choices among one or more sets of answers.
 This version of the package should be considered as brand new.  Almost all
 of the functions have been changed, including their argument list.
 See the file NEWS.Rd in the Inst folder for more information.
 Using the package does not require any formal statistical knowledge 
 beyond what would be provided by a first course in statistics in a 
 social science department.  There the user would encounter the concept 
 of probability and how it is used to model data and make decisions, 
 and would become familiar with basic mathematical and statistical notation.
 Most of the output is in graphical form.

Push a sample population for unit testing on data mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

Test the nullity of covariances, in a set of variables, using a simple univariate procedure. See Marques, Diago, Norouzirad, Bispo (2023) <doi:10.1002/mma.9130>.

Provides a bootstrap test which decides whether two dose response curves can be assumed as equal concerning their maximum absolute deviation. A plenty of choices for the model types are available, which can be found in the 'DoseFinding' package, which is used for the fitting of the models. See <doi:10.1080/01621459.2017.1281813> for details.

Provides two convenience functions assert() and test_pkg() to
    facilitate testing R packages.

GUI for entering test items and obtaining raw
   and transformed scores. The results are shown on the
   console and can be saved to a tabular text file for further
   statistical analysis. The user can define his own tests and
   scoring procedures through a GUI.