Asymptotic simultaneous confidence intervals for comparison of many treatments with one control,
 for the difference of binomial proportions, allows for Dunnett-like-adjustment, Bonferroni or unadjusted intervals.
 Simulation of power of the above interval methods, approximate calculation of any-pair-power, and sample size
 iteration based on approximate any-pair power. Exact conditional maximum test for many-to-one comparisons to a control.

Generation of multiple binary and continuous non-normal variables simultaneously 
             given the marginal characteristics and association structure based on the methodology 
             proposed by Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

Generating multiple binary and normal variables simultaneously given marginal characteristics and association structure based on the methodology proposed by Demirtas and Doganay (2012) <DOI:10.1080/10543406.2010.521874>.

Constructs confidence intervals on the probability of
        success in a binomial experiment via several parameterizations.

Twelve confidence intervals for one binomial proportion or a vector of binomial proportions are computed. The confidence intervals are: Jeffreys,  Wald, Wald corrected, Wald, Blyth and Still,  Agresti and Coull, Wilson, Score, Score corrected, Wald logit, Wald logit corrected, Arcsine and Exact binomial. References include, among others: Vollset, S. E. (1993). "Confidence intervals for a binomial proportion". Statistics in Medicine, 12(9): 809-824. <doi:10.1002/sim.4780120902>.

Detection of a statistically significant trend in the data provided by the user.
    This is based on the a signed test based on the binomial distribution.
    The package returns a trend test value, T, and also a p-value. A T value 
    close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing
    trend. A T value close to 0 indicates no trend. There is also a command to visualize
    the trend. A test data set called gtsa_data is also available, which has global mean 
    temperatures for January, April, July, and October for the years 1851 to 2022.
    Reference: Walpole, Myers, Myers, Ye. (2007, ISBN: 0-13-187711-9).