Compare C-statistics (concordance statistics)
    between two survival models, using either bootstrap resampling (Harrell's C)
    or Uno's C with perturbation-resampling (from the survC1 package). Returns
    confidence intervals and a p-value for the difference in C-statistics.
    Useful for evaluating and comparing predictive performance of survival models.
    Methods implemented for Uno's C are described in Uno et al. (2011) <doi:10.1002/sim.4154>.

It has been designed to calculate the required sample size in randomized clinical trials with composite endpoints. It also calculates the expected effect and the probability of observing the composite endpoint, among others. The methodology can be found in Bofill & Gómez (2019) <doi:10.1002/sim.8092> and Gómez & Lagakos (2013) <doi:10.1002/sim.5547>.

Compares two dataframes which have the same column
    structure to show the rows that have changed. Also gives a git style diff format
    to quickly see what has changed in addition to summary statistics.

Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.

Manages comparison of MCMC performance metrics from multiple MCMC algorithms. These may come from different MCMC configurations using the 'nimble' package or from other packages. Plug-ins for JAGS via 'rjags' and Stan via 'rstan' are provided. It is possible to write plug-ins for other packages. Performance metrics are held in an MCMCresult class along with samples and timing data. It is easy to apply new performance metrics. Reports are generated as html pages with figures comparing sets of runs. It is possible to configure the html pages, including providing new figure components.