Calculate robust measures of effect sizes using the bootstrap.

Compare dissolution profiles with confidence interval of similarity
  factor f2 using bootstrap methodology as described in the literature, such as 
  Efron and Tibshirani (1993, ISBN:9780412042317), Davison and Hinkley (1997,
  ISBN:9780521573917), and Shah et al. (1998) <doi:10.1023/A:1011976615750>. 
  The package can also be used to simulate dissolution profiles based on 
  mathematical modelling and multivariate normal distribution.

Bootstrap based goodness-of-fit tests. It allows
    to perform rigorous statistical tests to check if a chosen
    model family is correct based on the marked empirical
    process. The implemented algorithms are described in
    (Dikta and Scheer (2021) <doi:10.1007/978-3-030-73480-0>)
    and can be applied
    to generalized linear models without any further implementation
    effort. As far as certain linearity conditions are fulfilled
    the resampling scheme are also applicable beyond generalized
    linear models. This is reflected in the software architecture
    which allows to reuse the resampling scheme by implementing
    only certain interfaces for models that are not supported
    natively by the package.

Implements a bootstrap-based heterogeneity test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (or) in meta-analysis studies. Depending on the presence of moderators, this Monte Carlo based test can be implemented in the random- or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihoods, so installation of R package 'metafor' is required. This approach refers to the studies of Anscombe (1956) <doi:10.2307/2332926>, Haldane (1940) <doi:10.2307/2332614>, Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).