boot, lavaan, MASS, methods, mnormt, nlme, OpenMx, parallel,
sem, semTools
Implements methods that are useful in designing research studies and analyzing data, with
particular emphasis on methods that are developed for or used within the behavioral,
educational, and social sciences (broadly defined). That being said, many of the methods
implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a
suite of functions for a variety of related topics, such as effect sizes, confidence intervals
for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size
planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and
minimum-risk point estimation perspectives), mediation analysis, various properties of
distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally
an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became
more general and now contains methods applicable and used in a wide variety of fields and is an
orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has
greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed
list of those that have contributed and other details.

Spatial Designs for Ecological and Environmental Surveys
Provides spatially balanced designs from a set of (contiguous) potential sampling locations in a study region. Accommodates , without detrimental effects on spatial balance, sites that the researcher wishes to include in the survey for reasons other than the current randomisation (legacy sites).
mgcv, geometry, randtoolbox, mvtnorm, stats, class

Provides spatially survey balanced designs using the quasi-random number method described Robinson et al. (2013) <doi:10.1111/biom.12059>. These designs can accommodate, without substantial detrimental effects on spatial balance, legacy sites (Foster et al., 2017 <doi:10.1111/2041-210X.12782>), and for both point samples and transect samples (Foster et al. 2020, <doi:10.1111/2041-210X.13321>).  Additional information about the package use itself is given in Foster (2021) <doi:10.1111/2041-210X.13535>.
mgcv, geometry, randtoolbox, mvtnorm, stats, class, parallel