Allows users to stem Persian texts for text analysis.

Automated identification of printed array positions from high content 
    microscopy images and the export of those positions as individual images 
    written to output as multi-layered tiff files.

Provides functions for fitting and validation of models for subgroup
    identification and personalized medicine / precision medicine under the general subgroup
    identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>.
    This package is intended for use for both randomized controlled trials and
    observational studies and is described in detail in Huling and Yu (2021) 
    <doi:10.18637/jss.v098.i05>.

Implements the methodology of Huling, Smith, and 
    Chen (2020) <doi:10.1080/01621459.2020.1801449>, which allows for subgroup identification 
    for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part 
    modeling framework to handle semi-continuous data by separately modeling the positive part 
    of the outcome and an indicator of whether each outcome is positive, but still results in a 
    single treatment rule. High dimensional data is handled with a cooperative lasso penalty, 
    which encourages the coefficients in the two models to have the same sign.

Functions to setup a personal R package that attaches given
    libraries and exports personal helper functions.

An R-package-version of an open online science-based personality
    test from <https://openpsychometrics.org/tests/IPIP-BFFM/>,
    providing a better-designed interface and a more detailed report.
    The core command launch_test() opens a personality test in your browser,
    and generates a report after you click "Submit". In this report, your results
    are compared with other people's, to show what these results mean.
    Other people's data is from <https://openpsychometrics.org/_rawdata/BIG5.zip>.

Provides a robust framework for analyzing the extent to which differential survival with respect to higher level trait variation is reducible to lower level variation. In addition to its primary test, it also provides functions for simulation-based power analysis, reading in common data set formats, and visualizing results. Temporarily contains an edited version of function hr.mcp() from package 'wild1', written by Glen Sargeant. For tutorial see: http://evolve.zoo.ox.ac.uk/Evolve/Perspectev.html.