Makes it easy to push data to 'Power BI' using R and the 'Power BI 
    REST APIs' (see <https://docs.microsoft.com/en-us/rest/api/power-bi/>). 
    A set of functions for turning data frames into 'Power BI' datasets and 
    refreshing these datasets are provided. Administrative tasks such as 
    monitoring refresh statuses and pulling metadata about workspaces and users
    are also supported.

Functions for bootstrapping the power of ANOVA designs
    based on estimated means and standard deviations of the conditions.
    Please refer to the documentation of the boot.power.anova() function
    for further details.

A power analysis tool for jointly testing the cause-1 cause-specific hazard and the any-cause hazard with competing risks data.

Power and sample size calculation for bulk tissue and single-cell eQTL analysis
             based on ANOVA, simple linear regression, or linear mixed effects model. It can also calculate power/sample size 
             for testing the association of a SNP to a continuous type phenotype.
             Please see the reference: Dong X, Li X, Chang T-W, Scherzer CR, Weiss ST, Qiu W. (2021) <doi:10.1093/bioinformatics/btab385>.

Power estimation and sample size calculation for 10X Visium Spatial Transcriptomics data to detect differential expressed genes between two conditions based on bootstrap resampling. See Shui et al. (2024) <doi:10.1101/2024.08.30.610564> for method details.

Analytical power calculations for GxE and GxG interactions for case-control studies of candidate genes and genome-wide association studies (GWAS). This includes power calculation for four two-step screening and testing procedures.  It can also calculate power for GxE and GxG without any screening.

This R package allows the determination of some distributions of the voters' power when passing laws in weighted voting situations.

We extend 'dplyr' and 'fuzzyjoin' join functions with
    features to preprocess the data, apply various data checks, and deal with
    conflicting columns.