The Taylor Russell model is a widely used method for assessing test validity in personnel selection tasks. The three functions in this package extend this model in a number of notable ways. TR() estimates test validity for a single selection test via the original Taylor Russell model. It extends this model by allowing users greater flexibility in argument choice. For example, users can specify any three of the four parameters (base rate, selection ratio, criterion validity, and positive predictive value) of the Taylor Russell model and estimate the remaining parameter (see the help file for examples).  The TaylorRussell() function generalizes the original Taylor Russell model to allow for multiple selection tests (predictors).  To our knowledge, this is the first generalization of the Taylor Russell model to allow for three or more selection tests (it is also the first to correctly handle models with two selection tests). TRDemo() is a 'shiny' program for illustrating the underlying logic of the Taylor Russell model. Taylor, HC and Russell, JT (1939) "The relationship of validity coefficients to the practical effectiveness of tests in selection: Discussion and tables" <doi:10.1037/h0057079>.

For when your colors absolutely should not be excluded from the narrative.

A collection of interactive 'shiny' applications for performing comprehensive analyses in the field of tree breeding and genetics. The package is designed to assist users in visualizing and interpreting experimental data through a user-friendly interface. Each application is launched via a simple function, and users can upload data in 'Excel' format for analysis. For more information, refer to Singh, R.K. and Chaudhary, B.D. (1977, ISBN:9788176633079).

Estimation of the survivor average causal effect under outcomes truncated by death, which requires the existence of a substitution variable. It can be applied to both experimental and observational data.

Functions are provided for prior specification in divergence time
    estimation using fossils as well as other kinds of data. It
    provides tools for interacting with the input and output of Bayesian
    platforms in evolutionary biology such as 'BEAST2', 'MrBayes', 'RevBayes',
    or 'MCMCTree'.
    It Implements a simple measure similarity between probability
    density functions for comparing prior and
    posterior Bayesian densities, as well as code for calculating the
    combination of distributions using conflation of Hill (2008). Functions for estimating the
    origination time in collections of distributions using the x-intercept (e.g., Draper and Smith, 1998) and
    stratigraphic intervals (Marshall 2010) are also available.
    Hill, T. 2008. "Conflations of probability distributions". Transactions of the American Mathematical Society, 363:3351-3372. <doi:10.48550/arXiv.0808.1808>,
    Draper, N. R. and Smith, H. 1998. "Applied Regression Analysis". 1--706. Wiley Interscience, New York. <DOI:10.1002/9781118625590>,
    Marshall, C. R. 2010. "Using confidence intervals to quantify the uncertainty in the end-points of stratigraphic ranges". Quantitative Methods in Paleobiology, 291--316. <DOI:10.1017/S1089332600001911>.