Compute power and sample size for linear models of longitudinal
    data. Supported models include mixed-effects models and models fit by
    generalized least squares and generalized estimating equations. The package
    is described in Iddi and Donohue (2022) <DOI:10.32614/RJ-2022-022>. Relevant
    formulas are derived by Liu and Liang (1997) <DOI:10.2307/2533554>, 
    Diggle et al (2002) <ISBN:9780199676750>, and Lu, Luo, and Chen (2008)
    <DOI:10.2202/1557-4679.1098>.

Performs variety of viral quasispecies diversity analyses [see Gregori et al. (2016) <doi:10.1016/j.virol.2016.03.017>] based on long-read sequence alignment. Main functions include 1) sequencing error minimization and read sampling, 2) Single nucleotide variant (SNV) profiles comparison, and 3) viral quasispecies profiles comparison and visualization.

Time-dependent Receiver Operating Characteristic curves, Area Under the Curve, and Net Reclassification Indexes for repeated measures. It is based on methods in Barbati and Farcomeni (2017) <doi:10.1007/s10260-017-0410-2>.

Performs recursive partitioning of linear and nonlinear mixed effects models,
    specifically for longitudinal data. The package is an
    extension of the original 'longRPart' package by 
    Stewart and Abdolell (2013) <https://cran.r-project.org/package=longRPart>.

Assess the proportion of treatment effect explained by a longitudinal surrogate marker as described in Agniel D and Parast L (2021) <doi:10.1111/biom.13310>.

Tools are provided to expand vectors of short URLs into long 'URLs'. 
    No 'API' services are used, which may mean that this operates more slowly than 
    'API' services do (since they usually cache results of expansions that every 
    user of the service requests). You can setup your own caching layer with the 
    'memoise' package if you wish to have a speedup during single sessions or add 
    larger dependencies, such as 'Redis', to gain a longer-term performance boost 
    at the expense of added complexity.