A testing method for inferring microbial networks. It differs from existing microbial network analyses in that it provides calibrated results by controlling the false discovery rate. The method accounts for the complex features of taxa count data. It also accommodates both independent and clustered samples, offers separate linear and nonlinear tests for each pair of taxa, and includes an omnibus test that bypasses the need to specify the type of relationship for each pair of taxa.

Provides nonparametric permutation tests for testing all or
    any subset of random effects in linear and nonlinear mixed-effects
    models, without requiring normality or other distributional
    assumptions on random effects or errors. Three distribution-free
    variance-component estimators are implemented: Variance Least
    Squares ('VLS'), Method of Moments ('MM'), and Method of Moments
    with First-Order Approximation ('MMF'). A permutation procedure is
    used to obtain finite-sample p-values. Plotting functions support
    data exploration, model evaluation, and communication of results.
    Methods are described in Uwimpuhwe, Drikvandi, and Blozis (2026)
    <doi:10.1002/sim.70605>.

GUI for entering test items and obtaining raw
   and transformed scores. The results are shown on the
   console and can be saved to a tabular text file for further
   statistical analysis. The user can define his own tests and
   scoring procedures through a GUI.

Provides functionality of a statistical testing implementation whether a dataset comes from a symmetric distribution when the center of symmetry is unknown, including Wilcoxon test and sign test procedure. In addition, sample size determination for both tests is provided. The Wilcoxon test procedure is described in Vexler et al. (2023) <https://www.sciencedirect.com/science/article/abs/pii/S0167947323000579>, and the sign test is outlined in Gastwirth (1971) <https://www.jstor.org/stable/2284233>.

Software testing is important, but, in part because it is
    frustrating and boring, many of us avoid it. 'testthat' is a testing
    framework for R that is easy to learn and use, and integrates with
    your existing 'workflow'.