Provides a variety of functions useful for data analysis,
    selection, manipulation, and graphics.

Runs a Shiny web application that merges raw 'qPCR' fluorescence data with related 
    metadata to visualize species presence/absence detection patterns and assess data quality. 
    The application calculates threshold values from raw fluorescence data using a method based 
    on the second derivative method, Luu-The et al (2005) <doi:10.2144/05382RR05>,  and utilizes 
    the ‘chipPCR’ package by Rödiger, Burdukiewicz, & Schierack (2015) <doi:10.1093/bioinformatics/btv205> 
    to calculate Cq values. The application has the ability to connect to a custom developed MySQL 
    database to populate the applications interface. The application allows users to interact with 
    visualizations such as a dynamic map, amplification curves and standard curves, that allow for 
    zooming and/or filtering. It also enables the generation of customized exportable reports based
    on filtered mapping data.

Contains model-based treatment of missing data for regression 
    models with missing values in covariates or the dependent 
    variable using maximum likelihood or Bayesian estimation 
    (Ibrahim et al., 2005; <doi:10.1198/016214504000001844>;
    Luedtke, Robitzsch, & West, 2020a, 2020b;
    <doi:10.1080/00273171.2019.1640104><doi:10.1037/met0000233>).
    The regression model can be nonlinear (e.g., interaction 
    effects, quadratic effects or B-spline functions). 
    Multilevel models with missing data in predictors are
    available for Bayesian estimation. Substantive-model compatible 
    multiple imputation can be also conducted.

Allows users to conduct multivariate distance matrix regression using analytic p-values and compute measures of effect size. For details on the method, see McArtor, Lubke, & Bergeman (2017) <doi:10.1007/s11336-016-9527-8>.

Statistical inference for quadratic functional of the moderate-dimensional linear model in Guo and Cheng (2021) <DOI:10.1080/01621459.2021.1893177>.