The NADA2 package

The NADA2 package for R adds many new functions beyond those in the NADA package, adding more types of hypothesis tests including permutation tests for censored data, methods for trend analysis, multivariate methods, and more. None of the methods substitute 1/2DL or similar values for nondetects, but use maximum likelihood, nonparametric ranking procedures, and graphical methods based on percentiles to perform statistical methods for left-censored data including data below detection and quantitation limits.

Hundreds of articles have used the procedures in NADA and NADA2 to evaluate their data without substituting fabricated values for nondetects. A list of only a few of these articles is on our NADA2 references page.

Below is a video (approx. 53 minutes) that demonstrates what NADA2 can do for you. The Reference Manual and Vignette files on the NADA2 website https://CRAN.R-project.org/package=NADA2 provide written guidance on how to get the most out of this software.
NADA2: Everything You Can Do Today With Nondetects
What statistical analyses can you do today for data with nondetects without substituting numbers like ½ the detection limit? It is essentially every analysis you do when there are no nondetects. Our NADA online course teaches you to use the NADA2 package for R, including routines for drawing boxplots, scatterplots with fitted models, and probability plots to determine how well a standard distribution such as the normal, lognormal or gamma fit the data. You can compute prediction and tolerance intervals, and perform hypothesis tests (parametric, nonparametric and permutation varieties). Follow that up with multiple comparison tests to determine which groups differ from others. You can compute correlation coefficients, build and evaluate regression models to find the best model. You can perform trend analysis such as the seasonal Kendall test while adjusting for the effect of exogenous variables that are not time. You can even compute multivariate procedures such as cluster analysis, NMDS plots, PCA (Principal Components Analysis) and multivariate group and trend tests. All without substitution for nondetects. Take a tour of what this R package can do.
approx. 53 mins