Tools to process CBASS-derived PAM data efficiently. Minimal requirements are PAM-based photosynthetic efficiency data (or data from any other continuous variable that changes with temperature, e.g. relative bleaching scores) from 4 coral samples (nubbins) subjected to 4 temperature profiles of at least 2 colonies from 1 coral species from 1 site. Please refer to the following CBASS (Coral Bleaching Automated Stress System) papers for in-depth information regarding CBASS acute thermal stress assays, experimental design considerations, and ED5/ED50/ED95 thermal parameters: Nicolas R. Evensen et al. (2023) <doi:10.1002/lom3.10555> Christian R. Voolstra et al. (2020) <doi:10.1111/gcb.15148> Christian R. Voolstra et al. (2025) <doi:10.1146/annurev-marine-032223-024511>.

Implementation of the d/p/q/r family of functions for a continuous analog to the standard discrete beta-binomial with continuous size parameter and continuous support with x in [0, size + 1].

Compare baseline characteristics between two or more groups. The variables being compared can be factor and numeric variables. The function will automatically judge the type and distribution of the variables, and make statistical description and bivariate analysis.

Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, frequency-based designs, and D-optimal designs, as well as "labeled" designs (also known as "alternative-specific designs"), designs with "no choice" options, and designs with dominant alternatives removed. Conveniently inspect and compare designs using a variety of metrics, including design balance, overlap, and D-error, and simulate choice data for a survey design either randomly or according to a utility model defined by user-provided prior parameters. Conduct a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Bayesian D-efficient designs using the 'cea' and 'modfed' methods are obtained using the 'idefix' package by Traets et al (2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the 'logitr' package by Helveston (2023) <doi:10.18637/jss.v105.i10>.