Generates binary test data based on Item Response Theory using the two-parameter logistic model (Lord, 1980 <doi:10.4324/9780203056615>). Useful functions for test equating are included, e.g. functions for generating internal and external common items between test forms and a function to create a linkage plans between those forms. Ancillary functions for generating true item and person parameters as well as for calculating the probability of a person correctly answering an item are also included.

Implementation of the boosting procedure with the simulation and extrapolation approach to address variable selection and estimation for high-dimensional data subject to measurement error in predictors. It can be used to address generalized linear models (GLM) in Chen (2023) <doi: 10.1007/s11222-023-10209-3> and the accelerated failure time (AFT) model in Chen and Qiu (2023) <doi: 10.1111/biom.13898>. Some relevant references include Chen and Yi (2021) <doi:10.1111/biom.13331> and Hastie, Tibshirani, and Friedman (2008, ISBN:978-0387848570).

The focus is on simulating and modeling families with founders drawn from a structured population (for example, with different ancestries or other potentially non-family relatedness), in contrast to traditional pedigree analysis that treats all founders as equally unrelated.  Main function simulates a random pedigree for many generations, avoiding close relatives, pairing closest individuals according to a 1D geography and their randomly-drawn sex, and with variable children sizes to result in a target population size per generation.  Auxiliary functions calculate kinship matrices, admixture matrices, and draw random genotypes across arbitrary pedigree structures starting from the corresponding founder values.  The code is built around the plink FAM table format for pedigrees.  Described in Yao and Ochoa (2022) <doi:10.1101/2022.03.25.485885>.

Conducting Bayesian Optimal Interval (BOIN) design for phase I 
    dose-finding trials. 'simFastBOIN' provides functions for pre-computing 
    decision tables, conducting trial simulations, and evaluating operating 
    characteristics. The package uses vectorized operations and the 
    Iso::pava() function for isotonic regression to achieve efficient 
    performance while maintaining full compatibility with BOIN methodology. 
    Version 1.3.2 adds p_saf and p_tox parameters for customizable safety and 
    toxicity thresholds. Version 1.3.1 fixes Date field. Version 1.2.1 adds 
    comprehensive 'roxygen2' documentation and enhanced print formatting with 
    flexible table output options. Version 1.2.0 integrated C-based PAVA for 
    isotonic regression. Version 1.1.0 introduced conservative MTD selection 
    (boundMTD) and flexible early stopping rules (n_earlystop_rule). Methods 
    are described in Liu and Yuan (2015) <doi:10.1111/rssc.12089>.