Detection of item-wise Differential Item Functioning (DIF) 
             in fitted 'mirt', 'multipleGroup' or 'bfactor' models  
             using score-based structural change tests. Under the hood 
             the sctest() function from the 'strucchange' package is used.

In some situations where researchers would like to demonstrate
    causal effects, it is hard to obtain a sample size that would allow for a
    well-powered randomized controlled trial. Single case designs are experimental
    designs that can be used to demonstrate causal effects with only one participant
    or with only a few participants. The 'scdtb' package provides a suite of tools
    for analyzing data from studies that use single case designs. The nap() function
    can be used to compute the nonoverlap of all pairs as outlined by the What
    Works Clearinghouse (2022) <https://ies.ed.gov/ncee/wwc/Handbooks>. The
    package also offers the mixed_model_analysis() and cross_lagged() functions
    which implement mixed effects models and cross lagged analyses as described
    in Maric & van der Werff (2020) <doi:10.4324/9780429273872-9>. The
    randomization_test() function implements randomization tests based on methods
    presented in Onghena (2020) <doi:10.4324/9780429273872-8>. The scdtb() 'shiny'
    application can be used to upload single case design data and access various
    'scdtb' tools for plotting and analysis.

Implementation of Stepwise Clustered Ensemble (SCE) and Stepwise Cluster Analysis (SCA) for multivariate data analysis. The package provides comprehensive tools for feature selection, model training, prediction, and evaluation in hydrological and environmental modeling applications. Key functionalities include recursive feature elimination (RFE), Wilks feature importance analysis, model validation through out-of-bag (OOB) validation, and ensemble prediction capabilities. The package supports both single and multivariate response variables, making it suitable for complex environmental modeling scenarios. For more details see Li et al. (2021) <doi:10.5194/hess-25-4947-2021>.