Original 'ctsem' (continuous time structural equation modelling)
    functionality, based on the 'OpenMx' software, as described in 
    Driver, Oud, Voelkle (2017) <doi:10.18637/jss.v077.i05>, with updated details in vignette. 
    Combines stochastic differential equations representing latent processes with 
    structural equation measurement models. These functions were split off from
    the main package of 'ctsem', as the main package uses the 'rstan' package as a backend now --
    offering estimation options from max likelihood to Bayesian.
    There are nevertheless use cases for the wide format SEM style approach as offered here, 
    particularly when there are no individual differences in observation timing and the
    number of individuals is large. For the main 'ctsem' package, see <https://cran.r-project.org/package=ctsem>.

An implementation of several functions for feature extraction in 
    categorical time series datasets. Specifically, some features related to 
    marginal distributions and serial dependence patterns can be computed. These 
    features can be used to feed clustering and classification algorithms for
    categorical time series, among others. The package also includes some
    interesting datasets containing biological sequences. Practitioners from a 
    broad variety of fields could benefit from the general framework provided 
    by 'ctsfeatures'.

An interactive document on  the topic of classification tree analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at  <https://kartikeyab.shinyapps.io/CTShiny/>.

A collection of common test and item analyses from a classical test theory (CTT) framework. Analyses can be applied to both dichotomous and polytomous data. Functions provide reliability analyses (alpha), item statistics, disctractor analyses, disattenuated correlations, scoring routines, and empirical ICCs.

A Shiny interface developed in close coordination with the CTT package, providing a GUI that guides the user through CTT analyses.