Summarize model output using a robust effect size index. The index is introduced in Vandekar, Tao, & Blume (2020) <doi:10.1007/s11336-020-09698-2>.

Developed to assist researchers with planning analysis,
    prior to obtaining data from Trusted Research Environments (TREs) also known as safe havens.
    With functionality to export and import marginal distributions as well as synthesise data, both with
    and without correlations from these marginal distributions. Using a multivariate cumulative distribution (COPULA).
    Additionally the International Stroke Trial (IST) is included as an example dataset under ODC-By licence
    Sandercock et al. (2011) <doi:10.7488/ds/104>,
    Sandercock et al. (2011) <doi:10.1186/1745-6215-12-101>.

Datasets with energy consumption data of different data measurement frequencies. 
    The data stems from several publicly funded research projects of the Chair of Information  
    Systems and Energy Efficient Systems at the University of Bamberg.

Studies of resilience in older adults employ a single-arm design where everyone experiences the stressor. The simplistic approach of regressing change versus baseline yields biased estimates due to regression-to-the-mean. This package provides a method to correct the bias. It also allows covariates to be included. The method implemented in the package is described in Varadhan, R., Zhu, J., and Bandeen-Roche, K (2023), Biostatistics (To appear).

Contains various tools to perform and visualize Response Item Networks ('ResIN's'). 'ResIN' binarizes ordered-categorical and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.

Electrical properties of resistor networks using matrix methods.

A pair of functions for calculating mean residual life (MRL)
    , median residual life, and percentile residual life using the outputs of 
    either the 'flexsurv' package or parameters
    provided by the user. Input information about the distribution, the given
    'life' value, the percentile, and the type of residual life, 
    and the function will return your desired values. For the 'flexsurv' option,
    the function allows the user to input their own data for making predictions. 
    This function is based on Jackson (2016) <doi:10.18637/jss.v070.i08>.