iccREunder the Poisson distribution. The current approach is based on the 2013 paper by Nakagawa & Schielzeth titled “A general and simple method for obtaining R2 from generalized linear mixed-effects models”
blockDecayMat. Users can now generate correlation matrices that can accommodate clustered observations over time where the within-cluster correlation in the same time period can be different from the within-cluster correlation across time periods.
genCorMatto allow generation of cluster-specific correlation matrices in case one wants to induce variability in correlation across clusters.
addCorGento make it more flexible. It can now handle cluster-dependent data, and not just time-dependent data. In addition, performance has been dramatically improved.
genFormulato allow for ‘double dot’ functionality.
addSynthetic. Allows users to sample records with replacement from an existing data table.
genMarkov. Allows user to set probability distribution of start state.
survParamPlotto aid users in identifying parameters that can be used to generate desired distributions of time to event data.
genSurv. It is now possible to generate survival outcomes with hazard functions that change over time. In addition, competing risk outcomes can be explicitly generated.