simulab: Simulates a Wide Variety of Data Shapes, Sizes and Distributions

Generates a wide variety of data, in different shapes, sample sizes, distributions and parameters. The parameters are either drawn at random or set in advance, and in both cases they are stored with the data, so they are known and their recovery can be tested. Generators cover declared variables with treatment assignment and missing values, correlated and clustered data, latent profile, latent class, factor and item response models, longitudinal and multilevel processes, survival times with competing risks, sequences of states, and static, bipartite, multiplex, temporal and transition networks. Every generator returns batches of reproducible data sets for the evaluation of statistical methods, the testing of models and software, and teaching; simulated transition networks are native 'tna' models.

install.packages("simulab")

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