Rcpp (>= 0.11.5), methods, editrules, graphics, utils, igraph

An integrated editing and imputation method for continuous microdata under linear constraints is implemented. It relies on a Bayesian nonparametric hierarchical modeling approach as described in Kim et al. (2015) <doi:10.1080/01621459.2015.1040881>. In this approach, the joint distribution of the data is estimated by a flexible joint probability model. The generated edit-imputed data are guaranteed to satisfy all imposed edit rules, whose types include ratio edits, balance edits and range restrictions.
Rcpp, methods, editrules, graphics, utils, igraph

c(person("Axel", "Mayer", role=c("aut","cre"),
email="amayer2010@gmail.com"),
person("Lisa", "Dietzfelbinger", role=c("ctb"),
email="lisa.dietzfelbinger@uni-jena.de"))
Axel Mayer [aut, cre],
Lisa Dietzfelbinger [ctb]
Use structural equation modeling to estimate average and conditional effects of a treatment variable
on an outcome variable, taking into account multiple continuous and categorical covariates.
shiny (>= 0.11), foreign, ggplot2, nnet, survey,
lavaan.survey, car

methods, shiny (>= 0.11), foreign, ggplot2, nnet, survey,
lavaan.survey, car

Use structural equation modeling to estimate average and
conditional effects of a treatment variable on an outcome variable, taking into
account multiple continuous and categorical covariates.

methods, shiny (>= 1.5.0), foreign, ggplot2, nnet, survey,
lavaan.survey, car

Visualization of Categorical Response Models
The package provides functions to visualize regression
models with categorical response. The effects of the covariates
are plotted with star plots in order to allow for an optical
impression of the fitted model.

The package provides functions to visualize regression models with categorical response. The effects of the covariates are plotted with star plots in order to allow for an optical impression of the fitted model.

Provides functions to visualize regression models with categorical response. The effects of the variables are plotted with star plots in order to allow for an optical impression of the fitted model.