Packaged: 2017-11-28 08:27:41 UTC; mpierre-jean

Packaged: 2019-01-11 10:58:39 UTC; mpierre-jean

Title: A package for Multilevel Joint Modelling Multiple Imputation
Author: Matteo Quartagno, James Carpenter
Description: Building on Schafer's pan and on standalone program REALCOM, jomo is a package for multilevel joint modelling multiple imputation.
Binary and categorical variables are handled through latent normal variables and algorithms for cluster specific covariance matrices are introduced.

Title: Multilevel Joint Modelling Multiple Imputation
Description: Building on Schafer's package pan and on the standalone program REALCOM, jomo is a package for multilevel joint modelling multiple imputation.
Binary and categorical variables are handled through latent normal variables and algorithms for cluster-specific covariance matrices are introduced.

Description: Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation.
Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables and the option to use cluster-specific covariance matrices.

Description: Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation.
Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables and the option to use cluster-specific covariance matrices.

Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.

Description: Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi: 10.1002/9781119942283>.

Imports: stats, lme4, survival, MASS, ordinal

Description: Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi:10.1002/9781119942283>.
Imports: stats, lme4, survival, MASS, ordinal, tibble