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jomo (version 2.2-0)

Multilevel Joint Modelling Multiple Imputation

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.

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Version

Install

install.packages('jomo')

Monthly Downloads

61,493

Version

2.2-0

License

GPL-2

Maintainer

Matteo Quartagno

Last Published

July 25th, 2016

Functions in jomo (2.2-0)

jomo1con.MCMCchain

JM Imputation of single level data with continuous variables only - A tool to check convergence of the MCMC

Joint Modelling Imputation

A simulated clustered dataset

jomo1.MCMCchain

JM Imputation of single level data - A tool to check convergence of the MCMC

A package for Multilevel Joint Modelling Multiple Imputation

JM Imputation of single level data

JM Imputation of single level data with categorical variables

jomo1cat.MCMCchain

JM Imputation of single level data with categorical variables - A tool to check convergence of the MCMC

JM Imputation of single level data with continuous variables only

JM Imputation - A tool to check convergence of the MCMC

JM Imputation of clustered data with categorical variables

jomo1ran.MCMCchain

JM Imputation of clustered data - A tool to check convergence of the MCMC

jomo1rancon.MCMCchain

JM Imputation of clustered data with continuous variables only - A tool to check convergence of the MCMC

jomo1rancathr.MCMCchain

JM Imputation of clustered data with categorical variables with cluster-specific covariance matrices - A tool to check convergence of the MCMC

JM Imputation of single level data with mixed variable types

JM Imputation of clustered data

jomo1rancat.MCMCchain

JM Imputation of clustered data with categorical variables - A tool to check convergence of the MCMC

jomo1mix.MCMCchain

JM Imputation of single level data with mixed variable types

JM Imputation of clustered data with categorical variables with cluster-specific covariance matrices

JM Imputation of clustered data with continuous variables only

JM Imputation of 2-level data assuming a common level-1 covariance matrix across level-2 units.

JM Imputation of clustered data with mixed variable types

JM Imputation of 2-level data

jomo2.MCMCchain

JM Imputation of 2-level data - A tool to check convergence of the MCMC

jomo1ranconhr.MCMCchain

JM Imputation of clustered data with continuous variables only with cluster-specific covariance matrices - A tool to check convergence of the MCMC

JM Imputation of clustered data with continuous variables only with cluster-specific covariance matrices

jomo1ranmix.MCMCchain

JM Imputation of clustered data with mixed variable types - A tool to check convergence of the MCMC

JM Imputation of clustered data with mixed variable types with cluster-specific covariance matrices

jomo1ranmixhr.MCMCchain

JM Imputation of clustered data with mixed variable types with cluster-specific covariance matrices - A tool to check convergence of the MCMC

jomo2com.MCMCchain

JM Imputation of 2-level data assuming a common level-1 covariance matrix across level-2 units - A tool to check convergence of the MCMC

A simulated 2-level dataset

A simulated single level dataset

JM Imputation of 2-level data assuming cluster-specific level-1 covariance matrices across level-2 unit

jomo2hr.MCMCchain

JM Imputation of 2-level data assuming cluster-specific level-1 covariance matrices across level-2 units- A tool to check convergence of the MCMC