Joint Analysis and Imputation of Incomplete Data

Documentation for package ‘JointAI’ version 0.1.0

JointAI-package	JointAI: Joint Analysis and Imputation of Missing Values
add_samples	Add samples to an object of class JointAI
default_hyperpars	Get default values for hyperparameters Prints the list of default values for the hyperparameters
densplot	Plot posterior density from JointAI model
densplot.JointAI	Plot posterior density from JointAI model
get_imp_meth	Find default imputation methods and order
get_MIdat	Extract multiple imputed datasets (and export to SPSS)
glm_imp	Joint analysis and imputation of incomplete data
GR_crit	Gelman-Rubin criterion for convergence
JointAI	JointAI: Joint Analysis and Imputation of Missing Values
JointAIObject	Fitted object of class JointAI
lme_imp	Joint analysis and imputation of incomplete data
lm_imp	Joint analysis and imputation of incomplete data
longDF	Longitudinal example dataset
MC_error	Monte Carlo error
md_pattern	Missing data pattern
model_imp	Joint analysis and imputation of incomplete data
plot.MCElist	Monte Carlo error
predDF	Create a new dataframe for prediction
predDF.formula	Create a new dataframe for prediction
predDF.JointAI	Create a new dataframe for prediction
predict.JointAI	Predict values from an object of class JointAI
print.summary.JointAI	Summary of an object of class JointAI
summary.JointAI	Summary of an object of class JointAI
traceplot	Traceplot of a JointAI model
traceplot.JointAI	Traceplot of a JointAI model
wideDF	Cross-sectional example dataset