All functions

add_samples()

Continue sampling from an object of class JointAI

default_hyperpars()

Get the default values for hyperparameters

densplot()

Plot the posterior density from object of class JointAI

get_MIdat()

Extract multiple imputed datasets from an object of class JointAI

get_models()

Specify the default (imputation) model types

GR_crit()

Gelman-Rubin criterion for convergence

JointAI

JointAI: Joint Analysis and Imputation of Incomplete Data

JointAIObject

Fitted object of class 'JointAI'

list_models()

List covariate models

longDF

Longitudinal example dataset

MC_error() plot(<MCElist>)

Monte Carlo error

md_pattern()

Missing data pattern

lm_imp() glm_imp() clm_imp() lme_imp() glme_imp() clmm_imp() survreg_imp() coxph_imp()

Joint analysis and imputation of incomplete data

NHANES

National Health and Nutrition Examination Survey (NHANES) Data

parameters()

Parameter names of an JointAI object

plot(<JointAI>)

Plot an object object inheriting from class 'JointAI'

plot_all()

Visualize the distribution of all variables in the dataset

plot_imp_distr()

Plot the distribution of observed and imputed values

predDF()

Create a new dataframe for prediction

predict(<JointAI>)

Predict values from an object of class JointAI

residuals(<JointAI>)

Extract residuals from an object of class JointAI

set_refcat()

Specify reference categories for all categorical covariates in the model

sharedParams

Parameters used by several functions in JointAI.

simLong simWide

Simulated Longitudinal Data in Long and Wide Format

summary(<JointAI>) print(<summary.JointAI>) coef(<JointAI>) confint(<JointAI>) print(<JointAI>)

Summary of an object of class JointAI

traceplot()

Traceplot of a JointAI model

wideDF

Cross-sectional example dataset