R: Joint Analysis and Imputation of Incomplete Data

# Joint Analysis and Imputation of Incomplete Data

## Documentation for package ‘JointAI’ version 1.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

JointAI-package | JointAI: Joint Analysis and Imputation of Incomplete Data
add_samples | Continue sampling from an object of class JointAI
auto_corr | Autocorrelation of MCMC samples
auto_corr_plot | Autocorrelation of MCMC samples
betamm_imp | Joint Analysis and Imputation of incomplete data
betareg_imp | Joint Analysis and Imputation of incomplete data
clean_survname | Convert a survival outcome to a model name
clmm_imp | Joint Analysis and Imputation of incomplete data
clm_imp | Joint Analysis and Imputation of incomplete data
coef.JointAI | Summarize the results from an object of class JointAI
confint.JointAI | Summarize the results from an object of class JointAI
coxph_imp | Joint Analysis and Imputation of incomplete data
cross_corr | Cross-correlation of MCMC samples
cross_corr_plot | Cross-correlation of MCMC samples
default_hyperpars | Get the default values for hyper-parameters
densplot | Plot the posterior density from object of class JointAI
densplot.JointAI | Plot the posterior density from object of class JointAI
extract_state | Return the current state of a 'JointAI' model
get_MIdat | Extract multiple imputed datasets from an object of class JointAI
get_missinfo | Obtain a summary of the missing values involved in an object of class JointAI
glmer_imp | Joint Analysis and Imputation of incomplete data
glme_imp | Joint Analysis and Imputation of incomplete data
glm_imp | Joint Analysis and Imputation of incomplete data
GR_crit | Gelman-Rubin criterion for convergence
internal_clean_survname | Convert a survival outcome to a model name
JM_imp | Joint Analysis and Imputation of incomplete data
JointAI | JointAI: Joint Analysis and Imputation of Incomplete Data
JointAIObject | Fitted object of class 'JointAI'
list_models | List model details
lmer_imp | Joint Analysis and Imputation of incomplete data
lme_imp | Joint Analysis and Imputation of incomplete data
lm_imp | Joint Analysis and Imputation of incomplete data
lognormmm_imp | Joint Analysis and Imputation of incomplete data
lognorm_imp | Joint Analysis and Imputation of incomplete data
longDF | Longitudinal example dataset
MC_error | Calculate and plot the Monte Carlo error
md_pattern | Missing data pattern
mlogitmm_imp | Joint Analysis and Imputation of incomplete data
mlogit_imp | Joint Analysis and Imputation of incomplete data
model_imp | Joint Analysis and Imputation of incomplete data
NHANES | National Health and Nutrition Examination Survey (NHANES) Data
parameters | Parameter names of an JointAI object
PBC | PBC data
plot.JointAI | Plot an object object inheriting from class 'JointAI'
plot.MCElist | Calculate and plot the Monte Carlo error
plot_all | Visualize the distribution of all variables in the dataset
plot_imp_distr | Plot the distribution of observed and imputed values
predict.JointAI | Predict values from an object of class JointAI
print.Dmat | Summarize the results from an object of class JointAI
print.JointAI | Summarize the results from an object of class JointAI
print.summary.JointAI | Summarize the results from an object of class JointAI
rd_vcov | Extract the random effects variance covariance matrix
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 | Simulated Longitudinal Data in Long and Wide Format
simWide | Simulated Longitudinal Data in Long and Wide Format
summary.JointAI | Summarize the results from an object of class JointAI
sum_duration | Calculate the sum of the computational duration of a JointAI object
survreg_imp | Joint Analysis and Imputation of incomplete data
traceplot | Create traceplots for a MCMC sample
traceplot.JointAI | Create traceplots for a MCMC sample
wideDF | Cross-sectional example dataset