Function reference • JointAI

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`GR_crit()`	Gelman-Rubin criterion for convergence
`JointAI`	JointAI: Joint Analysis and Imputation of Incomplete Data
`JointAIObject`	Fitted object of class 'JointAI'
`MC_error()` `plot(<MCElist>)`	Calculate and plot the Monte Carlo error
`NHANES`	National Health and Nutrition Examination Survey (NHANES) Data
`PBC`	PBC data
`add_samples()`	Continue sampling from an object of class JointAI
`clean_survname()`	Convert a survival outcome to a model name
`default_hyperpars()`	Get the default values for hyper-parameters
`densplot()`	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
`list_models()`	List model details
`longDF`	Longitudinal example dataset
`md_pattern()`	Missing data pattern
`lm_imp()` `glm_imp()` `clm_imp()` `lognorm_imp()` `betareg_imp()` `mlogit_imp()` `lme_imp()` `lmer_imp()` `glme_imp()` `glmer_imp()` `betamm_imp()` `lognormmm_imp()` `clmm_imp()` `mlogitmm_imp()` `survreg_imp()` `coxph_imp()` `JM_imp()`	Joint Analysis and Imputation of incomplete 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
`predict(<JointAI>)`	Predict values from an object of class JointAI
`rd_vcov()`	Extract the random effects variance covariance matrix Returns the posterior mean of the variance-covariance matrix/matrices of the random effects in a fitted JointAI object.
`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
`sum_duration()`	Calculate the sum of the computational duration of a JointAI object
`print(<Dmat>)` `summary(<JointAI>)` `print(<summary.JointAI>)` `coef(<JointAI>)` `confint(<JointAI>)` `print(<JointAI>)`	Summarize the results from an object of class JointAI
`traceplot()`	Create traceplots for a MCMC sample
`wideDF`	Cross-sectional example dataset

Reference

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