Package index • JointAI

All functions

GR_crit(): Gelman-Rubin criterion for convergence
JointAI-package 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
auto_corr() auto_corr_plot(): Autocorrelation of MCMC samples
clean_survname(): Convert a survival outcome to a model name
cross_corr() 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
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
internal_clean_survname(): Convert a survival outcome to a model name
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
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