Missing Outcome Data in Health Economic Evaluation

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Documentation for package ‘missingHE’ version 1.5.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

anyBars	An internal function to detect the random effects component from an object of class formula
coef.missingHE	Extract regression coefficient estimates from objects in the class 'missingHE'
data_read_hurdle	A function to read and re-arrange the data in different ways for the hurdle model
data_read_pattern	A function to read and re-arrange the data in different ways
data_read_selection	A function to read and re-arrange the data in different ways
data_read_selection_long	A function to read and re-arrange the data in different ways
diagnostic	Diagnostic checks for assessing MCMC convergence of Bayesian models fitted in 'JAGS' using the function 'selection', 'selection_long', 'pattern' or 'hurdle'
fb	An internal function to extract the random effects component from an object of class formula
hurdle	Full Bayesian Models to handle missingness in Economic Evaluations (Hurdle Models)
isAnyArgBar	An internal function to detect the random effects component from an object of class formula
isBar	An internal function to detect the random effects component from an object of class formula
jagsresults	An internal function to summarise results from BUGS model
MenSS	MenSS economic data on STIs
nobars_	An internal function to separate the fixed and random effects components from an object of class formula
pattern	Full Bayesian Models to handle missingness in Economic Evaluations (Pattern Mixture Models)
PBS	PBS economic data on intellectual disability and challenging behaviour
pic	Predictive information criteria for Bayesian models fitted in 'JAGS' using the funciton 'selection', 'selection_long', 'pattern' or 'hurdle'
plot.missingHE	Plot method for the imputed data contained in the objects of class 'missingHE'
ppc	Posterior predictive checks for assessing the fit to the observed data of Bayesian models implemented in 'JAGS' using the function 'selection', 'selection_long', 'pattern' or 'hurdle'
print.missingHE	Print method for the posterior results contained in the objects of class 'missingHE'
prior_hurdle	An internal function to change the hyperprior parameters in the hurdle model provided by the user depending on the type of structural value mechanism and outcome distributions assumed
prior_pattern	An internal function to change the hyperprior parameters in the selection model provided by the user depending on the type of missingness mechanism and outcome distributions assumed
prior_selection	An internal function to change the hyperprior parameters in the selection model provided by the user depending on the type of missingness mechanism and outcome distributions assumed
prior_selection_long	An internal function to change the hyperprior parameters in the selection model provided by the user depending on the type of missingness mechanism and outcome distributions assumed
run_hurdle	An internal function to execute a JAGS hurdle model and get posterior results
run_pattern	An internal function to execute a JAGS pattern mixture model and get posterior results
run_selection	An internal function to execute a JAGS selection model and get posterior results
run_selection_long	An internal function to execute a JAGS selection model and get posterior results
selection	Full Bayesian Models to handle missingness in Economic Evaluations (Selection Models)
selection_long	Full Bayesian Models to handle missingness in Economic Evaluations (Selection Models)
summary.missingHE	Summary method for objects in the class 'missingHE'
write_hurdle	An internal function to select which type of hurdle model to execute for both effectiveness and costs. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of structural value mechanism assumed and independence or joint modelling This function selects which type of model to execute.
write_pattern	An internal function to select which type of pattern mixture model to execute. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of missingness mechanism assumed and independence or joint modelling This function selects which type of model to execute.
write_selection	An internal function to select which type of selection model to execute. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of missingness mechanism assumed and independence or joint modelling This function selects which type of model to execute.
write_selection_long	An internal function to select which type of selection model to execute. Alternatives vary depending on the type of distribution assumed for the effect and cost variables, type of missingness mechanism assumed and independence or joint modelling This function selects which type of model to execute.