Package index • psc

All functions

acc(): acc
bin.mod: Example model for a survival outcome
boot_lp(): Counter Factual Model - summary
boot_sest(): Counter Factual Model - summary
cfmDataSumm(): Summarising data within a Counter Factual Model (CFM)
cfmDataVis(): Visualising data within a CFM
cfmDataVis_fac(): Visualising Categorical Data
cfmDataVis_num(): Visualising Numerical Data
cfmSumm.flexsurvreg(): Counter Factual Model - summary
cfmSumm.glm(): Counter Factual Model - summary
coef(<psc>): Returns the coefficient estimate of a psc object.
cont.mod: Example model for a survival outcome
count.mod: Example model for a survival outcome
data: Example Dataset of patients with aHCC receiving Lenvetanib
e4_data: Example Dataset of patients treated with GemCap in the ESPAC-4 trial
facVisComp(): Visualising Categorical Data
gemCFM: Model for a survival outcome based on Gemcitbine patients from ESPAC-3
init(): Function for estimating initial parameter values
lik.flexsurvreg(): Likelihood function for a psc model of class 'flexsurvreg'
lik.glm(): Likelihood function for a psc model of class 'glm'
modelExtract(): A generic function for extracting model information
modelExtract(<flexsurvreg>): A generic function for extracting model information
modelExtract(<glm>): A generic function for extracting model information
modelExtract(<lmerMod>): A generic function for extracting model information
modp(): modp
numVisComp(): Visualising Numerical Data
plot(<psc>): Function for Plotting PSC objects
plot(<psc.binary>): Function for Plotting PSC objects
plot(<psc.cont>): Function for Plotting PSC objects
plot(<psc.count>): Function for Plotting PSC objects #' A function which illsutrates the predicted response under the counter factual model and the observed response under the experimental treatment(s).
plot(<psc.flexsurvreg>): Function for Plotting PSC objects
plotCFM(): Function for Plotting PSC objects
postSummary(): Posterior Summary
print(<psc>): Personalised Synthetic Controls - print
print(<quiet_gglist>): quiet_gglist
print(<quiet_gtsumm>): quiet_gtsumm
print(<quiet_list>): quiet_gtsumm
psc.object: Fitted psc object
pscCFM(): Creating a CFM model which can be shared
pscData(): A function which structures the Data Cohort in a format for model estimation
pscData_addLik(): A function that add a likelihood for estimation to the pscObject
pscData_addtrt(): A function that includes a treatment indicator when multiple treatment comparisons are required
pscData_error(): A function which performs error checks between the DC and CFM
pscData_match(): A function to ensure that data from the cfm and data cohort are compatible
pscData_miss(): A function which removes missing data from the DC
pscData_structure(): A function which structures the Data Cohort in a format for model estimation
pscEst(): Function for performing Bayesian MCMC estimation procedures in 'pscfit'
pscEst_run(): Running the Bayesian MCMC routine A procedure which runs the MCMC estimation routine
pscEst_samp(): Starting conditions for Bayesian MCMC estimation procedures in 'pscfit' A procedure which runs the sampling process for MCMC estimation
pscEst_start(): Starting conditions for Bayesian MCMC estimation procedures in 'pscfit' A procedure which sets the starting conditions for MCMC estimation
pscEst_update(): Updating the posterior distribution as part of the MCMC estimation process A procedure which performs a single update of the posterior distribution
pscfit(): Personalised Synthetic Controls model fit
spline_surv_est(): Counter Factual Model - summary
summary(<psc>): Personalised Synthetic Controls - summary
surv.mod: Example model for a survival outcome
visComp(): Visualising Comparisons between a CFM and a DC