Package: psc 2.0.1

psc: Personalised Synthetic Controls

Allows the comparison of data cohorts (DC) against a Counter Factual Model (CFM) and measures the difference in terms of an efficacy parameter. Allows the application of Personalised Synthetic Controls.

Authors:Richard Jackson [cre, aut, cph]

psc_2.0.1.tar.gz
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psc_2.0.1.tgz(r-4.6-any)psc_2.0.1.tgz(r-4.5-any)
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psc_2.0.1.tgz(r-4.5-emscripten)
psc.pdf |psc.html✨
psc/json (API)
NEWS

# Install 'psc' in R:
install.packages('psc', repos = c('https://richjjackson.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/richjjackson/psc/issues

Pkgdown/docs site:https://richjjackson.github.io

Datasets:
  • e4_data - Example Dataset of patients treated with GemCap in the ESPAC-4 trial
  • gemCFM - Model for a survival outcome based on Gemcitbine patients from ESPAC-3

On CRAN:

Conda:

5.41 score 2 stars 1 packages 17 scripts 580 downloads 10 exports 141 dependencies

Last updated from:015e2c0e77. Checks:4 ERROR, 5 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR234
source / vignettesOK256
linux-release-x86_64ERROR229
macos-release-arm64ERROR144
macos-oldrel-arm64ERROR161
windows-develOK155
windows-releaseOK158
windows-oldrelOK186
wasm-releaseOK173

Exports:initplotCFMpostSummarypscCFMpscDatapscEstpscEst_runpscEst_startpscEst_updatepscfit

Dependencies:abindassertthatbackportsbase64encbbmlebdsmatrixbigDbitopsbootbroombslibcachemcarcarDatacardscardxcheckmateclicolorspacecommonmarkcorrplotcowplotcpp11curldata.tableDerivdeSolvedigestdistributionaldoBydplyrenrichwithevaluateexactRankTestsfarverfastGHQuadfastmapflexsurvfontawesomeforecastFormulafracdifffsgenericsggplot2ggpubrggrepelggsciggsignifggtextgluegridExtragridtextgtgtablegtsummaryhighrhtmltoolshtmlwidgetsisobandjpegjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclelitedownlme4lmtestlsodamagrittrmarkdownMASSMatrixMatrixModelsmatrixStatsmaxstatmemoisemgcvmicrobenchmarkmimeminqamodelrmstatemuhazmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpngpolynomposteriorpurrrquadprogquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreactablereactRreformulasrlangrmarkdownrstatixrstpm2S7sassscalesSparseMstatmodstringistringrsurvivalsurvminertensorAtibbletidyrtidyselecttimeDatetinytexurcautf8V8vctrsviridisLitewithrxfunxml2yamlzoo

psc-vignette

Richard Jackson

Rendered frompsc.Rmdusingknitr::rmarkdownon Apr 12 2026.

Last update: 2026-01-12
Started: 2025-07-07

Readme and manuals

Help Manual

Help pageTopics
accacc
Example model for a survival outcomebin.mod
Counter Factual Model - summaryboot_lp
Counter Factual Model - summaryboot_sest
Summarising data within a Counter Factual Model (CFM)cfmDataSumm
Visualising data within a CFMcfmDataVis
Visualising Categorical DatacfmDataVis_fac
Visualising Numerical DatacfmDataVis_num
Counter Factual Model - summarycfmSumm.flexsurvreg
Counter Factual Model - summarycfmSumm.glm
Returns the coefficient estimate of a psc object.coef.psc
Example model for a survival outcomecont.mod
Example model for a survival outcomecount.mod
Example Dataset of patients with aHCC receiving Lenvetanibdata
Example Dataset of patients treated with GemCap in the ESPAC-4 triale4_data
Visualising Categorical DatafacVisComp
Model for a survival outcome based on Gemcitbine patients from ESPAC-3gemCFM
Function for estimating initial parameter valuesinit
Likelihood function for a psc model of class 'flexsurvreg'lik.flexsurvreg
Likelihood function for a psc model of class 'glm'lik.glm
A generic function for extracting model informationmodelExtract
A generic function for extracting model informationmodelExtract.flexsurvreg
A generic function for extracting model informationmodelExtract.glm
A generic function for extracting model informationmodelExtract.lmerMod
modpmodp
Visualising Numerical DatanumVisComp
Function for Plotting PSC objectsplot.psc
Function for Plotting PSC objectsplot.psc.binary
Function for Plotting PSC objectsplot.psc.cont
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.count
Function for Plotting PSC objectsplot.psc.flexsurvreg
Function for Plotting PSC objectsplotCFM
Posterior SummarypostSummary
Personalised Synthetic Controls - printprint.psc
quiet_gglistprint.quiet_gglist
quiet_gtsummprint.quiet_gtsumm
quiet_gtsummprint.quiet_list
Fitted 'psc' objectpsc.object
Creating a CFM model which can be sharedpscCFM
A function which structures the Data Cohort in a format for model estimationpscData
A function that add a likelihood for estimation to the pscObjectpscData_addLik
A function that includes a treatment indicator when multiple treatment comparisons are requiredpscData_addtrt
A function which performs error checks between the DC and CFMpscData_error
A function to ensure that data from the cfm and data cohort are compatiblepscData_match
A function which removes missing data from the DCpscData_miss
A function which structures the Data Cohort in a format for model estimationpscData_structure
Function for performing Bayesian MCMC estimation procedures in 'pscfit'pscEst
Running the Bayesian MCMC routine A procedure which runs the MCMC estimation routinepscEst_run
Starting conditions for Bayesian MCMC estimation procedures in 'pscfit' A procedure which runs the sampling process for MCMC estimationpscEst_samp
Starting conditions for Bayesian MCMC estimation procedures in 'pscfit' A procedure which sets the starting conditions for MCMC estimationpscEst_start
Updating the posterior distribution as part of the MCMC estimation process A procedure which performs a single update of the posterior distributionpscEst_update
Personalised Synthetic Controls model fitpscfit
Counter Factual Model - summaryspline_surv_est
Personalised Synthetic Controls - summarysummary.psc
Example model for a survival outcomesurv.mod
Visualising Comparisons between a CFM and a DCvisComp