Package: maicplus 0.1.2.9000

Isaac Gravestock

maicplus: Matching Adjusted Indirect Comparison

Facilitates performing matching adjusted indirect comparison (MAIC) analysis where the endpoint of interest is either time-to-event (e.g. overall survival) or binary (e.g. objective tumor response). The method is described by Signorovitch et al (2012) <doi:10.1016/j.jval.2012.05.004>.

Authors:Gregory Chen [aut], Michael Seo [aut], Isaac Gravestock [aut, cre], Miranta Antoniou [ctb], Chrysostomos Kalyvas [ctb], MSD, Inc. [cph, fnd], F. Hoffmann-La Roche AG [cph, fnd]

maicplus_0.1.2.9000.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
maicplus/json (API)

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

Bug tracker:https://github.com/hta-pharma/maicplus/issues

Pkgdown/docs site:https://hta-pharma.github.io

Datasets:
  • adrs_sat - Binary outcome data from single arm trial
  • adrs_twt - Binary outcome data from two arm trial
  • adsl_sat - Patient data from single arm study
  • adsl_twt - Patient data from two arm trial
  • adtte_sat - Survival data from single arm trial
  • adtte_twt - Survival data from two arm trial
  • agd - Aggregate effect modifier data from published study
  • centered_ipd_sat - Centered patient data from single arm trial
  • centered_ipd_twt - Centered patient data from two arm trial
  • pseudo_ipd_sat - Pseudo individual patient survival data from published study
  • pseudo_ipd_twt - Pseudo individual patient survival data from published two arm study
  • weighted_sat - Weighted object for single arm trial data
  • weighted_twt - Weighted object for two arm trial data

On CRAN:

Conda:

6.99 score 9 stars 54 scripts 458 downloads 27 exports 21 dependencies

Last updated from:e09b702ccf. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK269
source / vignettesOK244
linux-release-x86_64OK213
macos-release-arm64OK152
macos-oldrel-arm64OK199
windows-develOK142
windows-releaseOK139
windows-oldrelOK131
wasm-releaseOK173

Exports:basic_kmplotbasic_kmplot2buchercalculate_weights_legendcenter_ipdcheck_weightsdummize_ipdestimate_weightsfind_SE_from_CIget_pseudo_ipd_binaryget_time_asget_time_conversionglm_makeupkmplotkmplot2maic_anchoredmaic_forest_plotmaic_unanchoredmedSurv_makeupph_diagplotph_diagplot_lchph_diagplot_schoenfeldplot_weights_baseplot_weights_ggplotprocess_agdset_time_conversionsurvfit_makeup

Dependencies:bootclicpp11genericsgluelatticelifecyclelmtestlubridatemagrittrMASSMatrixmatrixStatsrlangsandwichstringistringrsurvivaltimechangevctrszoo

Anchored Survival Analysis
Loading R packages | Illustration using example data | Using bootstrap to calculate standard errors | Visualizing effect estimates with forest plot
Rendered fromanchored_survival.Rmdusingknitr::rmarkdown

Last update: 2025-09-01
Started: 2024-10-03

Testing PH assumptions
Loading R packages | Introduction | Unanchored case | Anchored case
Rendered fromtesting_ph_assumptions.Rmdusingknitr::rmarkdown

Last update: 2025-09-01
Started: 2025-05-23

Unanchored Survival Analysis
Loading R packages | Illustration using example data | Using bootstrap to calculate standard errors | Visualizing effect estimates with forest plot | References
Rendered fromunanchored_survival.Rmdusingknitr::rmarkdown

Last update: 2025-09-01
Started: 2024-10-03

Anchored Binary Analysis
Loading R packages | Illustration using example data | Using bootstrap to calculate standard errors
Rendered fromanchored_binary.Rmdusingknitr::rmarkdown

Last update: 2025-02-13
Started: 2024-10-03

Unanchored Binary Analysis
Loading R packages | Illustration using example data | Using bootstrap to calculate standard errors | References
Rendered fromunanchored_binary.Rmdusingknitr::rmarkdown

Last update: 2024-12-18
Started: 2024-10-03

Kaplan-Meier Plots
Loading R packages | Introduction | Unanchored case | Anchored case | References
Rendered fromkaplan_meier_plots.Rmdusingknitr::rmarkdown

Last update: 2024-10-11
Started: 2024-10-03

Preprocessing and Calculating Weights
Loading R packages | Preprocessing | Preprocessing IPD | Preprocessing aggregate data | How _SD prefix is handled | How _MEDIAN prefix is handled | Centering IPD | Calculating weights | References
Rendered fromcalculating_weights.Rmdusingknitr::rmarkdown

Last update: 2024-10-08
Started: 2024-10-03

Introduction
Statistical theory behind MAIC | References
Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2024-10-03
Started: 2024-10-03

Readme and manuals

Help Manual

Help pageTopics
Binary outcome data from single arm trialadrs_sat
Binary outcome data from two arm trialadrs_twt
Patient data from single arm studyadsl_sat
Patient data from two arm trialadsl_twt
Survival data from single arm trialadtte_sat
Survival data from two arm trialadtte_twt
Aggregate effect modifier data from published studyagd
Basic Kaplan Meier (KM) plot functionbasic_kmplot
Basic Kaplan Meier (KM) plot function using ggplotbasic_kmplot2
Bucher method for combining treatment effectsbucher print.maicplus_bucher
Center individual patient data (IPD) variables using aggregate data averagescenter_ipd
Centered patient data from single arm trialcentered_ipd_sat
Centered patient data from two arm trialcentered_ipd_twt
Check to see if weights are optimized correctlycheck_weights print.maicplus_check_weights
Create dummy variables from categorical variables in an individual patient data (ipd)dummize_ipd
Derive individual weights in the matching step of MAICestimate_weights plot.maicplus_estimate_weights
Calculate standard error from the reported confidence interval.find_SE_from_CI
Create pseudo IPD given aggregated binary dataget_pseudo_ipd_binary
Convert Time Values Using Scaling Factorsget_time_as
Helper function to summarize outputs from glm fitglm_makeup
Kaplan Meier (KM) plot function for anchored and unanchored caseskmplot
Kaplan-Meier (KM) plot function for anchored and unanchored cases using ggplotkmplot2
Anchored MAIC for binary and time-to-event endpointmaic_anchored
Forest Plot for One or More MAIC Objectsmaic_forest_plot
Unanchored MAIC for binary and time-to-event endpointmaic_unanchored
Helper function to retrieve median survival time from a 'survival::survfit' objectmedSurv_makeup
Diagnosis plot of proportional hazard assumption for anchored and unanchoredph_diagplot
PH Diagnosis Plot of Log Cumulative Hazard Rate versus time or log-timeph_diagplot_lch
PH Diagnosis Plot of Schoenfeld residuals for a Cox model fitph_diagplot_schoenfeld
Plot MAIC weights in a histogram with key statistics in legendplot_weights_base
Plot MAIC weights in a histogram with key statistics in legend using 'ggplot2'plot_weights_ggplot
Pre-process aggregate dataprocess_agd
Pseudo individual patient survival data from published studypseudo_ipd_sat
Pseudo individual patient survival data from published two arm studypseudo_ipd_twt
Get and Set Time Conversion Factorsget_time_conversion set_time_conversion
Helper function to select set of variables used for Kaplan-Meier plotsurvfit_makeup
Weighted object for single arm trial dataweighted_sat
Weighted object for two arm trial dataweighted_twt