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maicplus (version 0.1.2)

Matching Adjusted Indirect Comparison

Description

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) .

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Install

install.packages('maicplus')

Monthly Downloads

265

Version

0.1.2

License

Apache License 2.0

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Repository

https://github.com/hta-pharma/maicplus/

Homepage

https://hta-pharma.github.io/maicplus/

Maintainer

Isaac Gravestock

Last Published

February 21st, 2025

Functions in maicplus (0.1.2)

centered_ipd_sat

Centered patient data from single arm trial

ess_footnote_text

Note on Expected Sample Size Reduction

Check to see if weights are optimized correctly

Binary outcome data from two arm trial

Binary outcome data from single arm trial

Center individual patient data (IPD) variables using aggregate data averages

calculate_weights_legend

Calculate Statistics for Weight Plot Legend

Basic Kaplan Meier (KM) plot function

Create dummy variables from categorical variables in an individual patient data (ipd)

estimate_weights

Derive individual weights in the matching step of MAIC

get_pseudo_ipd_binary

Create pseudo IPD given aggregated binary data

ext_tte_transfer

helper function: transform TTE ADaM data to suitable input for survival R package

ph_diagplot_schoenfeld

PH Diagnosis Plot of Schoenfeld residuals for a Cox model fit

Helper function to retrieve median survival time from a survival::survfit object

ph_diagplot_lch

PH Diagnosis Plot of Log Cumulative Hazard Rate versus time or log-time

centered_ipd_twt

Centered patient data from two arm trial

find_SE_from_CI

Calculate standard error from the reported confidence interval.

Helper function to summarize outputs from glm fit

Kaplan-Meier (KM) plot function for anchored and unanchored cases using ggplot

Anchored MAIC for binary and time-to-event endpoint

maic_unanchored

Unanchored MAIC for binary and time-to-event endpoint

Diagnosis plot of proportional hazard assumption for anchored and unanchored

Kaplan Meier (KM) plot function for anchored and unanchored cases

Pseudo individual patient survival data from published two arm study

Helper function to select set of variables used for Kaplan-Meier plot

Reformat maicplus_bucher alike object

maicplus-package

maicplus: Matching Adjusted Indirect Comparison

Pre-process aggregate data

Pseudo individual patient survival data from published study

Convert Time Values Using Scaling Factors

set_time_conversion

Get and Set Time Conversion Factors

plot_weights_base

Plot MAIC weights in a histogram with key statistics in legend

Weighted object for two arm trial data

plot_weights_ggplot

Plot MAIC weights in a histogram with key statistics in legend using ggplot2

Weighted object for single arm trial data

Survival data from single arm trial

Basic Kaplan Meier (KM) plot function using ggplot

Bucher method for combining treatment effects

Patient data from single arm study

Survival data from two arm trial

Aggregate effect modifier data from published study

Patient data from two arm trial