Matching Adjusted Indirect Comparison


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Documentation for package ‘maicplus’ version 0.1.2

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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
basic_kmplot Basic Kaplan Meier (KM) plot function
basic_kmplot2 Basic Kaplan Meier (KM) plot function using ggplot
bucher Bucher method for combining treatment effects
centered_ipd_sat Centered patient data from single arm trial
centered_ipd_twt Centered patient data from two arm trial
center_ipd Center individual patient data (IPD) variables using aggregate data averages
check_weights Check to see if weights are optimized correctly
dummize_ipd Create dummy variables from categorical variables in an individual patient data (ipd)
estimate_weights Derive individual weights in the matching step of MAIC
find_SE_from_CI Calculate standard error from the reported confidence interval.
get_pseudo_ipd_binary Create pseudo IPD given aggregated binary data
get_time_as Convert Time Values Using Scaling Factors
get_time_conversion Get and Set Time Conversion Factors
glm_makeup Helper function to summarize outputs from glm fit
kmplot Kaplan Meier (KM) plot function for anchored and unanchored cases
kmplot2 Kaplan-Meier (KM) plot function for anchored and unanchored cases using ggplot
maic_anchored Anchored MAIC for binary and time-to-event endpoint
maic_unanchored Unanchored MAIC for binary and time-to-event endpoint
medSurv_makeup Helper function to retrieve median survival time from a 'survival::survfit' object
ph_diagplot Diagnosis plot of proportional hazard assumption for anchored and unanchored
ph_diagplot_lch PH Diagnosis Plot of Log Cumulative Hazard Rate versus time or log-time
ph_diagplot_schoenfeld PH Diagnosis Plot of Schoenfeld residuals for a Cox model fit
plot.maicplus_estimate_weights Derive individual weights in the matching step of MAIC
plot_weights_base Plot MAIC weights in a histogram with key statistics in legend
plot_weights_ggplot Plot MAIC weights in a histogram with key statistics in legend using 'ggplot2'
print.maicplus_bucher Bucher method for combining treatment effects
print.maicplus_check_weights Check to see if weights are optimized correctly
process_agd Pre-process aggregate data
pseudo_ipd_sat Pseudo individual patient survival data from published study
pseudo_ipd_twt Pseudo individual patient survival data from published two arm study
set_time_conversion Get and Set Time Conversion Factors
survfit_makeup Helper function to select set of variables used for Kaplan-Meier plot
weighted_sat Weighted object for single arm trial data
weighted_twt Weighted object for two arm trial data