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bonsaiforest (version 0.1.1)

Shrinkage Based Forest Plots

Description

Subgroup analyses are routinely performed in clinical trial analyses. From a methodological perspective, two key issues of subgroup analyses are multiplicity (even if only predefined subgroups are investigated) and the low sample sizes of subgroups which lead to highly variable estimates, see e.g. Yusuf et al (1991) . This package implements subgroup estimates based on Bayesian shrinkage priors, see Carvalho et al (2019) . In addition, estimates based on penalized likelihood inference are available, based on Simon et al (2011) . The corresponding shrinkage based forest plots address the aforementioned issues and can complement standard forest plots in practical clinical trial analyses.

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Install

install.packages('bonsaiforest')

Monthly Downloads

151

Version

0.1.1

License

Apache License 2.0

Issues

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Maintainer

Isaac Gravestock

Last Published

September 27th, 2024

Functions in bonsaiforest (0.1.1)

naivepop_fit_surv

Naivepop Fit Survival
naivepop

Naive Overall Population Model Estimation
trt_horseshoe

Subgroup Treatment Effect Horseshoe
print.summary.naivepop

Print Function for Naivepop Summary
print.summary.naive

Print Function for Naive Summary
survival_curves

Average Survival Curves
simul_covariates

Generation of a Design Matrix for Simulations
plot.summary.elastic_net

Forest plot Summary Elastic Net
simul_data

Simulate Covariates and Progression Free Survival Data
plot.summary.horseshoe

Forest plot Summary Horseshoe
naive_fit_bin

Naive Fit Binary
summary.horseshoe

Summary Horseshoe Function
km_fun

Helper Function to get Kaplan-Meier Estimate
naivepop_fit_bin

Naivepop Fit Binary
print.summary.horseshoe

Print Function for Horseshoe Summary
plot.summary.naive

Forest plot Summary Naive
simul_pfs

Simulation of Progression Free Survival Times
naive_fit_surv

Naive Fit Survival
plot.compare.data

Compare Forest Plots
preprocess

Data Preprocessing
summary.elastic_net

Summary Elastic Net Function
print.summary.elastic_net

Print Function for Elastic Net Summary
subgroups

Subgroup Treatment Effect
summary.naivepop

Summary Naivepop Function
summary.naive

Summary Naive
elastic_net_fit_surv

Elastic Net Fit Survival
ahr_estimation

Average Hazard Ratio Estimation
ahr_from_km

Average Hazard Estimation based on Kaplan-Meier Estimates
compare

Compare Treatment Estimate Methods
elastic_net

Elastic Net Penalization Model Estimation
naive

Naive Model Estimation
lor_estimation

Estimation of Log-Odds Ratio
horseshoe

Bayesian Shrinkage Model Estimation
generate_stacked_data

Generation of Stacked Data by Subgroups
bonsaiforest-package

bonsaiforest: Shrinkage Based Forest Plots
elastic_net_fit_bin

Elastic Net Fit Binary
horseshoe_fit_bin

Horseshoe Fit Binary
horseshoe_fit_surv

Horseshoe Fit Survival
design_matrix1

Design Matrix Subgroup x_1a
example_data

Example data
cut_norm_quant

Helper for Cutting into Normal Quantiles
design_dummy1

Design Dummy Subgroup x_1a
elastic_net_surv

H0, Coefficients Elastic Net Survival Model and Matrices
est_coef_bin1

Estimated coefficients elastic net Binary