# R example codes for predboot package (https://github.com/nomahi/predboot)
# Reference: Noma, H., Shinozaki, T., Iba, K., Teramukai, S. and Furukawa, T. A. (2020). 
# Confidence intervals of prediction accuracy measures for multivariable prediction models based on the bootstrap-based optimism correction methods. 
# arXiv:2005.01457. https://arxiv.org/abs/2005.01457


# Installation of the predboot package
require(devtools)
devtools::install_github("nomahi/predboot")

# Load the example dataset
library(predboot)
?predboot		# Help file
data(exdata)	# A hypothetical simulated cohort dataset

# Location-shifted bootstrap CI for ML estimation
pred.ML(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000)	# 8 variables model
pred.ML(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000)	# 17 variables model

# Two-stage bootstrap CI for ML estimation
pred.ML2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000) 	# 8 variables model
pred.ML2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000) 	# 17 variables model

# Location-shifted bootstrap CI for ridge estimation
pred.ridge(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000)	# 8 variables model
pred.ridge(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000)	# 17 variables model

# Two-stage bootstrap CI for ridge estimation
pred.ridge2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000) 	# 8 variables model
pred.ridge2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000) 	# 17 variables model

# Location-shifted bootstrap CI for lasso estimation
pred.lasso(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000)	# 8 variables model
pred.lasso(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000)	# 17 variables model

# Two-stage bootstrap CI for lasso estimation
pred.lasso2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR, data=exdata, B=1000) 	# 8 variables model
pred.lasso2(Y ~ A65 + SEX + DIA + HYP + HRT + HIG + SHO + TTR + PMI + HEI + WEI + HTN + SMK1 + SMK2 + LIP + PAN + FAM + ST4, data=exdata, B=1000) 	# 17 variables model