Confidence intervals for crossover points using the bootstrap methods

Description

Calculate confidence intervals for crossover points of two simple linear regression lines using the bootstrap

Usage

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BootC(Data)

Arguments

Data

a dataframe containing data values for y, x1, and x2

Details

The function BootC() calculates confidence intervals for the crossover point C using the boot package in R. Bootstrap confidence intervals include Normal, Basic, Percentile, and BCa confidence intervals.

Author(s)

Sunbok Lee

References

Bollen, K. A., & Stine, R. (1990). Direct and indirect effects: Classical and bootstrap estimate of variability. Sociological Methodology, 20, 115-140.

Examples

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# example data
library(MASS)
out <- mvrnorm(1000, mu = c(0,0), Sigma = matrix(c(1,0.2,0.2,1), ncol = 2),empirical = TRUE)
x1 <- out[,1]
x2 <- out[,2]
epsilon <-rnorm(1000,0,1)
y <- 1 + 1*x1 + 0.5*x2 + 1*x1*x2 + epsilon  # true C = -0.5/1 = -0.5
simData <- data.frame(y=y,x1=x1,x2=x2)

# run BootC()
library(boot)
BootC(simData)