BootC: Confidence intervals for crossover points using the bootstrap...

Description Usage Arguments Details Author(s) References Examples

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)


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