CutCI: Calculate confidence intervals for grouped values

Description

CutCI groups values of one variable into intervals with the same number of observations each and computes confidence intervals for the mean of another variable in each interval.

CIrho computes the normal theory confidence interval for a vector of values.

Usage

CutCI(dat, number = 10, func = mean, alpha=0.95)
CIrho(rho, alpha = 0.95)

Arguments

dat

a numerical data frame or matrix with two columns, the first of which gets averaged, and the second of which defines the grouping

number

the number of equal-count intervals

func

summary function for computing the mean

rho

a vector of measurements

alpha

the desired confidence level

Value

x: the midpoints of the grouping intervals
y: the means within each interval, as computed by func
yci: a matrix with two columns, giving the lower and upper end of the confidence interval respectively

Details

The quantiles for the confidence interval are taken from the standard normal distribution, so a reasonable number of observations per interval would be good.

Examples

Run this code

x = rnorm(100, mean=2)
CIrho(x)

y = 2 + 3*x + rnorm(100)
cc = CutCI(cbind(x,y), number=5)
print(cc)

# Show it
plot(cc$x, cc$y)
arrows(cc$x, cc$yci[,1], cc$x, cc$yci[,2], length=0)