scaleUsage.r

set.seed(20091975)
## number of stimuli
J <- 6

## draw the stimuli. hold them fixed
x <- sort(runif(J))

sim <- function(
                N=100, ## number of individuals
                intercept=0, 
                slope=1,
                sigma=.1
                ) {
    a <- rep(intercept,N)
    b <- rep(slope,N)
    y <- a+b%*%t(x)+matrix(rnorm(N*J,0,sigma), ncol=J)
    ## constrain
    y[y<0] <- 0
    y[y>1] <- 1
    ## calculate bias
    bias <- x-predict(lm(x~apply(y,2,mean)))
    bias
}


res <- t(sapply(seq(-0.5,.5, .1), function(x) apply(replicate(100, sim(intercept=x)),1,mean)))
matplot(res)