Modelfree estimation of a psychometric function 


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bootstrap_ci_th
[ci,th0] = bootstrap_ci_th(TH,r,m,x,N,h0,alpha,X,link,guessing,lapsing,K,p,ker,maxiter,tol);
Bootstrap estimate of a confidence interval at a significance level alpha for the estimated threshold for the local polynomial estimate of the psychometric function with guessing and lapsing rates. The confidence interval is based on bootstrap percentiles.
Input:
TH
: required threshold level
r
: number of successes at pointsx
m
: number of trials at pointsx
x
: stimulus levels
N
: number of bootstrap replications;N
should be at least 1000 for reliable results
h0
: bandwidthOptional input:
alpha
: significance level of the confidence interval; default is 0.05
X
: set of values at which estimates of the psychometric function for the threshold estimation are to be obtained; if not given, 1000 equally spaced points from minimum to maximum ofx
are used
link
: name of the link function; default is'logit'
guessing
: guessing rate; default is 0
lapsing
: lapsing rate; default is 0
K
: power parameter for Weibull and reverse Weibull link; default is 2
p
: degree of the polynomial; default is1
ker
: kernel function for weights; default is'normpdf'
maxiter
: maximum number of iterations in Fisher scoring; default is 50
tol
: tolerance level at which to stop Fisher scoring; default is 1e6
Output:
ci
: confidence interval based on bootstrap percentiles
th0
: threshold estimate