Bootstrap estimate of confidence interval for threshold estimation

Description

Finds bootstrap estimate of a confidence interval at a significant level alpha for the estimated threshold for the local polynomial estimation of psychometric function (PF) with guessing and lapsing rates specified in lims. Confidence interval is based on bootstrap percentiles

Usage

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bootstrap_ci_th( TH, r, m, x, N, h0, alpha = 0.05, X = (max(x)-min(x))*(0:999)/999+min(x), link = c( "logit" ), guessing = 0, lapsing = 0, K = 2, p = 1, ker = c( "dnorm" ), maxiter = 50, tol = 1e-6 )

Arguments

TH

required threshold level

r

number of successes in points x

m

number of trials in points x

x

stimulus levels

N

number of bootstrap replications

h0

pilot bandwidth; if not specified, then the scaled plug-in bandwidth is used

alpha

significance level of the confidence interval

X

set of value for which to calculate the estimates of PF for the thresholdestimation; if not given 1000 equally spaced points from min to max of xdes are used

link

name of the link function to be used; 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

order of the polynomial; default is 1

ker

kernel function for weights; default "dnorm"

maxiter

maximum number of iterations in Fisher scoring; default is 50

tol

tolerance level at which to stop Fisher scoring; default is 1e-6

Value

value

Object with 2 components: ci: confidence interval based on bootstrap percentiles th0: threshold estimate

Examples

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data( "01_Miranda" )
bwd <- 0.2959;
value <- bootstrap_ci_th( 0.5, example01$r, example01$m, example01$x, 10, bwd );

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