simu.6pt: Perform Bootstrap Test on 6-point Likelihood for MLDS FIT

Description Usage Arguments Value Author(s) References See Also Examples

Description

Using the fitted responses (probabilities) to the difference scale, new responses are generated which permit new 6-point likelihoods to be calculated. The distribution of a large number of such likelihoods can be compared with that obtained from the observed responses to evaluate the internal consistency of the estimated scale.

Usage

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simu.6pt(obj, nsim = 1, nrep, no.warn = TRUE)

Arguments

obj

object of class ‘mlds’

nsim

integer indicating number of bootstrap trials.

nrep

integer indicating how many sessions with are in the data set.

no.warn

logical indicating when TRUE (default) to suppress warnings from glm.

Value

LIST with 4 components

boot.samp

vector of numeric giving the log likelihood for the 6-point test for each simulation.

lik6pt

numeric indicating the log likelihood for the 6-point test on the original data

p

proportion of simulations on which the simulated log likelihood was higher than that obtained from the original sample.

N

numeric indicating the number of simulations. It should be the length of boot.samp.

Author(s)

Kenneth Knoblauch and Laurence T. Maloney

References

Maloney, L. T. and Yang, J. N. (2003). Maximum likelihood difference scaling. Journal of Vision, 3(8):5, 573–585, http://journalofvision.org/3/8/5/, doi:10.1167/3.8.5.

Knoblauch, K. and Maloney, L. T. (2008) MLDS: Maximum likelihood difference scaling in R. Journal of Statistical Software, 25:2, 1–26, http://www.jstatsoft.org/v25/i02.

See Also

mlds, lik6pt

Examples

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	data(kk1)
	x.mlds <- mlds(SwapOrder(kk1))
	#nsim should be near 10,000 for stability,
	# but this will take a little time
	simu.6pt(x.mlds, 100, nrep = 1)

MLDS documentation built on May 1, 2019, 6:50 p.m.