MLDS (version 0.2-1)

lik6pt: Compute Log Likelihood for 6-point Test

Description

The 6-point test evaluates the validity of the estimated difference scale. Given 6 values, a, b, c, a', b', c', on the stimulus scale, if the pair $(a, b) > (a', b')$ and $(b, c) > (b', c')$ then it must be that $(a, c) > (a', c')$, where the symbol $>$ is taken here to mean is judged more different than. Given the observer's difference scale and $\sigma$ estimate, the likelihood of the choices made is calculated based on the link function indicated in the mlds object.

Usage

lik6pt(x, Six.Pts, ...)

Arguments

x

an object of class 'mlds', typically created by mlds

Six.Pts

a list of 3 data.frames, with names A, B, E. Each data.frame corresponds to a sample from a difference scaling experiment. The corresponding rows of the three data.frames yield the triples of trials that provide a 6

...

currently unused.

Value

• Returns the likelihood of the observer's responses for all of the 6-point conditions from a given data set. As currently implemented, it returns a 1x1 matrix.

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

Get6pts, mlds, simu.6pt

Examples

data(kk1)
x.df <- mlds(SwapOrder(kk1))
lik6pt(x.df, Get6pts(x.df))