lik6pt function

Compute Log Likelihood for 6-point Test

Compute Log Likelihood for 6-point Test

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)(a, b) > (a', b') and (b,c)>(b,c)(b, c) > (b', c') then it must be that (a,c)>(a,c)(a, c) > (a', c'), where the symbol >> is taken here to mean is judged more different than . Given the observer's difference scale and σ\sigma estimate, the likelihood of the choices made is calculated based on the link function indicated in the mlds object.

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-point test. The list can be constructed with the function GetSixPts.
  • ...: currently unused.

Returns

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, tools:::Rd_expr_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, tools:::Rd_expr_doi("10.18637/jss.v025.i02") .

Author(s)

Kenneth Knoblauch, based on C code by Laurence T. Maloney and J. N. Yang.

See Also

Get6pts, mlds, simu.6pt

Examples

data(kk1) x.df <- mlds(SwapOrder(kk1)) lik6pt(x.df, Get6pts(x.df, nrep = 1))
  • Maintainer: Kenneth Knoblauch
  • License: GPL (>= 2)
  • Last published: 2023-08-20

Useful links