nosof94 {catlearn}R Documentation

Type I-VI category structure CIRP

Description

Shepard et al. (1961) stated that where there are two, equal-sized categories constructed from the eight stimuli it is possible to produce from varying three binary stimulus dimensions, there are only six logically distinct category structures. Shepard et al. (1961) labeled these structures as Types I through VI (see e.g. Nosofsky et al., 1994, Figure 1, for details). The CIRP concerns the relative difficulty of learning these category structures, as indexed by classification accuracy. The result, expressed in terms of accuracy, is:

I > II > [III, IV, V] > VI

The experiment reported by Nosofsky et al. (1994) provides the data for this CIRP.

Usage

data(nosof94)

Format

A data frame with the following columns:

type

Type of category structure, as defined by Shepard et al. (1961). Takes values : 1-6

block

Training block. Takes values: 1-16

error

Mean error probability, averaged across participants

Details

Wills et al. (n.d.) discuss the derivation of this CIRP. In brief, the effect has been independently replicagted. Nosofsky et al. (1994) was selected as the CIRP because it had acceptable sample size (N=40 per Type), and included simulations of the results with a number of different formal models. Inclusion of this dataset in catlearn thus permits a validation of catlearn model implementations against published simulations.

In Nosofsky et al. (1994) the stimuli varied in shape (squares or triangles), type of interior line (solid or dotted), and size (large or small). Each participant learned two problems. Each problem was trained with feedback, to a criterion of four consecutive sub-blocks of eight trials with no errors, or for a maximum of 400 trials.

The data are as shown in the first 16 rows of Table 1 of Nosofsky et al. (1994). Only the first 16 blocks are reported, for comparability with the model fitting reported in that paper. Where a participant reached criterion before 16 blocks, Nosofsky et al. assumed they would have made no further errors if they had continued.

Author(s)

Andy J. Wills andy@willslab.co.uk

Source

Nosofsky, R.M., Gluck, M.A., Plameri, T.J., McKinley, S.C. and Glauthier, P. (1994). Comparing models of rule-based classification learning: A replication and extension of Shepaard, Hovland, and Jenkins (1961). Memory and Cognition, 22, 352-369.

References

Shepard, R.N., Hovland, C.I., & Jenkins, H.M. (1961). learning and memorization of classifications. Psychological Monographs, 75, Whole No. 517.

Wills et al. (n.d.). Benchmarks for category learning. Manuscript in preparation.

See Also

nosof94train, nosof94oat


[Package catlearn version 1.0 Index]