Evaluate m-alternative forced choice test

Scores a set of test trials against a model's word-object matrix, returning the probability of choosing the correct object on each trial. Each trial presents one word and a set of candidate referents; the correct object is the one whose id matches the word's id (the package's diagonal convention), unless the test gives an explicit correct object for that trial (e.g. to test a word's association with a second, co-occurring referent, with its own referent absent). A thin wrapper over predict_referent().

Usage

mafc_test(m, test, ...)

Arguments

m

A matrix representing model memory with words as rows and referents as columns.

test

A list representing the test trials: words (one word per trial), objects (the candidate referents on each trial), and optionally correct (the correct referent on each trial; defaults to the word's own id).

...

Further arguments passed to predict_referent() (e.g. pragmatic, threshold, or d, the exponent of a power choice rule).

Value

A vector with the probability of choosing the correct object, given each word.

Examples

dat <- xsl_datasets[[10]]
x <- xsl_run(baseline(), dat)
mat <- x$fits[[1]]$matrix
mafc_test(mat, dat$test)
#>  [1] 0.6666667 0.8571429 0.7500000 0.6000000 0.8571429 0.6666667 0.8571429
#>  [8] 0.6000000 0.8571429 0.6666667 0.6666667 0.5454545 0.8571429 0.8571429
#> [15] 0.6000000 0.6000000 0.6000000 0.6666667