Table 1. Fit Statistics for Guessing, Threshold, Associative Learning, and Hypothesis Testing Models of Concept Identification Learning.

	Fit Statistics
Model	Parameters	Deviance	pD	WAIC	K-S D Errors
Guessing	0	3,945,960.00	--	--	0.77
Threshold	101,785	2,376,306.00			0.00
Associative Learning
Guessing and Learned	35,556	1,862,407.00	24,816.66	1,923,774.00	0.13
Perseverative, Guessing, and Learned	71,111	1,832,287.00	29,067.85	1,904,628.00	0.12
Hypothesis Testing
Guessing and Learned	35,556	1,844,850.00	22,528.04	1,902,575.00	0.13
Perseverative, Guessing, and Learned	71,111	1,803,620.00	28,024.10	1,876,088.00	0.12

Note. Parameters = total number of parameters; Deviance = -2log-likelihood; pD = effective number of parameters; WAIC = Wantanabe-Akaike information criterion; K-S D Errors= Kolmogorov-Smirnov distance comparing observed and model expected cumulative distributions of total errors. Guessing and Threshold model parameters were not estimated, and thus these have no pD or WAIC values.