Table 2. Estimated coefficients with standard errors from hierarchical multinomial regression predicting subgoal choice.

Likelihood-ratio test statistics compare regression models to the null hypothesis of sampling subgoals uniformly at random.

Normative Algorithm	Explicit Probe	Implicit Probe	Teleportation Question
RRTD-IDDFS	β = 1.78	β = 1.63	β = 0.73
	SE = 0.04	SE = 0.04	SE = 0.06
	χ2(2) = 5183.1	χ2(2) = 3941.2	χ2(1) = 155.7
	p < .001	p < .001	p < .001
RRTD-BFS	β = 4.98	β = 4.94	β = 1.45
	SE = 0.10	SE = 0.11	SE = 0.20
	χ2(2) = 4412.8	χ2(2) = 3402.8	χ2(1) = 55.1
	p < .001	p < .001	p < .001
RRTD-RW	β = 0.37	β = 0.92	β = 0.29
	SE = 0.02	SE = 0.03	SE = 0.05
	χ2(2) = 686.7	χ2(2) = 1822.1	χ2(1) = 39.9
	p < .001	p < .001	p < .001
Solway et al. (2014) [8]	β = 0.75	β = 0.69	β = 0.37
	SE = 0.02	SE = 0.02	SE = 0.03
	χ2(2) = 3929.7	χ2(2) = 3072.7	χ2(1) = 114.3
	p < .001	p < .001	p < .001
Tomov et al. (2020) [7]	β = 1.09	β = 0.97	β = 0.41
	SE = 0.03	SE = 0.02	SE = 0.04
	χ2(2) = 3678.7	χ2(2) = 3056.4	χ2(1) = 102.4
	p < .001	p < .001	p < .001
Heuristic	Explicit Probe	Implicit Probe	Teleportation Question
QCut	β = −0.14	β = −0.19	β = 0.04
	SE = 0.01	SE = 0.01	SE = 0.04
	χ2(2) = 1504.3	χ2(2) = 1236.3	χ2(1) = 1.4
	p < .001	p < .001	p = .238
Degree Cent. (log)	β = 0.73	β = 0.64	β = 0.45
	SE = 0.02	SE = 0.02	SE = 0.04
	χ2(2) = 2534.3	χ2(2) = 1923.3	χ2(1) = 116.0
	p < .001	p < .001	p < .001
Betweenness Cent. (log)	β = 0.86	β = 0.82	β = 0.58
	SE = 0.02	SE = 0.02	SE = 0.03
	χ2(2) = 5598.2	χ2(2) = 4666.1	χ2(1) = 307.3
	p < .001	p < .001	p < .001
State Occupancy (log)	β = 1.00	β = 0.89	β = 0.39
	SE = 0.03	SE = 0.03	SE = 0.04
	χ2(2) = 3222.8	χ2(2) = 2673.3	χ2(1) = 103.3
	p < .001	p < .001	p < .001