Table 9. Experiment 2: Model estimates for the planned analysis with set size as a categorical predictor.

Measure	Predictor	$\hat{\beta }$ (log ms)	95% CrI	Bayes factors (BF10)
				Informative	Planned	Diffuse
First fixation duration
	Intercept	5.66	[5.55, 5.75]	–	–	–
	Set size	0.02	[−0.01, 0.05]	1.69	0.10	0.02
	Distance	0.01	[−0.02, 0.03]	0.27	0.06	0.04
	Set size × distance	0.01	[−0.02, 0.03]	0.19	0.00	0.00
First pass reading time
	Intercept	5.74	[5.58, 5.89]	–	–	–
	Set size	0.02	[−0.01, 0.05]	2.02	0.10	0.02
	Distance	0.00	[−0.02, 0.03]	0.27	0.05	0.03
	Set size × distance	0.01	[−0.02, 0.03]	0.32	0.01	0.00
Total fixation time
	Intercept	5.89	[5.71, 6.06]	–	–	–
	Set size	0.00	[−0.04, 0.04]	1.16	0.09	0.02
	Distance	0.00	[−0.03, 0.03]	0.28	0.05	0.03
	Set size × distance	0.01	[−0.04, 0.04]	0.59	0.02	0.00
Regression path duration
	Intercept	5.86	[5.69, 6.03]	–	–	–
	Set size	0.01	[−0.03, 0.05]	1.38	0.08	0.02
	Distance	0.01	[−0.02, 0.04]	0.41	0.07	0.04
	Set size × distance	0.01	[−0.02, 0.04]	0.80	0.05	0.01

Note:

$\hat{\beta }$ represents the model’s estimated effect for each of the predictors on the log scale. The log transform means that estimates with a positive sign indicate slower reading times and that readers who are slower on average will be more affected by the manipulation than faster readers. The 95% Bayesian credible interval (CrI) gives the range in which 95% of the model’s samples fell. Bayes factors are presented for a range of β priors including, from left to right: more informative than the prior used in the planned analysis, N(0, 0.1); the prior used in the planned analysis, N(0, 0.5); and more diffuse than the prior used in the planned analysis, N(0, 1). BF₁₀ indicates the Bayes factor for the full model (1) against a reduced model (0). Bayes factors of less than 0.3 indicate evidence for the reduced model, while Bayes factors greater than 3.0 suggest evidence for the full model.