. 2022 Jun 29;50(6):1284–1298. doi: 10.3758/s13421-022-01331-0

Table 3.

Summary of linear mixed effects models analyzed in Study 2

	Lexical Recognition RT		Semantic Processing RT
	Model 1		Model 2		Model 3
Predictors	Estimates	p	Estimates	p	Estimates	p
(Intercept)	915.79	<0.001	977.62	<0.001	977.61	<0.001
Log Frequency (Year 2000)	-63.55	<0.001	3.50	0.609	3.71	0.590
Word Length	28.14	<0.001	-21.36	0.002	-21.36	0.002
Age of Acquisition (AOA)	79.17	<0.001	10.53	0.105	10.48	0.107
Emotionality	-3.50	0.075	-11.20	0.108	-11.47	0.102
Valence	-6.49	0.001	-15.69	0.018	-15.83	0.017
Arousal	-28.87	<0.001	1.27	0.855	1.45	0.835
Concreteness	-7.59	0.001	-46.65	<0.001	-38.29	<0.001
Age (Continuous)	1.86	<0.001
Age (Middle-aged Adults = TRUE)			48.69	0.043	48.93	0.042
Semantic Stability btw 1970-2000	-2.48	0.218	-20.80	0.001	-11.46	0.091
Middle-aged:Semantic Stability					-18.93	<0.001
Middle-aged:Concreteness					-16.70	<0.001
Concreteness:Semantic Stability					0.38	0.956
Middle-aged:Concreteness:Semantic Stability					-6.59	0.083
Random Effects
σ²	327530.75		142385.96		142216.83
τ₀₀	17564.11 _Word		33545.40 _id		33545.82 _id
			6465.37 _Word		6500.28 _Word
ICC	0.05		0.22		0.22
N	5385 _Word		237 _id		237 _id
			180 _Word		180 _Word
Observations	3267383		42505		42505
Marginal R² / Conditional R²	0.056/0.104		0.018/0.233		0.019/0.235

Age is coded as a categorical variable (Younger adults = 0, Middle-aged adults = 1) in the semantic decision task (Models 2 & 3) while it is a continuous variable in lexical decision task (Model 1). All continuous predictors are standardized.