The relationship of bicycle use and aggressive driving behaviour: a latent variable model approach

Figures & data

Table 1. Description and values of the variables.

Variable	Description		Categories	Frequency	%
Gender	Gender of respondent		Male	195	65.0
			Female	105	35.0
Age	Age of respondent		18–24	102	34.0
			25–54	138	46.0
			55–64	45	15.0
			65+	15	5.0
Driving experience	Driving experience of respondent		0–5 years	116	38.7
			6+ years	184	61.3
Bike use	Use or former use of a bicycle in the city		Motorcycle and car	51	17.0
			Car only	121	40.3
			Bicycle and car	93	31.0
			All	35	11.7
Lane-change behavior	The respondent attempts lane-change if his/her lane is more congested		When necessary	202	67.3
			Constantly	98	32.7
Emergency lane use	The respondent drives on the emergency lane of motorways in order to travel faster		Sometimes	63	21.0
			Only during congestion	34	11.3
			Never	203	67.7
Maximum speed in urban areas (categorical)	The maximum speed of a driver when driving in an urban area		Below speed limit	25	8.3
			Speed limit	91	30.3
			Above speed limit	184	61.3
Maximum speed in urban areas	The maximum speed of a driver when driving in an urban area (km/h)	Min value	Max value	Mean	Std. Deviation
		30.00	140.00	63.95	17.228

Table 2. Latent variable indicators’ categories.

Variable	Categories	Code
Lane-change behavior	When necessary	(reference)
	Constantly	I1
Emergency lane use	Sometimes	I21
	Only during congestion	I22
	Never	(reference)
Maximum speed in urban areas	Below speed limit	I31
	Speed limit	(reference)
	Above speed limit	I32

Table 3. Inferential statistics results.

		Lane-change behavior				Emergency lane use					Speed limit
		Frequencies				Frequencies					Frequencies
		When necessary	Constantly	Statistical test		Some times	Only during congestion	Never	Statistical test		Below speed limit	Speed limit	Above speed limit	Statistical test
Gender	Male	129	66	Pearson Chi-squared	0.352	41	24	130	Pearson Chi-squared	0.549	11	46	138	Pearson Chi-squared	21.287
	Female	73	32	p-value	0.553	22	10	73	p-value	0.760	14	15	46	p-value	0.000
Age	18–24	61	41	Mann-Whitney U	8500	25	14	63	Kruskal-Wallis H	1.685	4	27	71	Kruskal-Wallis H	24.177
	25–54	97	41	Wilcoxon W	13351	26	13	99	df	2	5	46	87	df	2
	55–64	29	16	Z-score	−2.139	10	7	28	Asymp. Sig.	0.431	7	13	25	Asymp. Sig.	0.000
	65+	15	0	Asymp. Sig.	0.032	2	0	13			9	5	1
Years of driving	0–5 years	75	41	Pearson Chi-squared	0.617	29	15	72	Pearson Chi-squared	2.743	6	32	78	Pearson Chi-squared	3.815
	6+ years	127	57	p-value	0.432	34	19	131	p-value	0.254	19	59	106	p-value	0.148
Transport modes used	Motorcycle and car	35	16	Pearson Chi-squared	22.389	11	2	38	Pearson Chi-squared	35.728	3	11	37	Pearson Chi-squared	27.308
	Car only	64	57			35	25	61			7	25	89
	Bicycle and car	77	16	p-value	0.000	9	4	80	p-value	0.000	10	44	39	p-value	0.000
	All	26	9			8	3	24			5	11	19

Table 4. Parameter estimates of the model.

Variable	Estimate	t-ratio
Latent variable specification
Female dummy	−0.8947	−3.15
Age dummy variables
Age 18–24 (reference)	-	-
Age 25–54	−0.2865	−1.39
Age 55–64	−0.7559	−1.99
Age 65+	−3.4520	−3.89
Bicycle use dummy varibles
Car only (reference)	-	-
Motorcycle and car	−0.7076	−2.38
Bicycle and car	−1.5565	−4.68
All	−1.1958	−2.87
Indicators’ specification
μ1	0.3428	1.25
μ21	−0.4064	−1.39
μ22	−0.7027	−2.05
μ31	−4.2463	−2.97
μ32	2.5120	4.27
ζ1	0.9062	3.63
ζ21	0.5559	2.84
ζ22	1.2111	3.11
ζ31	−0.9984	−1.96
ζ32	1.2067	3.27
LL: −623.67
LL (null): −673.46
Likelihood ratio test: 99.58 (df = 7, χ^2, crit .01 = 18.48)
AIC: 1281.34
AIC (null): 1366.92
BIC: 1344.31
BIC (null): 1403.96
Observations: 300

Table 5. Likelihood ratio tests’ results.

Variables	LL	Models compared	LR	Degrees of freedom	χ^2(95%,df)
Null model (Model 0)	−673.46
Bike use variable included (Model 1)	−650.00	Model 1 vs Model 0	46.93	3	7.81
Gender variable included (Model 2)	−644.86	Model 2 vs Model 1	10.27	1	3.84
Age variable included (Model 3)	−623.67	Model 3 vs Model 2	42.38	3	7.81

Table 6. T-ratios derived from the delta method.

	Age variable				Bike use variable
		Levels				Levels
		Age 25-54	Age 55-64	Age 65+		Motorcycle and car	Bicycle and car	All
	Age 25-54				Motorcycle and car
Reference level	Age 55-64	0.4694	-	-	Bicycle and car	0.8489	-	-
		-1.25				-3.06
	Age 65+	3.1655	2.6961	-	All	0.4882	-0.3607	-
		-3.7	-2.72			-1.21	(-0.85)

Table 7. Average marginal effects of independent variables.

	Lane-change behavior			Emergency lane use			Maximum speed in urban areas
		When necessary	Constantly	Never	Sometimes	Only during congestion	At the speed limit	Below speed limit	Above speed limit
Female dummy		0.161	−0.161	0.140	−0.051	−0.089	0.148	0.083	−0.231
Age 25–54		0.052	−0.052	0.045	−0.016	−0.029	0.047	0.027	−0.074
Age 55–64		0.136	−0.136	0.119	−0.043	−0.075	0.125	0.070	−0.195
Age 65+		0.622	−0.622	0.541	−0.197	−0.344	0.571	0.321	−0.892
Motorcycle and car		0.127	−0.127	0.111	−0.040	−0.071	0.117	0.066	−0.183
Bicycle and car		0.280	−0.280	0.244	−0.089	−0.155	0.257	0.145	−0.402
All		0.215	−0.215	0.188	−0.068	−0.119	0.198	0.111	−0.309

Figure 1. The effect of gender on the lane-change indicator.

Figure 2. The effect of age on the lane-change indicator.

Figure 3. The effect of bike use on the lane-change indicator.

Figure 4. The effect of gender on the emergency lane use indicator.

Figure 5. The effect of age on the emergency lane use indicator.

Figure 6. The effect of bike use on the emergency lane use indicator.

Figure 7. The effect of gender on the speed violation indicator.

Figure 8. The effect of age on the speed violation indicator.

Figure 9. The effect of bike use on the speed violation indicator.

Data availability statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author ([email protected]) upon reasonable request.