Prediction Methods for Routine Maintenance Costs of a Reinforced Concrete Beam Bridge Based on Panel Data

Table 2

Hierarchical regression analysis results of the RC beam bridge.

Variables in the model			Group 3 (2)			Group 3 (3)			Group 3 (4)			Group 3 (5)
			β			β			β			β
Independent variables	1	Shanbei	0.229	1.124	0.271	0.082	0.324	0.749	0.145	0.829	0.414	0.1	0.6	0.51
		Guanzhong	−0.068	−0.352	0.728	−0.019	−0.111	0.912	−0.06	−0.354	0.726	−0.077	−0.454	0.653
	2	Age	0.613	3.782	0.001	0.609	3.917	0.001	0.622	3.977	0	0.643	3.64	0.001
	3	AADT	0.238	0.498	0.623	0.13	0.695	0.493
		Heavy traffic	−0.079	−0.174	0.863
		Heavy-truck ratio				0.187	0.834	0.411
		ESAL							0.049	0.301	0.766
		Cumulative ESAL										−0.026	−0.137	0.892
Summary of the model	R^2		0.393			0.408			0.377			0.376
	Adjusted R^2		0.281			0.298			0.289			0.287
			0.014			0.011			0.008			0.009
			0.018			0.032			0.002			0
			0.677			0.487			0.766			0.892