Table 4.

Model-averaged posterior summaries for multiple linear regression coefficients: Baseline.

Coefficient	P(incl)	P(excl)	P(incl|data)	P(excl|data)	BFincl	Mean	SD	95% Credible interval
								Lower	Upper
Intercept	1.000	0.000	1.000	0.000	1.000	14.980	0.506	13.986	16.036
CCP-R	0.550	0.450	0.921	0.079	9.588	0.655	0.330	−0.011	1.183
CCP-NC	0.511	0.489	0.444	0.556	0.765	0.085	0.173	−0.190	0.473
Fear	0.625	0.375	0.922	0.078	7.070	0.695	0.483	−0.047	1.774
Anger	0.475	0.525	0.379	0.621	0.676	0.012	0.082	−0.155	0.247
CCA	0.550	0.450	0.661	0.339	1.596	0.262	0.332	−0.024	1.105
Fear * CCA	0.375	0.625	0.401	0.599	1.116	−0.015	0.025	−0.081	0.007

The first column lists all predictor included in the regression; P(incl) and P(excl) represent the prior inclusion and exclusion probabilities, respectively; P(incl|data) and P(excl|data) represent the posterior inclusion and exclusion probabilities. BF_incl is the inclusion Bayes factor which quantifies the change from prior to posterior odds, Mean and SD are the posterior mean and standard deviation of the parameter following model averaging. The last two columns represent the 95% credible interval (CI) for each parameter. CCP-R, Reality subdimensions of the climate change perception scale; CCP-NC, Negative consequences subdimension of the climate change perception scale; Fear, climate change-related fear; Anger, climate change-related anger; CCA, climate change anxiety.