Table 4.

Predictors overall fairness of the compensation process

Independent variables	Overall fairness claims process
	Model 1				Model 2
	AOR	CI		p	AOR	CI		p
Age	0.99	0.97,	1.01	.21	1.00	0.97,	1.02	.73
Gender	0.75	0.38,	1.48	.41	0.79	0.37,	1.68	.54
Country of birth	0.91	0.44,	1.87	.79	0.87	0.38,	1.97	.73
Socio-economic status	1.84	0.95,	3.56	.07	1.38	0.65,	2.94	.41
Education	0.58	0.28,	1.21	.15	0.46	0.20,	1.06	.07
Marital status	2.11	1.09,	4.06	.03	1.69	0.81,	3.55	.16
Injury	0.43	0.19,	0.94	.04	0.65	0.26,	1.60	.35
Hospital admission	0.73	0.36,	1.49	.38	1.08	0.48,	2.45	.85
Time after injury	1.04	0.54,	1.99	.91	1.08	0.48,	2.44	.86
Medical assessment					0.31	0.12,	0.78	.01
Lawyer involvement					0.33	0.13,	0.81	.02
Claim status					1.71	0.68,	4.32	.26
Previous claim					1.66	0.68,	4.03	.26

Notes: Model 1 Nagelkerke R² = .111; Model 2 Nagelkerke R² = .339

Multiple logistic regression analysis, modelling the probability that the process was considered fair (versus not fair/neutral). The first model includes demographic and injury details. The second model adds the claim factors. ‘At-fault’ was not included because this variable only applies to the Victorian sample. There was no multicollinearity

Coding: Gender (0 = Male; 1 = Female); Country of birth (0 = Other; 1 = Australia); Socio-economic status (0 = Lower; 1 = Higher); Education (0 = Low/Medium; 1 = High); Marital status (0 = Single/Divorced; 1 = Married); Injury (0 = Other; 1 = Whiplash/soft tissue injury); Hospital admission (0 = No; 1 = Yes); Time after injury (0 = 12 months; 1 = 24 months). Medical assessment (0 = No; 1 = Yes); Lawyer involvement (0 = No; 1 = Yes); Claim status (0 = Pending; 1 = Settled); Previous claim (0 = No; 1 = Yes); Overall fairness claims process (0 = not fair/neutral, 1 = fair). Reference category = 0