Table 3.

Conditional logit model results for all patients

Variable	Description	β coefficient	Standard error	p value
Constant		0.17	0.20	0.40
Pain level	Minimal (0-2 of 10)	Constrained to be 0
	Moderate (3-6 of 10)	0.19	0.13	0.15
	Severe (7-10 of 10)	-0.59	0.13	< 0.01
Physical function level	100% of complete physical function	Constrained to be 0
	75% of complete physical function	-0.44	0.11	< 0.01
	50% of complete physical function	-0.80	0.10	< 0.01
Risk of infection (per 10% increase)		-0.22	0.07	< 0.01
Risk of reoperation (per 10% increase)		-0.05	0.07	0.51
Risk of implant failure leading to premature revision (per 10% increase)		-0.14	0.09	0.10
Risk of DVT (per 10% increase)		0.07	0.08	0.40
Risk of mortality (per 10% increase)		-0.04	0.08	0.66
Return to work	Return in 1 week	Constrained to be 0
	Return in 3 months	-0.20	0.12	0.09
	No return to work	-0.38	0.10	< 0.01

The β coefficient, or preference weights, signify the relative weight or importance of a corresponding attribute for participants deciding between surgical treatment for their arthritis as opposed to nonoperative treatment. The magnitude of the coefficients also has no intrinsic meaning, but these coefficients can be compared with one another to observe how respondents value each attribute, with relatively higher absolute values indicating greater importance placed on that attribute during decision-making. The sign (+/-) of a coefficient indicates whether that attribute contributes positively or negatively to the collective participants’ utility, or overall benefit gained as a result of choosing surgical treatment for arthritis as opposed to nonoperative treatment.