Table 4.

Solitary and dyadic sexual desire associated with sexual satisfaction (Study 1)

	Single individuals				Partnered individuals
	β	t	p	$r_s^2$	β	t	p	$r_s^2$
Gender	.05	0.76	.45	.08	− .06	− 0.96	.34	.01
Age	− .01	− 0.23	.82	.00	− .05	− 0.83	.41	.10
Solitary desire	− .01	− 0.08	.94	.20	− .29	− 4.38	< .001	.16
Dyadic desire	− .34	− 5.10	< .001	.98	–	–	–
Dyadic desire (Partner)	–	–	–		.43	6.68	< .001	.52
Dyadic desire (Other)	–	–	–		− .11	− 1.58	.12	.06

$r_s^2$ = squared structure coefficient, representing the proportion of variance in the regression effect explained by each predictor, irrespective of collinearity with other predictors. We also reported results from commonality analysis which separates the unique variance explained by each predictor from the shared variance between all combinations of predictors and can help interpreting the regression results, especially in the presence of multicollinearity (Ray‐Mukherjee et al., 2014). Gender was coded as 0 = men and 1 = women