Table 3.

Multivariable modeling

Ordinary least squares: Outcome score ~ sex + BMI + faults (surgical leg) + faults (normal leg) + ratio (surgical leg avg distance/normal leg avg distance)
	Model- correlation values		Predictors—P values
	R2 values	Adj R2 values	Sex	BMI	Faults	Faults	Hop ratio
			Male	Weight	No. of faults on surgical leg	No. of faults on normal leg	Surgical leg avg measure
				Height2			Normal leg avg measure
IKDC
Single hop	0.2	0.1	0.38	0.13	0.95	0.37	<0.01*
Triple hop	0.2	0.2	0.56	0.22	0.35	0.53	<0.01*
Crossover hop	0.2	0.1	0.32	0.03*	0.65	0.08	0.06
Timed hop	0.2	0.1	0.52	0.13	0.65	0.99	0.01*
KOOS sports and recreation
Single hop	0.2	0.1	0.53	0.95	0.02*	0.26	<0.01*
Triple hop	0.1	0.0	0.51	0.97	0.19	0.45	0.06
Crossover hop	0.1	0.0	0.79	0.43	0.32	0.46	0.11
Timed hop	0.1	0.0	0.61	0.90	0.82	0.58	0.03*
KOOS knee-related quality of life
Single hop	0.1	0.0	0.96	0.66	0.66	0.10	0.19
Triple hop	0.1	0.0	0.87	0.91	0.70	0.36	0.04*
Crossover hop	0.0	0.0	0.82	0.52	0.56	0.46	0.55
Timed hop	0.1	0.0	0.99	0.69	0.84	0.92	0.07
Marx
Single hop	0.1	0.0	0.53	0.32	0.70	0.04*	0.61
Triple hop	0.1	0.0	0.60	0.45	0.41	0.05*	0.64
Crossover hop	0.1	0.0	0.41	0.18	0.16	0.22	0.93
Timed hop	0.1	0.0	0.49	0.51	0.78	0.84	0.18

Results of ordinary least squares modeling. General model is provided above the chart. Models are grouped by outcome score. Each model is identified by the hop test used to create the ratio. Coefficients, coefficients adjusted for the number of degrees of freedom, and the P value for each independent predictor are listed.

^*Indicates P values less than 0.05. These values are also shown in bold