Table 2—

Comparison of linear regression models to evaluate age and height as predictors of speed and stride length for the same 57 dogs as in Table 1.

Outcome	Predictor	Adjusted R2*	AIC	Akaike weight†
Stride length	Age (y)	0.035	33.828	< 0.001
	Height (cm)	0.76	−45.87	0.198
	Height + age	0.78	−48.67	0.802
Stair trial 1	Age (y)	0.23	−6.37	0.497
	Height (cm)	0.031	5.95	0.001
	Height + age	0.24	−6.39	0.502
Off-leash trial	Age (y)	0.19	150.49	0.386
	Height (cm)	0.04	159.92	0.003
	Height + age	0.215	149.57	0.611
On-leash trial with investigator	Age (y)	0.102	50.95	0.159
	Height (cm)	0.080	52.37	0.078
	Height + age	0.165	47.81	0.763
On-leash trial with owner	Age (y)	0.127	56.19	< 0.001
	Height (cm)	0.328	41.24	0.023
	Height + age	0.421	33.74	0.977

^*Adjusted R² values indicate the proportion of variance in the outcome variable that is explained by the model, corrected for the number of predictor variables in the model.

^†Akaike weights indicate the relative probability of a given model being the best fitting among all models considered for a given outcome (eg, an Akaike weight of 0.977 for a given model was interpreted as meaning that there was a 97.7% probability it was the best fitting model among the other candidate models for a given outcome).

AIC = Akaike information criterion (measure of the quality of fit of each model, weighted by the number of factors in the model; smaller AIC values indicate a better fit).