Table 3.

Coefficients From the Best-Fitting Logistic Regression Model Predicting Acute Musculoskeletal Injury^a

Step	Coefficients	Estimate	Standard Error	Z Value	P Value	Δ Deviance	Akaike Information Criterion
1	Intercept	−1.566	0.083	−18.86	<.001		1645.0
2	Point of instruction 1	−0.007	0.273	−0.02	.97	15.74	1635.3
	Point of instruction 2	0.727	0.291	2.49	.01
	Point of instruction 3	−0.156	0.288	0.54	.59
3	ln (Run.c)	1.172	0.398	2.94	<.01	14.60	1622.7
4	FitSum.c	−0.010	0.004	−2.49	.01	5.61	1619.0
5b	Age.c	0.045	0.019	2.35	.02	5.26	1615.8

Abbreviations: Age.c, centered mean of ages; Δ Deviance, change in deviance compared with the model in the previous step; FitSum.c, centered mean of the push-up and sit-up variables combined; ln (Run.c), centered mean of the natural logarithm of run time.

^aPoints of instruction 1 through 3 are simple contrast codes for the different programs of instruction (the intercept is thus equivalent to the grand mean). Null deviance = 1643.0 with 1787 degrees of freedom. Adding the interactions of ln (Run.c), FitSum.c, and Age.c in step 6 (not shown) did not improve the fit of the model.

^bDenotes the best-fitting model according to Akaike information criterion and Δ Deviance (P < .05).