Table 4.

Regression models. The tables show the significant regression models at a farm level (A) or individual level (B).

A. Farm level
Formula = PRCV ~ swIAV + PRRSV + PRRSV *swIAV + SOV + PCMV + PCV3 + PCV2 + PRCV*PCMV *SOV + PRCV *PCV3
	Estimate	Std. Error	t-value	Pr (>|t|)
Intercept	−0.276	0.198	−1.424	0.1612
PCMV	0.297	0.148	2.005	0.0509
SOV	0.358	0.138	2.592	0.0128
PCV3	0.342	0.144	2.369	0.0221
Multiple R-squared	0.432	F-statistic	5.005
Adjusted R-squared	0.346	p -value	< 0.001
Residual standard error	0.301
B. Individual results
Formula = PRCV ~ swIAV + PRRSV + PRRSV *swIAV + SOV + PCMV + PCV3 + PCV2 + PCMV *SOV + PCVM *PRRSV + SOV *PCV2
	Estimate	Std. Error	t -value	Pr (>|t|)
Intercept	0.531	0.280	1.932	0.059
PRRSV	−0.888	0.440	−2.016	0.049
Multiple R2	0.466	F-statistic	4.912
Adjusted R2	0.491	p -value	<0.001
Residual standard error	0.382
Formula = SOV ~ swIAV + PRRSV + PRRSV *swIAV + PCMV + PCV3 + PCV2 + PCMV *PRCV + PRCV *PRRSV
	Estimate	Std. Error	t -value	Pr (>|t|)
Intercept	0.658	0.164	3.990	<0.001
PCMV	−0.520	0.141	−3.679	<0.001
PCV2	0.474	0.167	2.829	0.006
Multiple R2	0.534	F-statistic	7.543
Adjusted R2	0.464	p -value	<0.001
Residual standard error	0.369
Formula = PCMV ~ swIAV + PRRSV + PRRSV *swIAV + SOV + PCV3 + PCV2 + SOV *PRCV + PRCV *PRRSV
	Estimate	Std. Error	t -value	Pr (>|t|)
Intercept	0.857	0.120	7.127	p < 0.001
PRCV	−0.332	0.124	−2.676	0.010
SOV	−0.454	0.122	−3.711	p < 0.001
Multiple R2	0.551	F-statistic	9.596
Adjusted R2	0.493	p- value	<0.001
Residual standard error	0.350