Table 1.

Logistic regression analyses of aphid survival.

treatment	regression equationa	β1b	β2b	β3b
controlSs	Y=−2.60−0.58SsWI−0.25SsNY+0.12SsAZ	p=0.0184; 95% CI: −1.06 to −0.10	p=0.3199; 95% CI: −0.74 to 0.24	p=0.6793; 95% CI: −0.44 to 0.67
day 2 heat shockSs	Y=−0.03+0.30SsWI+0.29SsNY+0.19SsAZ	p<0.0001; 95% CI: 0.15 to 0.45	p<0.0001; 95% CI: 0.15 to 0.43	p=0.0099; 95% CI: 0.04 to 0.33
day 6 heat shockSs	Y=0.90−0.28SsWI− 0.46SsNY−0.44SsAZ	p=0.0005; 95% CI: −0.44 to −0.12	p<0.0001; 95% CI: −0.61 to −0.30	p<0.0001; 95% CI: −0.60 to −0.27
controlHd/Ri	Y=−2.92−0.01Hd+0.58Ri	p=0.9652; 95% CI: −0.58 to 0.56	p=0.1544; 95% CI: −0.22 to 1.39	n.a.
day 2 heat shockHd/Ri	Y=0.77+0.29Hd−0.27Ri	p=0.0111; 95% CI: 0.07 to 0.52	p=0.0439; 95% CI: −0.53 to −0.01	n.a.

^aRegression equation is $Y={\beta }_0+{\beta }_1{\text{Ss}}^{\text{WI}}+{\beta }_2{\text{Ss}}^{\text{NY}}+{\beta }_3{\text{Ss}}^{\text{AZ}}$ (for S. symbiotica experiments) or (for H. defensa and R. insecticola experiments) $Y={\beta }_0+{\beta }_1\text{Hd}+{\beta }_2\text{Ri}$.

^bStatistics indicate whether β parameter estimates (representing the relative difference in the log odds of survival between infected and uninfected aphids) differed significantly from zero.