我创建了一个涉及两个变量的混合模型（一个连续，一个有三个级别），并且无法弄清楚如何计算它们各自的值。型号代码：
*Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) ['glmerMod']
Family: binomial ( logit )
Formula: active ~ tair * breeding + (1 | id/family)
Data: adata_sc
AIC BIC logLik deviance df.resid
1948.6 2000.1 -966.3 1932.6 4584
Scaled residuals:
Min 1Q Median 3Q Max
-24.1182 0.0720 0.1422 0.2636 1.5627
Random effects:
Groups Name Variance Std.Dev.
family:id (Intercept) 0.9841 0.992
id (Intercept) 1.1295 1.063
Number of obs: 4592, groups: family:id, 61; id, 44
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 8.34402 0.52641 15.851 <2e-16 ***
tair -0.22059 0.01669 -13.218 <2e-16 ***
breeding1 3.85335 1.92894 1.998 0.0458 *
breeding2 -1.38633 1.24099 -1.117 0.2639
tair:breeding1 -0.14504 0.06889 -2.105 0.0353 *
tair:breeding2 0.10345 0.04664 2.218 0.0266 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) tair brdng1 brdng2 tr:br1
tair -0.838
breeding1 -0.175 0.216
breeding2 -0.309 0.335 0.097
tair:brdng1 0.166 -0.230 -0.981 -0.097
tair:brdng2 0.327 -0.374 -0.100 -0.975 0.103*
从上面的输出中，我如何计算育种0的值（我假设是截距），还有tair：brdng0？