Table 4. GLMM results.
Dependent variable | Effect | df | Wald X2 | P-value |
---|---|---|---|---|
Mean FGM concentration | transfer | 1 | 0.097 | 0.755 |
age | 1 | 2.476 | 0.116 | |
rear | 1 | 1.002 | 0.317 | |
mean | 1 | 4.521 | 0.033 | |
Cutoff (2.5 SD of mean FGM concentration) | transfer | 1 | 0.316 | 0.574 |
age | 1 | 1.982 | 0.159 | |
rear | 1 | 0.935 | 0.334 | |
sd2.5 | 1 | 2.055 | 0.152 | |
Baseline | transfer | 1 | 0.266 | 0.606 |
age | 1 | 1.95 | 0.163 | |
rear | 1 | 1.041 | 0.308 | |
base_mean | 1 | 2.515 | 0.113 | |
Peak mean | transfer | 1 | 0.026 | 0.871 |
age | 1 | 1.9 | 0.168 | |
rear | 1 | 1.105 | 0.293 | |
peak_mean | 1 | 6.598 | 0.01 | |
Proportion of peaks | transfer | 1 | 0.078 | 0.781 |
age | 1 | 0.747 | 0.387 | |
rear | 1 | 0.736 | 0.391 | |
pop | 1 | 1.892 | 0.169 |
Bold typing indicates statistically significant effects. In each model, breeding success was the dependent variable and the predictor was changed to a different cortisol measure with transfer, age and rearing as confounding variables.