I am running a glmmTMB to see if there is a significant difference in survival to the eyed egg stage (proportional data between 0 and 1) depending on what genetic male type was used (W, YY, or F1) to fertilize said eggs. I have female fish as my random effect as each female fish is a repeated measure. Below is my code and output:

model_glmm_Eyed <- glmmTMB(Eyed ~ Genetic + (1 | FemaleID), data = df, family = beta_family())

Conditional model: Estimate Std. Error z value Pr(>|z|) (Intercept) 1.4800 0.1991 7.432 1.07e-13 *** GeneticW 0.3309 0.2936 1.127 0.260 GeneticYY -0.4053 0.2472 -1.640 0.101 

emmeans(model_glmm_Eyed, pairwise ~ Genetic)

$emmeans Genetic emmean SE df asymp.LCL asymp.UCL F1 1.48 0.199 Inf 1.090 1.87 W 1.81 0.269 Inf 1.284 2.34 YY 1.07 0.203 Inf 0.676 1.47 Results are given on the logit (not the response) scale. Confidence level used: 0.95 $contrasts contrast estimate SE df z.ratio p.value F1 - W -0.331 0.294 Inf -1.127 0.4972 F1 - YY 0.405 0.247 Inf 1.640 0.2290 W - YY 0.736 0.299 Inf 2.460 0.0370 Results are given on the log odds ratio (not the response) scale. P value adjustment: tukey method for comparing a family of 3 estimates 

I have two questions regarding this analysis

1. Why am I not seeing results for males with genetic type F1? Are they getting absorbed in the intercept and being used as the baseline comparison? If so, how do I change this?

2. If I run post-hoc test, it shows me the pairwise comparison for all three male types. It shows a significant difference in the survival to the eyed stage between W and YY male types. I am confused about how to interpret this. When I visually look at my data it appears that there should be a difference in the survival to the eyed stage between W and YY males but it isn't appearing that way in the glmmTMB.

Any insight into why I might be getting these weird results or if I should run a different test would be greatly appreciated! :)