Repeated within family measurements in an lmer I'm trying to model in R, how lizard head size (Continuous) can be predicted by mass (Continuous), hatch time (Factor: Early vs Late), and Clutch mass (Continuous), with Family as a random factor. An example model would be:
model <- lmer(log(Head) ~ log(Mass) + Hatch_time + Clutch_mass + 
                          (1|Family), data = dat)

However, there is a problem. My `Clutch_mass' continuous variable is repeated within each family, as within family clutch mass is the same. There are 12 individuals from each family, meaning each clutch mass value is repeated 12 times. How could I include this variable in my model, whilst avoiding replication?

As @AdamO said in comments, having a predictor variable that's the same for all members of a group isn't a problem in a mixed model "unless doing so perfectly explains all the residual variation," which isn't likely in biological studies. To that extent, your "original model is potentially fine."
That doesn't, however, remove the need to evaluate whether you have the proper functional form for your model. For example, I wonder why you are modeling log(Head) as a linear function of Clutch_mass (presumably the sum of all Mass values for a clutch) while you model it as a function of the individual's log(Mass). More generally, flexible fits of continuous predictor variables with regression splines or generalized additive models can be more useful unless there's a theoretical reason to expect that a log or other transformation is appropriate.
