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Add a location-specific random intercept to the random-slope linear mixed model:Take the location effects, incubator slopes and individual errors to be mutually independent, with the original variances ${\tau }^2$ and ${\sigma }^2$. The random intercept models variation already present at hatching because of the origin of the eggs. Because larvae are subsequently assigned to incubators, location and incubator are crossed random effects, not automatically nested groups. The corresponding code isThe resulting covariance between two observations contains ${\omega }^2$ if they share a location and ${\tau }^2{t}_i{t}_k$ if they share an incubator. If the three named locations themselves are the only populations of interest, use a fixed location factor instead:Choosing between these interpretations depends on the inferential target; with only three locations, a location variance component will be weakly estimated.