Simple question but I can't find the answer anywhere online or in any of my texts. I think people assume you know, but I don't. What is an error structure, specifically for selecting the family distribution for a Generalized Linear Mixed Model? Is it the same as the distribution of your dependent variable?
I believe error structure in this respect is referring to the "element of randomness" in your model. For example, in least squares regression, we often assume that the error term of the model (i.e. residuals) follows a normal distribution
$$Y = \beta_0 + \beta_1X_1 + \epsilon, \:\:\: \epsilon \sim N(0,\sigma^2)$$
Without the error term, our model would be deterministic, or in other words for a given set of values for your independent variables, we could always obtain the exact value of the dependent variable, which we generally know is not the case.
So the error structure for a generalized regression model depends on the distribution of your dependent variable and the link function used to relate the independent variables to the dependent one. You say you're using a generalized mixed model, which probably has its own specific assumptions that lead to the nature of the error structure.
Moreover, while this question is basic in nature, it not quite so depending on the nature of the data and the question you are trying to answer.