I'm very familiar with a lot of undergraduate to M.S.-level textbooks, as well as measure-theoretic textbooks, but I'm not at all knowledgeable about Ph.D. methods texts.
Namely, there's a Ph.D. methods course which has the following description:
Methods of constructing complex models including adding parameters to existing structures, incorporating stochastic processes and latent variables. Use of modified likelihood functions; quasi-likelihoods; profiles; composite likelihoods. Asymptotic normality as a basis of inference; Godambe information. Sample reuse; block bootstrap; resampling with dependence. Simulation for model assessment. Issues in Bayesian analysis.
I would really like to start learning this information. What is/are suitable textbook(s) which cover the material above?