Fox, J., 2008. Applied Regression Analysis and Generalized Linear Models, Sage. (Ch. 14, 15)
Eliason, 1993. Maximum Likelihood Estimation. Logic and Practice. Sage. (Ch. 1, 2)
Enders, C.K., 2010. Applied Missing Data Analysis. Guilford Press. (Ch. 3 – “An Introduction to Maximum Likelihood Estimation” offers a clear and intuitive discussion of ML)
King, G. 1998. Unifying Political Methodology. University of Michigan Press. (Ch. 1, 2 for a conceptual discussion of the inferential logic and the likelihood. Ch. 3, 4, 5 are optional, but recommended)
Long, J. Scott, 1997. Regression Models for Categorical and Limited Dependent Variables. Sage. (Ch. 5, 6, 8)
Books about R:
Adler, J., 2010. R in a Nutshell – A Desktop Quick Reference, O'Reilly. (A general introduction to R, we will take some examples from the book in the lab sessions)
Benoit, K., 1996. Democracies Really Are More Pacific (in general). Journal of Conflict Resolution.
Berry, W.D., DeMeritt, J.H.R., and Esarey, J., 2010. Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential? American Journal of Political Science.
Berry, W.D., Golder, M., and Milton, D., 2012. Improving Tests of Theories Positing Interaction. Journal of Politics.
Brambor, T., Clark, W. R., Golder, M., 2006. Understanding Interaction Models: Improving Empirical Analyses, Political Analysis.
Braumoeller, B.F., 2004. Hypothesis testing and multiplicative interaction terms. International Organization.
Fitzmaurice, G.M, Laird, N.M., Ware, J.H., 2004. Applied Longitudinal Analysis. Wiley. (Ch. 10 – “Review of Generalized Linear Models” is yet another reading explaining the logic of GLMs, like the Fox chapter. You don't have to read it all – definitely skip the SAS part – but it might be useful to hear the same concepts repeated in a different context)