Designed for students with prior knowledge in statistics and linear regression, this advanced course covers a wide variety of generalized linear models for categorical dependent variables that are commonly used in social science research, as well as such alternatives as quantile regression and robust regression. It also introduces selected models for complex data structures, including multilevel analysis, time-series analysis, and survival analysis. This course will address such model specifications as random- and fixed-effects and other topics. The course will be application oriented with special attention paid to estimation of the aforementioned models using social science datasets.