Employing the highly dynamic statistical software, R, to support a number of functionalities that are not readily found together, if at all, in other survey analysis software, the author has created a software package for analyzing data from complex surveys. This popular software has been thoroughly revised for the Second Edition to reflect the new research and improvements in rank testing, model selection criteria and likelihood-ratio tests for regression models, quantile estimation, estimation of small probabilities, and survival analysis. Bridging the model-based and design-based divide, the new edition provides additional coverage of the basic topics in survey sampling, such as simple random sampling, stratified sampling, cluster sampling, and regression analysis, as well as the most up-to-date modern methodology in complex survey research to provide readers with a comprehensive understanding of the survey analysis field. The Second Edition features numerous examples and exercises based on large-scale real-world national surveys datasets, such as the National Health and Nutrition Examination Survey, the National Health Interview Survey, CPS, and British Household Survey; medical cohort studies; and artificial samples from county-level data from U.S. presidential elections. The new edition has a unique section in Chapter 1 and two appendices on analysis of very large surveys, focusing on the American Community Survey, which is an ongoing U.S. Census Bureau survey that samples a percentage of the population each year. The book remains unique from existing literature by placing emphasis on calibration, replication, two-phase sampling, graphical methods for survey data, and common concerns of survey analysts, such as when to use weights in regression models.