By Thomas M. Carsey and Jeffrey J. Harden
Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way.
Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results.
The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project.
The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
Thomas M. Carsey is the Thomas J. Pearsall Distinguished Professor of Political Science and Director of the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. Jeffrey J. Harden is an assistant professor in the Department of Political Science at the University of Colorado, Boulder specializing in political methodology and American politics.
Publication date: 2015