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 qin repeated samples, q 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.Monte Carlo simulation is a valuable tool for everyone from students just beginning to learn statistical methods to applied researchers ... the manual under the aHelpa menu 1This is particularly evident in the social sciences, where simulation has been used to evaluate and ... Grizzle, 1996; Green aamp; Vavreck, 2008; Harden aamp; Desmarais, 2011), evaluate substantive theory (e.g., Adler, 2000; Adler aamp; Lapinski, anbsp;...
|Title||:||Monte Carlo Simulation and Resampling Methods for Social Science|
|Author||:||Thomas M. Carsey, Jeffrey J. Harden|
|Publisher||:||SAGE Publications - 2013-08-06|