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Monte Carlo Simulation and Resampling Methods for Social Science

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Monte Carlo Simulation and Resampling Methods for Social Science by Thomas M. Carsey
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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.
SAGE Publications; August 2013
304 pages; ISBN 9781483324920
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Title: Monte Carlo Simulation and Resampling Methods for Social Science
Author: Thomas M. Carsey; Jeffrey J. Harden
 
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Excellent textbook
This is a must-read for those interested in Monte Carlo simulation, in the context of linear and non-linear econometric models, and for those who want to improve their R-programming skills.
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ISBNs
9781452288901
9781483313474
9781483324920