Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book 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.
Зміст
1. Introduction
2. Probability
3. Introduction to R
4. Random Number Generation
5 .Statistical Simulation of the Linear Model
6. Simulating Generalized Linear Models
7. Testing Theory Using Simulation
8. Resampling Methods
9. Other Simulation-Based Methods
10. Final Thoughts
Про автора
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. He received his Ph D in political science from the University of North Carolina at Chapel Hill. His methodology interests include model selection, robust regression methods, multilevel data, and the use of Monte Carlo simulation to better understand issues that arise in applied analysis. His research agenda in American politics focuses on political representation, mass/elite linkages, and state politics. Harden has published articles in Political Analysis, Sociological Methods & Research, Legislative Studies Quarterly, State Politics & Policy Quarterly, and Public Choice.
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