000			01878nam a22002177a 4500
999			_c1777 _d1777
005			20220208133331.0
008			220208b ||||| |||| 00| 0 eng d
020			_a9781452288901
082			_a300.1518282 _bCAR
100			_aCarsey, Thomas M. _94694
245			_aMonte carlo simulation and resampling methods for social science
260			_bSage Publications, Inc. _aLos Angeles _c2014
300			_ax, 293 p.
365			_aUSD _b60.00
504			_aTable of content 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
520			_aDescription Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book illustrates 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 students 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.
650			_aMonte Carlo method _95215
650			_aSocial sciences--Methodology _91907
650			_aSocial sciences--Statistical methods _91897
942			_2ddc _cBK