

Maximum Likelihood for Social Science by Michael D Ward
This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.-
Data Analysis Using Regression and Multilevel/Hierarchical Models
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Regression and Other Stories
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Counterfactuals and Causal Inference
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Essential Mathematics for Political and Social Research
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Multiverse Analysis
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Spatial Analysis for the Social Sciences
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Time Series Analysis for the Social Sciences
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Causal Mediation Analysis
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Statistical Modeling and Inference for Social Science
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Inferential Network Analysis
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Ecological Inference
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Event History Modeling
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Computational Social Science
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Formal Models of Domestic Politics
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Spatial Models of Parliamentary Voting
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Political Game Theory
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Maximum Likelihood for Social Science |
| Author | Michael D Ward |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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