Maximum Likelihood for Social Science: Strategies for Analysis (Analytical Methods for Social Research)
暫譯: 社會科學的最大似然估計:分析策略(社會研究的分析方法)
Michael D. Ward, John S. Ahlquist
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商品描述
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.
商品描述(中文翻譯)
本書提供了一個實用的最大似然法介紹,該方法在社會科學研究中被廣泛使用。Ward 和 Ahlquist 專注於在 R 語言中的應用計算,並使用來自實際已發表研究的真實社會科學數據。這本書在同類書籍中獨樹一幟,發展了基於模擬的模型評估和選擇工具,並與統計推斷相結合。本書涵蓋了類別數據的標準模型,以及計數、持續時間數據和處理缺失數據的策略。通過實例、數學和程式碼的練習,作者幫助讀者理解最大似然法有用的情境,並培養將數學陳述轉換為可執行計算機程式碼的技能。讀者不僅將學會使用基於似然的工具並生成有意義的解釋,還將為進一步學習更高級的統計技術奠定堅實的基礎。