Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2025


Data Analysis Using Regression and Multilevel/Hierarchical Models

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Andrew Gelman 作者
Cambridge University Press
譯者
2006-12-18 出版日期
648 頁數
USD 69.99 價格
Paperback
Analytical Methods for Social Research 叢書系列
9780521686891 圖書編碼

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 圖書標籤: 統計  數學  R  模型  statistics  統計學  機器學習  分析   


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發表於2025-02-16

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2025

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2025

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2025



Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 用戶評價

評分

Gelman還有本Bayesian Data Anlaysis也是領域標杆

評分

有點難讀啊。。沒有 Trochim寫的書通俗易懂

評分

有點難讀啊。。沒有 Trochim寫的書通俗易懂

評分

36-663 Hierarchical/Bayesian/Multilevel Models 開啓瞭新世界的大門

評分

Andrew Gelman Regression Hierarchical Models

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 著者簡介


Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 著者簡介


Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 圖書描述

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http://www.stat.columbia.edu/~gelman/arm/

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Data Analysis Using Regression and Multilevel/Hierarchical Models 在線電子書 讀後感

評分

A very good guide for HLM. Yet it should be noted that HLM here is based upon Bayesian methods. For data from survey, WinBugs frequently fails. >-<

評分

A very good guide for HLM. Yet it should be noted that HLM here is based upon Bayesian methods. For data from survey, WinBugs frequently fails. >-<

評分

A very good guide for HLM. Yet it should be noted that HLM here is based upon Bayesian methods. For data from survey, WinBugs frequently fails. >-<

評分

A very good guide for HLM. Yet it should be noted that HLM here is based upon Bayesian methods. For data from survey, WinBugs frequently fails. >-<

評分

A very good guide for HLM. Yet it should be noted that HLM here is based upon Bayesian methods. For data from survey, WinBugs frequently fails. >-<

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