Applied Longitudinal Data Analysis 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Applied Longitudinal Data Analysis

简体网页||繁体网页
Judith D. Singer 作者
Oxford University Press, USA
译者
2003-03-19 出版日期
644 页数
USD 69.50 价格
Hardcover
丛书系列
9780195152968 图书编码

Applied Longitudinal Data Analysis 在线电子书 图书标签: 统计  统计学  统计分析  HLM  追踪数据分析  计量  statistics  Stat   


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发表于2024-11-26


Applied Longitudinal Data Analysis 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied Longitudinal Data Analysis 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied Longitudinal Data Analysis 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



Applied Longitudinal Data Analysis 在线电子书 用户评价

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: O212.7/S617

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Do not use it unless your instructor choose it. You won't get the idea of longitudinal data analysis because the writing style of this book is way too condense. For learning fixed and random effect models, go directly to princeton university online resources.

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I never thought that I would use beautiful to describe a book on statistics. But this book IS beautifully written.

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好看好看,上完一般意义上的HLM简直是自学multilevel growth curve 的最佳课本。

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好看好看,上完一般意义上的HLM简直是自学multilevel growth curve 的最佳课本。

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Applied Longitudinal Data Analysis 在线电子书 图书描述

Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models.

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