基本信息
- 原书名：Applied Regression Analysis and Other Multivariable Methods,Third Edition
- 原出版社： Thomson
编辑推荐
回归分析的理论与方法给出了分析各种领域变量关系的基本框架、在统计学、生物统计学、心理学、社会学、商业和工程等领域都有很多应用。
本书作者是生物统计学领域的专家，对回归分析十分熟悉。本书把重点放在实际研究中可能用到的实用技能上，适合作为高等院校研究生、高年级本科生的教材或教学参考书，同时也是卫生科学、社会科学、生物科学和行为科学等领域的专业人员及理论研究人员难得的参考书。
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内容简介
作译者
David．Kleinbaum，博土、埃默里大学流行病学系教授、主要研究方向为传染病传播定量分析。
Lawrence L．Kupper，生物统计学博士，北卡罗来纳大学公共健康学院生物统计学教授，主要研究方向为流行病学与环境健康中的生物统计。
Keith E．Mullerl北卡罗来纳大学公共健康学院生物统计学副教授。
Azhar Nizam，埃默里大学统计学硕士。
Lawrence L．Kupper，生物统计学博士，北卡罗来纳大学公共健康学院生物统计学教授，主要研究方向为流行病学与环境健康中的生物统计。
Keith E．Mullerl北卡罗来纳大学公共健康学院生物统计学副教授。
Azhar Nizam，埃默里大学统计学硕士。
目录
1 CONCEPTS AND EXAMPLES OF RESEARCH
1-1 Concepts 1
1-2 Examples 2
1-3 Concluding Remarks
References 6
2 CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS
2-1 Classification of Variables 7
2-2 Overlapping of Classification Schemes 11
2-3 Choice of Analysis 11
References 13
3 BASIC STATISTICS: A REVIEW 14
3-1 Preview 14
3-2 Descriptive Statistics 15
3-3 Random Variables and Distributions 16
3-4 Sampling Distributions of t, X2, and F 19
3-5 Statistical Inference: Estimation 21
3-6 Statistical Inference: Hypothesis Testing 24
3-7 Error Rates, Power, and Sample Size 28
Problems 30
References 33
1-1 Concepts 1
1-2 Examples 2
1-3 Concluding Remarks
References 6
2 CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS
2-1 Classification of Variables 7
2-2 Overlapping of Classification Schemes 11
2-3 Choice of Analysis 11
References 13
3 BASIC STATISTICS: A REVIEW 14
3-1 Preview 14
3-2 Descriptive Statistics 15
3-3 Random Variables and Distributions 16
3-4 Sampling Distributions of t, X2, and F 19
3-5 Statistical Inference: Estimation 21
3-6 Statistical Inference: Hypothesis Testing 24
3-7 Error Rates, Power, and Sample Size 28
Problems 30
References 33
前言
This is the second revision of our second-level statistics text, originally published in 1978 and first revised in 1987. As before, this text is intended primarily for advanced undergraduates, graduate students, and working professionals in the health, social, biological, and behavioral sciences who engage in applied research in their fields. The book may also provide professional statisticians with some new insights into the application of advanced statistical techniques to real-life problems.
We have attempted in this revision to retain the basic structure and flayor of the earlier two editions, while at the same time making changes to keep pace with current analytic practices and computer usage in applied research. Notable changes in the third edition, discussed in more
detail later, include a fourth author (Azhar Nizam), some reorganization of topics (in Chapters
22-24), expanded coverage of some conteot areas (such as logistic regression, in Chapter 23), a new chapter (Chapter 21 on repeated measures ANOVA), some new exercises for the reader, and
the integration of computer output (using the SAS package, primarily) into our discussion of
examples in the main body of the text and as a component of exercises given at the end of each
chapter. We have deleted from the previous editions chapters on discriminant analysis, factor
analysis, and categorical data analysis. This decision was based on our finding from a survey of
previons users of our text that these chapters were rarely used for classroom instruction and
were largely out of date. At the same time, the chapters we have added to replace this material
seem more relevant to current applied research practice.
In this revision, as in our previous versions, we emphasize the intuitive logic and assump-
tions that underlie the techniques covered, the purposes for which these techniques are de-
signed, the advantages and disadvantages of the techniques, and valid interpretations based on
the techniques. Although we describe the statistical calculations required for the techniques we
cover, we rely on computer output (even more so in this revision than previously) to provide the
results of such calculations, so the reader can concenuate oo how to apply a given technique
rather than on how to carry out the calculations. The mathematical formulas that we do present
require no more than simple algebraic manipulations. Proofs are of secondary importance and
are generally omitted. Neither calculus nor matrix algebra is used anywhere in the main text,
We have attempted in this revision to retain the basic structure and flayor of the earlier two editions, while at the same time making changes to keep pace with current analytic practices and computer usage in applied research. Notable changes in the third edition, discussed in more
detail later, include a fourth author (Azhar Nizam), some reorganization of topics (in Chapters
22-24), expanded coverage of some conteot areas (such as logistic regression, in Chapter 23), a new chapter (Chapter 21 on repeated measures ANOVA), some new exercises for the reader, and
the integration of computer output (using the SAS package, primarily) into our discussion of
examples in the main body of the text and as a component of exercises given at the end of each
chapter. We have deleted from the previous editions chapters on discriminant analysis, factor
analysis, and categorical data analysis. This decision was based on our finding from a survey of
previons users of our text that these chapters were rarely used for classroom instruction and
were largely out of date. At the same time, the chapters we have added to replace this material
seem more relevant to current applied research practice.
In this revision, as in our previous versions, we emphasize the intuitive logic and assump-
tions that underlie the techniques covered, the purposes for which these techniques are de-
signed, the advantages and disadvantages of the techniques, and valid interpretations based on
the techniques. Although we describe the statistical calculations required for the techniques we
cover, we rely on computer output (even more so in this revision than previously) to provide the
results of such calculations, so the reader can concenuate oo how to apply a given technique
rather than on how to carry out the calculations. The mathematical formulas that we do present
require no more than simple algebraic manipulations. Proofs are of secondary importance and
are generally omitted. Neither calculus nor matrix algebra is used anywhere in the main text,
