# 2005 StatisticalModels

- (Freedman, 2005a) ⇒ David A. Freedman. (2005). “Statistical Models: theory and practice." Cambridge University Press. ISBN:0521854830

**Subject Headings:** Statistical Model Family, Likelihood Function, Latent Variable, Covariance Matrix.

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### Book Overview

Explaining the things you need to know in order to read empirical papers in the social and health sciences, as well as techniques needed to build personal statistical models, this user-friendly volume includes background material on study design, bivariate regression, and matrix algebra. To develop technique, Freedman also includes computer labs, with sample computer programs, and illustrates the principles and pitfalls of modeling. The book is rich in exercises with answers. Target audiences include undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

### Table of Contents

1 Observational Studies and Experiments 1.1 Introduction 1 1.2 The HIP trial 4 1.3 Snow on cholera 6 1.4 Yule on the causes of poverty 9 Exercise set A 13 1.5 End notes 14

2 The Regression Line 2.1 Introduction 18 2.2 The regression line 18 2.3 Hooke’s law 22 Exercise set A 23 2.4 Complexities 23 2.5 Simple vs multiple regression 25 Exercise set B 26 2.6 End notes 28

3 Matrix Algebra 3.1 Introduction 29 Exercise set A 30 3.2 Determinants and inverses 31 Exercise set B 33 3.3 Random vectors 35 Exercise set C 35 3.4 Positive definite matrices 36 Exercise set D 37 3.5 The normal distribution 38 Exercise set E 39 3.6 If you want a book on matrix algebra 40

4 Multiple Regression 4.1 Introduction 41 Exercise set A 44 4.2 Standard errors 45 Things we don’t need 48 Exercise set B 49 4.3 Explained variance in multiple regression 50 Association or causation? 52 4.4 Generalized least squares 52 4.5 Examples on GLS 55 Exercise set C 56 4.6 What happens to OLS if the assumptions break down? 57 4.7 Normal theory 57 Statistical significance 60 Exercise set D 60 4.8 The F-test 61 “The” F-test in applied work 63 Exercise set E 63 4.9 Data snooping 64 Exercise set F 65 4.10 Discussion questions 65 4.11 End notes 72

5 Path Models 5.1 Stratification 75 Exercise set A 80 5.2 Hooke’s law revisited 81 Exercise set B 82 5.3 Political repression during the McCarthy era 82 Exercise set C 84 5.4 Inferring causation by regression 85 Exercise set D 87 5.5 Response schedules for path diagrams 88 Selection vs intervention 95 Structural equations and stable parameters 95 Ambiguity in notation 96 Exercise set E 96 5.6 Dummy variables 97 Types of variables 98 5.7 Discussion questions 99 5.8 End notes 106

6 Maximum Likelihood 6.1 Introduction 109 Exercise set A 113 6.2 Probit models 114 Why not regression? 117 The latent-variable formulation 117 Exercise set B 118 Identification vs estimation 119 What if the Ui are N(µ, s2)? 120 Exercise set C 120 6.3 Logit models 121 Exercise set D 122 6.4 The effect of Catholic schools 123 More on table 3 126 Latent variables 126 Response schedules 127 The second equation 128 Mechanics: bivariate probit 130 Why a model rather than a cross-tab? 132 Interactions 132 More on the second equation 133 Exercise set E 133 6.5 Discussion questions 135 6.6 End notes 142

7 The Bootstrap 7.1 Introduction 148 Exercise set A 159 7.2 Bootstrapping a model for energy demand 160 Exercise set B 166 7.3 End notes 167

8 Simultaneous Equations 8.1 Introduction 169 Exercise set A 174 8.2 Instrumental variables 174 Exercise set B 177 8.3 Estimating the butter model 177 Exercise set C 178 8.4 What are the two stages? 178 Invariance assumptions 179 8.5 A social-science example: education and fertility 180 More on Rindfuss et al 184 8.6 Covariates 184 8.7 Linear probability models 185 The assumptions 186 The questions 188 Exercise set D 188 8.8 More on IVLS 189 Some technical issues 189 Exercise set E 191 Simulations to illustrate IVLS 191 Further reading on econometric technique 192 8.9 Issues in statistical modeling 192 8.10 Critical literature 195 Response schedules 199 8.11 Evaluating the models in chapters 6–8 200 8.12 Summing up 200,

Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
---|---|---|---|---|---|---|---|---|---|---|

2005 StatisticalModels | David A. Freedman | Statistical Models: theory and practice | http://books.google.com/books?id=TUbKc9o4az4C | 2005 |

Facts about "2005 StatisticalModels"

Author | David A. Freedman + |

title | Statistical Models: theory and practice + |

titleUrl | http://books.google.com/books?id=TUbKc9o4az4C + |

year | 2005 + |