1 Preliminaries -- 1.1 Independence and Conditional Independence -- 1.2 Undirected Graphs -- 1.3 Data, Models, and Graphs -- 1.4 Simpson's Paradox -- 1.5 Overview of the Book -- 2 Discrete Models -- 2.1 Three-Way Tables -- 2.2 Multi-Way Tables -- 3 Continuous Models -- 3.1 Graphical Gaussian Models -- 3.2 Regression Models -- 4 Mixed Models -- 4.1 Hierarchical Interaction Models -- 4.2 Breaking Models into Smaller Ones -- 4.3 Mean Linearity -- 4.4 Decomposable Models -- 4.5 CG-Regression Models -- 4.6 Incomplete Data -- 4.7 Discriminant Analysis -- 5 Hypothesis Testing -- 5.1 An Overview -- 5.2 X2-Tests -- 5.3 F-Tests -- 5.4 Exact Conditional Tests -- 5.5 Deviance-Based Tests -- 5.6 Permutation F-Test -- 5.7 Pearson x2-Test -- 5.8 Fisher's Exact Test -- 5.9 Rank Tests -- 5.10 Wilcoxon Test -- 5.11 Kruskal-Wallis Test -- 5.12 Jonckheere-Terpstra Test -- 5.13 Tests for Variance Homogeneity -- 5.14 Tests for Equality of Means Given Homogeneity -- 5.15 Hotelling's T2 -- 6 Model Selection and Criticism -- 6.1 Stepwise Selection -- 6.2 The EH-Procedure -- 6.3 Selection Using Information Criteria -- 6.4 Comparison of the Methods -- 6.5 Box-Cox Transformations -- 6.6 Residual Analysis -- 6.7 Dichotomization -- 7 Directed Graphs and Their Models -- 7.1 Directed Acyclic Graphs -- 7.2 Chain Graphs -- 7.3 Local Independence Graphs -- 7.4 Covariance Graphs -- 7.5 Chain Graphs with Alternative Markov Properties -- 7.6 Reciprocal Graphs -- 8 Causal Inference -- 8.1 Philosophical Aspects -- 8.2 Rubin's Causal Model -- 8.3 Pearl's Causal Graphs -- 8.4 Discussion -- A The MINI Command Language -- A.1 Introduction -- A.2 Declaring Variables -- A.3 Undirected Models -- A.3.1 Deleting Edges -- A.3.2 Adding Edges -- A.3.3 Other Model-Changing Commands -- A.3.4 Model Properties -- A.4 Block-Recursive Models -- A.4.1 Defining the Block Structure -- A.4.2 Block Mode -- A.4.3 Defining Block-Recursive Models -- A.4.4 Working with Component Models -- A.5 Reading and Manipulating Data -- A.5.1 Reading Casewise Data -- A.5.2 Reading Counts, Means, and Covariances -- A.5.3 Transforming Data -- A.5.4 Restricting Observations -- A.5.5 Generating Raw Data -- A.5.6 Deleting Variables -- A.6 Estimation -- A.6.1 Undirected Models (Complete Data) -- A.6.2 Undirected Models (Missing Data) -- A.6.3 CG-Regression Models -- A.7 Hypothesis Testing -- A.7.1 x2-Tests -- A.7.2 Test of Homogeneity -- A.7.3 F-Tests -- A.7.4 Edge Deletion Tests -- A.7.5 Edge Deletion F-Tests -- A.7.6 Exact Tests -- A.7.7 Symmetry Tests -- A.7.8 Randomisation Tests -- A.8 Model Selection -- A.8.1 Stepwise Selection -- A.8.2 The EH-Procedure -- A.8.3 Selection Using Information Criteria -- A.9 The Box-Cox Transformation -- A.10 Residuals -- A.11 Discriminant Analysis -- A.12 Utilities -- A.12.1 File Input -- A.12.2 The Workspace -- A.12.3 Printing Information -- A.12.4 Displaying Parameter Estimates -- A.12.5 Displaying Summary Statistics -- A.12.6 Setting the Maximum Model -- A.12.7 Fixing Variables -- A.12.8 Macros -- B Implementation Specifics of MB'! -- B.1 Calling MIM -- B.2 The Main Menu -- B.3 Entering Commands and Navigating the Work Area -- B.4 The Built-In Editor -- B.5 Interactive Data Entry -- B.6 Independence Graphs -- B.7 Simple Data Graphics -- B.7.1 Scatter Plots -- B.7.2 Histograms -- B.7.3 Box Plots -- B.8 Graphics Export Formats -- B.9 Direct Database Access -- B.10 Program Intercommunication -- C On Multivariate Symmetry -- D On the Estimation Algorithms -- D.1 The MIPS Algorithm -- D.1.1 Notation -- D.1.2 The Likelihood Equations -- D.1.3 The General Algorithm -- D.1.4 The A-Collapsible Variant -- D.1.5 The Mean Linear Variant -- D.1.6 The Q-Equivalent Variant -- D.1.7 The Step-Halving Variant -- D.2 The EM-Algorithm -- D.3 The ME-Algorithm -- References.