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Basic Definitions and Overview | |
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Nonindependence | |
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Basic Definitions | |
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Distinguishability[superscript 1] | |
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Between-Dyads, Within-Dyads, and Mixed Variables | |
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Level of Measurement | |
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Idiographic and Nomothetic Analyses | |
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Dyadic Designs | |
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Data Organization | |
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Standard Design | |
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Other Designs | |
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A Database of Dyadic Studies | |
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Overview of the Book | |
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Summary and Conclusions | |
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The Measurement of Nonindependence | |
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Interval Level of Measurement | |
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Distinguishable Members | |
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Indistinguishable Members | |
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Categorical Measures | |
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Distinguishable Members | |
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Indistinguishable Members | |
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Consequences of Ignoring Nonindependence | |
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What Not to Do | |
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Power Considerations | |
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Power of the Test of r | |
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Power of Kappa | |
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Summary and Conclusions | |
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Analyzing Between- and Within-Dyads Independent Variables | |
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Interval Outcome Measures and Categorical Independent Variables | |
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One Between-Dyads Independent Variable | |
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Multiple Between-Dyads Independent Variables | |
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One Within-Dyads Independent Variable | |
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Multiple Within-Dyads Variables | |
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One Between-Dyads and One Within-Dyads Variable | |
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General Case | |
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Interval Outcome Measures and Interval Independent Variables | |
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Between-Dyads Independent Variable | |
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Within-Dyads Independent Variable | |
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General Case | |
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Categorical Outcome Variables | |
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Within-Dyads Independent Variable | |
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Between-Dyads Independent Variable | |
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Summary and Conclusions | |
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Using Multilevel Modeling to Study Dyads | |
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Mixed-Model ANOVA | |
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Multilevel-Model Equations | |
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Multilevel Modeling with Maximum Likelihood | |
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Adaptation of Multilevel Models to Dyadic Data | |
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Computing the Intraclass Correlation and Variance Explained with Multilevel Models | |
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Random Effects with Dyads | |
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Distinguishable Dyads | |
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Summary and Conclusions | |
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Using Structural Equation Modeling to Study Dyads | |
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Steps in SEM | |
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Specification | |
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Identification | |
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Estimation | |
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Testing | |
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Confirmatory Factor Analysis | |
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Path Analyses with Dyadic Data | |
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SEM for Dyads with Indistinguishable Members | |
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Model Fit and Model Comparisons | |
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Example | |
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Double-Entry Method | |
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Summary and Conclusions | |
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Tests of Correlational Structure and Differential Variance | |
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Distinguishable Dyads | |
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Equality of Variances | |
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Equality of Correlations | |
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Latent-Variable Correlations | |
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Omnibus Test of Distinguishability | |
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Categorical Variables | |
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Indistinguishable Dyads | |
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Correlations | |
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Latent Variable Correlations | |
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Comparing Intraclass Correlations | |
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Variances | |
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Summary and Conclusions | |
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Analyzing Mixed Independent Variables: The Actor-Partner Interdependence Model | |
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The Model | |
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Conceptual Interpretation of Actor and Partner Effects | |
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The Relative Size of Actor and Partner Effects | |
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Partner-Oriented Interaction Effects | |
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Actor-Partner Interactions | |
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Estimation of the APIM: Indistinguishable Dyad Members | |
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Pooled-Regression Method | |
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Estimating the APIM with Multilevel Analysis | |
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Estimating the APIM with SEM | |
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Estimation of the APIM: Distinguishable Dyads | |
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Pooled-Regression Method | |
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Multilevel Modeling | |
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Structural Equation Modeling | |
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Power and Effect Size Computation | |
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Specification Error in the APIM | |
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Summary and Conclusions | |
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Social Relations Designs with Indistinguishable Members | |
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The Basic Data Structures | |
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Round-Robin Design | |
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Block Design | |
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Block-Round-Robin Designs | |
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Other Designs | |
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Model | |
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The SRM Components | |
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Estimation of SRM Effects | |
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The SRM Variances | |
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The SRM Reciprocity Correlations | |
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Self-Actor and Self-Partner Correlations | |
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Actor and Partner Correlations with Individual-Difference Variables | |
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Dyadic Analysis of Relationship Effects | |
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Multivariate Correlations | |
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Details of an SRM Analysis | |
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Software | |
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Statistical Issues | |
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Significance Testing | |
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Power | |
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Model Assumptions | |
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Social Relations Analyses: An Example | |
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Summary and Conclusions | |
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Social Relations Designs with Roles | |
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SRM Studies of Family Relationships | |
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Design and Analysis of Studies | |
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The Model | |
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The Components | |
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Generalized and Dyadic Reciprocity | |
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Estimation of Variance in the SRM with Roles | |
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Family Subsystems | |
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Application of the SRM with Roles Using Confirmatory Factor Analysis | |
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The Four-Person Design | |
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The Base Model | |
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Illustration of the Four-Person Family Design | |
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Model Evaluation | |
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Parameter Estimates | |
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Respecifications of the Base Model | |
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The Three-Person Design | |
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Base Model | |
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Illustration | |
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Alternative Three-Person Models | |
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Multiple Perspectives on Family Relationships | |
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Means and Factor Score Estimation | |
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Constraints on the SRM Effects | |
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Estimation of SRM Effects for a Particular Family | |
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Power and Sample Size | |
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Summary and Conclusions | |
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One-with-Many Designs | |
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Design Issues | |
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Measuring Nonindependence | |
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Indistinguishable Partners | |
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Distinguishable Partners | |
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The Meaning of Nonindependence in the One-with-Many Design | |
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Univariate Analysis with Indistinguishable Partners | |
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Naive Analysis | |
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Between-Within Analysis | |
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Multilevel Analysis | |
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Univariate Estimation with Distinguishable Partners | |
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Repeated-Measures Analysis of Variance and MANOVA | |
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Multilevel Analysis | |
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Structural Equation Modeling | |
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The Reciprocal One-with-Many Design | |
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Indistinguishable Partners | |
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Distinguishable Partners | |
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Summary and Conclusions | |
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Social Network Analysis | |
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Definitions | |
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The Representation of a Network | |
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Network Measures | |
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Centrality | |
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Reciprocity | |
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Triads | |
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Subgroups | |
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Density | |
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The p[subscript 1] Model | |
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The Model | |
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Relation to the SRM | |
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Another Look at the Sampson Data | |
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Summary and Conclusions | |
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Dyadic Indexes | |
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Item Measurement Issues | |
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Measures of Profile Similarity | |
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Types | |
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Which Measure to Use? | |
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Mean and Variance of the Dyadic Index | |
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Average Measure | |
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Tests of Heterogeneity | |
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Stereotype Accuracy | |
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Differential Endorsement of the Stereotype | |
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Pseudo-Couple Analysis | |
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Idiographic versus Nomothetic Analysis | |
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Illustration | |
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Summary and Conclusions | |
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Over-Time Analyses: Interval Outcomes | |
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Cross-Lagged Regressions | |
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Analysis Model | |
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Computer Programs | |
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Example | |
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Over-Time Standard APIM | |
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Specification of Error Structure | |
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Measurement of the Causal Variable | |
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Example | |
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Growth-Curve Analysis | |
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Definition of Time Zero | |
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Functional Form | |
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Structural Equation Modeling | |
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Multilevel Modeling | |
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General Error Models | |
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Example | |
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Cross-Spectral Analysis | |
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Nonlinear Dynamic Modeling | |
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Summary and Conclusions | |
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Over-Time Analyses: Dichotomous Outcomes | |
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Sequential Analysis | |
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The Model | |
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Illustration | |
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Statistical Analysis of Sequential Data: Log-Linear Analysis | |
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Logit Model | |
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Significance Testing and Aggregation across Dyads | |
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The Assumption of Stationarity in Time-Series Analysis | |
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Beyond the Basic Analysis | |
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Statistical Analysis of Sequential Data: Multilevel Modeling | |
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Event-History Analysis | |
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Censored Scores | |
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Individual-Level Events | |
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Discrete Analysis | |
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Summary and Conclusions | |
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Concluding Comments | |
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Specialized Dyadic Models | |
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Mutual Influence | |
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Common-Fate Models | |
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Going Beyond the Dyad | |
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Triads | |
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Groups | |
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Network Autocorrelation | |
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Conceptual and Practical Issues | |
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The Meaning of Nonindependence | |
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Design and Measurement Issues in Dyadic Research | |
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Recruitment and Retention | |
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The Seven Deadly Sins of Dyadic Data Analysis | |
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The Last Word | |
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References | |
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Index | |