Dyadic Data Analysis

Dyadic Data Analysis

by David A. Kenny, Deborah A. Kashy, William L. Cook
     
 

ISBN-10: 1572309865

ISBN-13: 9781572309869

Pub. Date: 08/14/2006

Publisher: Guilford Publications, Inc.

"This is a well-written and thoroughgoing discussion of issues and approaches in the analysis of dyadic data, written by leaders in the field. Dyadic data is a commonly found data structure in social psychology and social relations research. The authors describe and demonstrate several statistical methods, including multilevel and structural equation modeling

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Overview

"This is a well-written and thoroughgoing discussion of issues and approaches in the analysis of dyadic data, written by leaders in the field. Dyadic data is a commonly found data structure in social psychology and social relations research. The authors describe and demonstrate several statistical methods, including multilevel and structural equation modeling approaches. The book would be appropriate for advanced undergraduate social psychology methods classes, as well as graduate seminars. I strongly recommend this text to every social relations and social psychology researcher. I expect it will soon become a widely cited classic."—Bruno D. Zumbo, University of British Columbia

Product Details

ISBN-13:
9781572309869
Publisher:
Guilford Publications, Inc.
Publication date:
08/14/2006
Series:
Methodology In The Social Sciences Series
Edition description:
1ST
Pages:
458
Sales rank:
1,416,998
Product dimensions:
6.00(w) x 9.00(h) x (d)

Table of Contents

1. Basic Definitions and Overview
 
Nonindependence
Basic Definitions
Data Organization
A Database of Dyadic Studies

2. The Measurement of Nonindependence

Interval Level of Measurement
Categorical Measures
Consequences of Ignoring Nonindependence
What Not to Do
Power Considerations

3. Analyzing Between- and Within-Dyads Independent Variables

Interval Outcome Measures and Categorical Independent Variables
Interval Outcome Measures and Interval Independent Variables
Categorical Outcome Variables

4. Using Multilevel Modeling to Study Dyads

Mixed-Model ANOVA
Multilevel-Model Equations
Multilevel Modeling with Maximum Likelihood
Adaptation of Multilevel Models to Dyadic Data

5. Using Structural Equation Modeling to Study Dyads

Steps in SEM
Confirmatory Factor Analysis
Path Analyses with Dyadic Data
SEM for Dyads with Indistinguishable Members

6. Tests of Correlational Structure and Differential Variance

Distinguishable Dyads
Indistinguishable Dyads

7. Analyzing Mixed Independent Variables: The Actor–Partner Interdependence Model

The Model
Conceptual Interpretation of Actor and Partner Effects
Estimation of the APIM: Indistinguishable Dyad Members
Estimation of the APIM: Distinguishable Dyads
Power and Effect Size Computation
Specification Error in the APIM

8. Social Relations Designs with Indistinguishable Members

The Basic Data Structures
Model
Details of an SRM Analysis
Model
Social Relations Analyses: An Example

9. Social Relations Designs with Roles

SRM Studies of Family Relationships
Design and Analysis of Studies
The Model
Application of the SRM with Roles Using Confirmatory Factor Analysis
The Four-Person Design
Illustration of the Four-Person Family Design
The Three-Person Design
Multiple Perspectives on Family Relationships
Means and Factor Score Estimation
Power and Sample Size

10. One-with-Many Designs

Design Issues

Measuring Nonindependence
The Meaning of Nonindependence in the One-with-Many Design
Univariate Analysis with Indistinguishable Partners
Univariate Estimation with Distinguishable Partners
The Reciprocal One-with-Many Design

11. Social Network Analysis

Definitions
The Representation of a Network
Network Measures
The p1

12. Dyadic Indexes

Item Measurement Issues
Measures of Profile Similarity
Mean and Variance of the Dyadic Index
Stereotype Accuracy
Differential Endorsement of the Stereotype
Pseudo-Couple Analysis
Idiographic versus Nomothetic Analysis
Illustration

13. Over-Time Analyses: Interval Outcomes

Cross-Lagged Regressions
Over-Time Standard APIM
Growth-Curve Analysis
Cross-Spectral Analysis
Nonlinear Dynamic Modeling

14. Over-Time Analyses: Dichotomous Outcomes

Sequential Analysis
Statistical Analysis of Sequential Data: Log-Linear Analysis
Statistical Analysis of Sequential Data: Multilevel Modeling
Event-History Analysis

15. Concluding Comments

Specialized Dyadic Models
Going Beyond the Dyad
Conceptual and Practical Issues
The Seven Deadly Sins of Dyadic Data Analysis
The Last Word

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