Dyadic data analysis
著者
書誌事項
Dyadic data analysis
(Methodology in the social sciences)
Guilford Press, c2006
- : hardcover
大学図書館所蔵 全22件
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  福島
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  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
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  広島
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  徳島
  香川
  愛媛
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  福岡
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注記
Includes bibliographical references (p. 427-443) and index
内容説明・目次
内容説明
Interpersonal phenomena such as attachment, conflict, person perception, helping, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, or parent-child, teacher-student, or doctor-patient pairs, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model the statistical interdependence that can exist between partners. The companion website provides clarifications, elaborations, corrections, and data and files for each chapter.
目次
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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