Variations on the Common Fate Model for Dyadic Analysis
Recommendations for Model Selection
Bibliographic Data
| ID | 12524906 |
|---|---|
| Authors | Robert E Wickham (0000-0002-0132-6235, Department of Psychological Sciences Northern Arizona University Flagstaff Arizona USA), Robert Wickham (corresponding author) |
| Year | 2025 |
| Volume | 32 |
| Issue | 4 |
| Publication date | 2025-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Personal Relationships (JOURNAL) |
| Journal identifiers | ISSN: 1350-4126 • E-ISSN: 1475-6811 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/pere.70049 |
| OpenAlex | W7116947125 |
| Language | EN |
| References cited | 25 |
Interest in two‐person interaction scenarios has increased substantially over the prior decades, and a multitude of analytic approaches have been developed to accommodate these designs. Although the Actor‐Partner model has received the most attention, useful variations on the Common Fate Model (CFM) for dyadic analysis have emerged. Specifically, the Between‐Within CFM (BW‐CFM) has arisen as a compelling approach, as it produces a Dyad‐level coefficient representing the between‐dyads effect, within‐dyad coefficients at the Person‐level, and allows for the estimation of contextual effects. Although the basic configuration of the BW‐CFM is well understood, several configurations of the model that accommodate different patterns of Person‐level relationships remain unexplored. The present work examines specifications of the BW‐CFM that are likely to arise in real‐world analysis, describes a procedure for selecting the optimal specification of Person‐level parameters and illustrates the application of a procedure for quantifying the degree of model selection uncertainty
Estimation · Model selection · Model validation · Multitude · Selection (genetic algorithm · Specification · Work (physics · Mental Health Research Topics · Personality Traits and Psychology · Social Power and Status Dynamics
The common fate model for dyadic data
A new look at the statistical model identification
Species Richness of Parasite Assemblages
Estimating the Dimension of a Model
Understanding Dyad, Person, and Contextual Effects in Dyadic Analysis
The Effect of Different Forms of Centering in Hierarchical Linear Models
Models of Non-Independence in Dyadic Research
| Highly cited | No |
|---|