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Review your selected methods side by side; rows that differ are highlighted.
| Dyadic Analysis× | Relational Event Model× | |
|---|---|---|
| Field | Sociology | Sociology |
| Family | Regression model | Regression model |
| Year of origin≠ | 1981 | 2008 |
| Originator≠ | Holland & Leinhardt (p1); Kenny (Social Relations Model) | Carter T. Butts |
| Type≠ | Analysis of the dyad as the unit, decomposing relational effects | Event-history model for time-stamped relational events |
| Seminal source≠ | Holland, P. W., & Leinhardt, S. (1981). An exponential family of probability distributions for directed graphs. Journal of the American Statistical Association, 76(373), 33–50. DOI ↗ | Butts, C. T. (2008). A relational event framework for social action. Sociological Methodology, 38(1), 155–200. DOI ↗ |
| Aliases | dyad analysis, dyadic data analysis, social relations model, dyad census | REM, relational event framework, dynamic network event model, event-history network model |
| Related | 4 | 4 |
| Summary≠ | Dyadic analysis treats the dyad — the pair of actors and the relation between them — as the unit of analysis, separating the relational outcome into what each actor brings to all their relationships and what is unique to the specific pair. It spans the descriptive dyad census of network analysis and statistical frameworks such as Holland and Leinhardt's p1 model and Kenny's Social Relations Model, all of which respect the structural non-independence inherent in relational data. | The relational event model (REM), introduced by Carter Butts in 2008, analyzes streams of time-stamped interactions — emails, radio calls, messages, citations — as a continuous-time event-history process. Rather than treating a network as a static set of ties, it models the instantaneous rate at which any sender directs an action at any receiver as a function of the history of past events, letting researchers test how prior interaction shapes future interaction. |
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