| Records |
| Author |
Iacobucci, D.; Wasserman, S. |
| Title |
Social networks with two sets of actors |
Type |
Journal Article |
| Year |
1990 |
Publication |
Psychometrika |
Abbreviated Journal |
Psychometrika |
Volume  |
55 |
Issue |
4 |
Pages |
707-720 |
| Keywords |
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| Abstract |
Abstract Traditional network research analyzes relational ties within a single group of actors: the models presented in this paper involve relational ties exist beteen two distinct sets of actors. Statistical models for traditional networks in which relations are measured within a group simplify when modeling unidirectional relations measured between groups. The traditional paradigm results in a one-mode socionatrix; the network paradigm considered in this paper results in a two-mode socionatrix; A statistical model is presented, illustrated on a sample data set, and compared to its traditional counterpart. Extensions are discussed, including those that model multivariate relations simultaneously, and those that allow for the inclustion of attributes of the individuals in the group. |
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| Call Number |
Equine Behaviour @ team @ |
Serial |
5036 |
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| Author |
Wasserman, S. |
| Title |
Conformity of two sociometric relations |
Type |
Journal Article |
| Year |
1987 |
Publication |
Psychometrika |
Abbreviated Journal |
Psychometrika |
| Volume |
52 |
Issue |
1 |
Pages |
3-18 |
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| Abstract |
Abstract The problem of comparing two sociometric relations or measurements (A andB) recorded in distinct sociomatrices was originally discussed by Katz and Powell in the early 1950's and Hubert and Baker in the late 1970's. The problem is considered again using a probabilistic model designed specifically for discrete-valued network measurements. The model allows for the presence of various structural tendencies, such as reciprocity and differential popularity. A parameter that isolates the tendency for actors to choose other actors on both relations simultaneously is introduced, and estimated conditional on the presence of other parameters that reflect additional important network properties. The parameter is presented as a symmetric index but is also generalized to the predictive (A onB orB onA) situation. This approach to the problem is illustrated with the same data used by the earlier solutions, and the unique nature of the two relations in the data set (A = received choices,B = perceived choices), as it affects the modeling, is discussed. Significance tests for the parameter and related parameters are described, as well as an extension to more than two relations. |
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Equine Behaviour @ team @ |
Serial |
5027 |
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