手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| MRQAP Network Regression× | ソーシャルネットワーク分析× | |
|---|---|---|
| 分野≠ | Sociology | ネットワーク分析 |
| 系統≠ | Regression model | Machine learning |
| 提唱年≠ | 1988 (MRQAP); 2007 (double-semipartialing test) | 1934 (sociometry); 1994 (modern formalization) |
| 提唱者≠ | David Krackhardt; David Dekker, David Krackhardt & Tom Snijders | Moreno, J.L.; formalized by Wasserman & Faust |
| 種類≠ | Permutation-based multiple regression for dyadic (matrix) outcomes | Structural/relational analysis framework |
| 原典≠ | Krackhardt, D. (1988). Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Networks, 10(4), 359–381. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| 別名 | MRQAP, multiple regression QAP, Dekker double-semipartialing, QAP regression | SNA, network analysis, sociometric analysis, relational analysis |
| 関連≠ | 4 | 5 |
| 概要≠ | Multiple regression quadratic assignment procedure (MRQAP) extends QAP to the regression setting: it predicts a dependent relational matrix from several independent relational matrices on the same actors — for example, modeling who collaborates with whom as a function of who is co-located, who shares a department, and who has prior friendship. Coefficients are estimated by ordinary least squares on the vectorized matrices, but significance is assessed by permutation, because dyadic dependence invalidates the standard regression standard errors. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
| ScholarGateデータセット ↗ |
|
|