ScholarGate
Trợ lý

So sánh phương pháp

Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.

MRQAP Network Regression×Dyadic Analysis×
Lĩnh vựcSociologySociology
HọRegression modelRegression model
Năm ra đời1988 (MRQAP); 2007 (double-semipartialing test)1981
Người khởi xướngDavid Krackhardt; David Dekker, David Krackhardt & Tom SnijdersHolland & Leinhardt (p1); Kenny (Social Relations Model)
LoạiPermutation-based multiple regression for dyadic (matrix) outcomesAnalysis of the dyad as the unit, decomposing relational effects
Công trình gốcKrackhardt, D. (1988). Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Networks, 10(4), 359–381. DOI ↗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 ↗
Tên gọi khácMRQAP, multiple regression QAP, Dekker double-semipartialing, QAP regressiondyad analysis, dyadic data analysis, social relations model, dyad census
Liên quan44
Tóm tắtMultiple 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.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.
ScholarGateBộ dữ liệu
  1. v1
  2. 2 Nguồn tài liệu
  3. PUBLISHED
  1. v1
  2. 2 Nguồn tài liệu
  3. PUBLISHED

Đến trang tìm kiếm Tải xuống bản trình chiếu

ScholarGateSo sánh phương pháp: MRQAP Network Regression · Dyadic Analysis. Truy cập ngày 2026-06-24 từ https://scholargate.app/vi/compare