Salīdzināt metodes

	Quadratic Assignment Procedure	Network Autocorrelation Model
Nozare	Sociology	Sociology
Saime	Process / pipeline	Regression model
Izcelsmes gads	1976 (QAP); 1988 (network application)	1980 (spatial/network models); 2002 (weight matrix)
Autors	Lawrence Hubert & James Schultz; David Krackhardt	Patrick Doreian; Roger Leenders (weight-matrix synthesis)
Tips	Permutation-based test of association between two matrices	Regression with an autoregressive term on a network weight matrix
Pirmavots	Krackhardt, D. (1988). Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Networks, 10(4), 359–381.	Leenders, R. Th. A. J. (2002). Modeling social influence through network autocorrelation: Constructing the weight matrix. Social Networks, 24(1), 21–47.
Citi nosaukumi	QAP correlation, QAP permutation test, matrix permutation test, Hubert-Schultz QAP	network effects model, social influence model, network disturbances model, autoregressive network model
Saistītās	4	4
Kopsavilkums	The quadratic assignment procedure (QAP) is a permutation-based method for testing the association between two relational matrices measured on the same set of actors — for example, whether who advises whom is correlated with who is friends with whom. Because the dyads in a network are not independent, ordinary correlation and regression give invalid p-values; QAP fixes this by comparing the observed matrix correlation to a reference distribution generated by randomly relabeling the nodes of one matrix many times.	The network autocorrelation model adapts spatial-econometric regression to social networks to estimate peer influence: it explains an actor's outcome — an attitude, behavior, or performance — as a function of their own covariates plus a weighted average of their network partners' outcomes. The autocorrelation parameter ρ captures the strength of social influence, and the network weight matrix W encodes who influences whom and how strongly.