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Log-Linear Mobility Model×Goodman Association Model×
ГалузьSociologySociology
РодинаRegression modelRegression model
Рік появи1970s1979
Автор методуLeo Goodman; Robert HauserLeo A. Goodman
ТипLog-linear / Poisson model for cell counts in mobility tablesLog-multiplicative model for association in ordered contingency tables
Основоположне джерелоHauser, R. M. (1978). A structural model of the mobility table. Social Forces, 56(3), 919–953. DOI ↗Goodman, L. A. (1979). Simple models for the analysis of association in cross-classifications having ordered categories. Journal of the American Statistical Association, 74(367), 537–552. DOI ↗
Інші назвиlog-linear model for mobility, topological mobility model, quasi-independence model, levels modelRC association model, row-column association model, log-multiplicative model, RC(M) model
Пов'язані55
ПідсумокLog-linear mobility models analyze an origin-by-destination mobility table by modeling the logarithm of its expected cell counts as a sum of terms: separate effects for the origin and destination marginals plus interaction terms that capture the origin–destination association. By specifying that association parametrically — through diagonal, level, or scaled terms — these models test precise hypotheses about the structure of social fluidity independent of the changing sizes of classes.Goodman's association models, especially the row-column (RC) model, analyze the association in a two-way contingency table by representing it as a product of estimated scores for the row categories and scores for the column categories, scaled by an intrinsic association parameter. Introduced by Leo Goodman in 1979, they are log-multiplicative rather than purely log-linear, allowing ordered categories to be assigned data-driven scores and the strength of association to be summarized in a single, interpretable coefficient.
ScholarGateНабір даних
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  3. PUBLISHED
  1. v1
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ScholarGateПорівняння методів: Log-Linear Mobility Model · Goodman Association Model. Отримано 2026-06-24 з https://scholargate.app/uk/compare