So sánh phương pháp

	Thurstone Scaling	Mô hình Bradley-Terry	Phân tích Tương ứng
Lĩnh vực	Thống kê	Ra quyết định	Thống kê
Họ	Latent structure	Regression model	Latent structure
Năm ra đời	1927	1952	1984
Người khởi xướng	Louis Leon Thurstone	Ralph Bradley & Milton Terry	Jean-Paul Benzécri; Michael Greenacre
Loại	Psychological measurement and attitude scaling model	Probabilistic paired comparison model	Exploratory multivariate technique for categorical data
Công trình gốc	Thurstone, L. L. (1927). A law of comparative judgment. Psychological Review, 34(4), 273–286.	Bradley, R. A., & Terry, M. E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(3/4), 324–345.	Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2
Tên gọi khác	Law of Comparative Judgment, Thurstone's Method of Equal-Appearing Intervals, Case V Scaling, Thurstone Ölçekleme	BT Model, Bradley-Terry-Luce Model, Paired Comparison Model, İkili Karşılaştırma Modeli	CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi
Liên quan	2	3	2
Tóm tắt	Thurstone Scaling, formally the Law of Comparative Judgment, is a psychometric model introduced by Louis Leon Thurstone in 1927 for deriving interval-level scale values from pairwise comparison data. By assuming that each stimulus evokes a normally distributed discriminal process on a psychological continuum, the method converts proportions of preference judgments into z-scores and recovers the latent positions of stimuli, enabling rigorous attitude and preference measurement.	The Bradley-Terry model is a probabilistic model for paired comparisons that assigns a latent strength parameter to each item and predicts the probability that one item beats another in a head-to-head contest. Introduced by Ralph A. Bradley and Milton E. Terry in 1952, it provides a principled statistical framework for ranking items from pairwise preference data, including incomplete comparison designs where not every pair is directly observed.	Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations.