পদ্ধতির তুলনা করুন

	আনফোল্ডিং মডেল	কোরস্পন্ডেন্স অ্যানালাইসিস
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Latent structure	Latent structure
উদ্ভবের বছর	2005	1984
প্রবর্তক	Clyde Coombs; Borg & Groenen	Jean-Paul Benzécri; Michael Greenacre
ধরন	Preference scaling via ideal-point representation	Exploratory multivariate technique for categorical data
মৌলিক উৎস	Borg, I., & Groenen, P. J. F. (2005). Modern Multidimensional Scaling: Theory and Applications (2nd ed.). Springer. ISBN: 978-0-387-25150-9	Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2
অপর নাম	Ideal Point Model, Preferential Choice Scaling, Coombs Unfolding, Katlanma Modeli	CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi
সম্পর্কিত	2	2
সারসংক্ষেপ	The Unfolding Model is a geometric approach to preference analysis that represents both individuals and choice objects (stimuli) as points in a shared low-dimensional space. Originating with Clyde Coombs's foundational 1950 work on preferential choice and rigorously systematized by Borg and Groenen (2005), the model assumes each person prefers the stimulus closest to their personal ideal point, thereby 'unfolding' rank-order preference data into a joint spatial map.	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.