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Probability models for categorial data.
Multinomial distribution, asymptotic properties, delta-method.
Loglinear models, maximum likelihood estimators, tests of fit.
Contingency tables in two and three dimensions. Hypotheses of independence,
symmetry, marginal homogeneity. Iterative proportional fitting algorithm.
Loglinear models for multidimensional tables.
Small cell contingency tables, incomplete tables.
Measures of association.
Logit models.
Generalized linear models.
Last update: T_MUUK (31.01.2001)
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The aim of the subject is to acquaint students with specific properties of categorical data and to provide an overview of statistical methods and new developments in analysis of categorical data.
Last update: T_KPMS (20.05.2008)
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Agresti, A.: Analysis of Ordinal Categorical Data. J. Wiley, New York 1984.
Agresti, A.: Categorical Data Analysis. J. Wiley, New York 1990.
Andersen, E.B.: The Statistical Ananlysis of Categorical Data. Springer-Verlag 1994.
Prášková, Z.: Kontingenční tabulky (skripta). UK Praha, 1985. Last update: Zakouřil Pavel, RNDr., Ph.D. (05.08.2002)
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Lecture+exercises. Last update: G_M (28.05.2008)
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Probability models for categorial data. Multinomial distribution, asymptotic properties, delta-method. Loglinear models, maximum likelihood estimators, tests of fit. Contingency tables in two and three dimensions. Hypotheses of independence, symmetry, marginal homogeneity. Iterative proportional fitting algorithm. Loglinear models for multidimensional tables. Small cell contingency tables, incomplete tables. Measures of association. Logit models. Generalized linear models. Last update: T_KPMS (29.04.2003)
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