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Analysis of variance of categorical data−nested designs
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In this paper, a categorical analysis of variance, or catanova, is presented for two factors, one nested in the other, and a breakdown is given of the total observed variation into independent sources so that the effects of each factor can be tested and concluded separately.Abstract:
Categorical analysis of variance, or catanova, is presented in this paper for two factors one of which is nested in the other. A breakdown is given of the total observed variation into independent sources so that the effects of each factor can be tested and concluded separately. In catanova, frequency data are analysed in their original format, without the need for any transformation such as logit or log linear.read more
Citations
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Application of Categorical Data-nested Design of Knowledge & Control Practices of HBV Infection
O. A. P. Otaru,P. N. Ogbonda +1 more
TL;DR: In this article, the significance of main factor (University) and sub-factor (Faculty) are studied using categorical data in nested classification using the CATANOVA technique.
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CATANOVA Analysis of Knowledge and Control Practices of Hepatitis B Virus Infection amongst Tertiary University Students
TL;DR: The objective of the research was to study the significant effect of gender, faculties and interaction using categorical data in a two-way cross classification using CATANOVA technique to reveal poor level of student’s knowledge and control practices of hepatitis B virus infection.
References
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Journal ArticleDOI
The Analysis of Variance
TL;DR: In this paper, the basic theory of analysis of variance by considering several different mathematical models is examined, including fixed-effects models with independent observations of equal variance and other models with different observations of variance.
Journal ArticleDOI
Probability and Statistical Inference.
TL;DR: Probability and Statistical Inference as mentioned in this paper, by Robert V. Hogg and Elliot A. Tanis. New York, Macmillan, 1977. ix, 450 p. 24 cm.
Book
Probability and Statistical Inference
Robert V. Hogg,Elliot A. Tanis +1 more
TL;DR: In this article, the authors present a generalization of the Bivariate Normal Distribution to the continuous type of data, where the Gamma and Chi-square distributions are used to measure the mean, variance, and standard deviation.
Journal ArticleDOI
An Analysis of Variance for Categorical Data
TL;DR: In this article, a measure of variation for categorical data is discussed, and a test statistic is constructed on the basis of these properties, and its asymptotic behavior under the null hypothesis of independence is studied.