The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
An Analysis of Variance for Categorical Data
Abstract
A measure of variation for categorical data is discussed. We develop an analysis of variance for a one-way table, where the response variable is categorical. The data can be viewed alternatively as falling in a two-dimensional contingency table with one margin fixed. Components of variation are derived, and their properties are investigated under a common multinomial model. Using these components, we propose a measure of the variation in the response variable explained by the grouping variable. A test statistic is constructed on the basis of these properties, and its asymptotic behavior under the null hypothesis of independence is studied. Empirical sampling results confirming the asymptotic behavior and investigating power are included.
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Pearson, K. (1900) · The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science · doi:10.1080/14786440009463897 · Cited by 4,069
THE COMPARISON OF PERCENTAGES IN MATCHED SAMPLES
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An Introduction to Linear Statistical Models
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Variabilità e mutabilità : contributo allo studio delle distribuzioni e delle relazioni statistiche
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On the bias of various estimators of the logit and its variance with application to quantal bioassay
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Analysis of Factorial Arrangements when the Data are Proportions
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Fifty Years of Classification and Regression Trees
Loh, W. (2014) · International Statistical Review · doi:10.1111/insr.12016 · Cited by 649
A Computer-Derived Protocol to Aid in the Diagnosis of Emergency Room Patients with Acute Chest Pain
Goldman, L., Weinberg, M., Weisberg, M., Olshen, R., Cook, E. F., Sargent, R. K., Lamas, G. A., Dennis, C., Wilson, C., Deckelbaum, L., et al. (1982) · New England Journal of Medicine · doi:10.1056/nejm198209023071004 · Cited by 502
Regression and ANOVA with Zero-One Data: Measures of Residual Variation
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A novel evolutionary data mining algorithm with applications to churn prediction
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Relative Entropy Measures of Multivariate Dependence
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Metadata
- Authors
- Light, R. J., & Margolin, B. H.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1971-09
- Volume
- 66
- Issue
- 335
- Pages
- 534-544
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2001461029
- Cited by
- 329
- References
- 9
- FWCI
- 4.79
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
