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Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables
by
Ando, Shuji
in
Confidence intervals
/ Contingency
/ Contingency tables
/ Datasets
/ Economic Theory/Quantitative Economics/Mathematical Methods
/ Inequality
/ Mathematics and Statistics
/ Normal distribution
/ Original Paper
/ Probability
/ Probability Theory and Stochastic Processes
/ Statistics
2024
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Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables
by
Ando, Shuji
in
Confidence intervals
/ Contingency
/ Contingency tables
/ Datasets
/ Economic Theory/Quantitative Economics/Mathematical Methods
/ Inequality
/ Mathematics and Statistics
/ Normal distribution
/ Original Paper
/ Probability
/ Probability Theory and Stochastic Processes
/ Statistics
2024
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Do you wish to request the book?
Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables
by
Ando, Shuji
in
Confidence intervals
/ Contingency
/ Contingency tables
/ Datasets
/ Economic Theory/Quantitative Economics/Mathematical Methods
/ Inequality
/ Mathematics and Statistics
/ Normal distribution
/ Original Paper
/ Probability
/ Probability Theory and Stochastic Processes
/ Statistics
2024
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Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables
Journal Article
Measure of deviancy from marginal mean equality based on cumulative marginal probabilities in square contingency tables
2024
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Overview
This study proposes a measure that can concurrently evaluate the degree and direction of deviancy from the marginal mean equality (ME) model in square contingency tables with ordered categories. The proposed measure is constructed as the function of the row and column cumulative marginal probabilities. When the ME model does not fit data, we are interested in measuring the degree of deviancy from the ME model, because the model having weaker restrictions than the ME model is only the saturated model. This existing measure, which represents the degree of deviancy from the ME model, does not depend on the probabilities that observations will fall in the main diagonal cells of the table. For the data in which observations are concentrated in the main diagonal cells, the existing measure may overestimate the degree of deviancy from the ME model. The proposed measure can address this issue. This study derives an estimator and an approximate confidence interval for the proposed measure using the delta method. The proposed measure would be utility for comparing degrees of deviancy from the ME model in two datasets. The proposed measure is evaluated the usefulness with the application to real data of clinical trials.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
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