Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article
Author

Kouji Tahata

Tokyo University of Science, Japan
3 articles in our journals

Articles where this person is an author, newest first. People are matched by their name as printed (no ORCID iD is recorded for them), not by name alone; search the name as text to find namesakes too.

Research ArticleOpen accessMeasure of Departure from Partial Symmetry for Square Contingency TablesYusuke Saigusa, Kouji Tahata, Sadao TomizawaFor square contingency tables, the present paper newly considers the partial symmetry model which indicates that there is a symmetric structure of probabilities for at least one of pairs of symmetric cells. It also proposes the measure to express the degree of departure from the partial symmetry model. Examples are given. …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 9 Aug 2016 · 7,416 accessesView PDFCite
Research ArticleOpen accessMeasure of Departure from Average Cumulative Symmetry for Square Contingency Tables with Ordered CategoriesKouta Miyazawa, Sadao Tomizawa, Kouji TahataProblem statement: For square contingency tables with ordered categories, we are interested in considering a structure of weak symmetry when Bowker's symmetry model does not hold and in measuring the degree of departure from weak symmetry. Approach: The present study considered the average cumulative symmetry model that has a weaker restriction than the structure of symmetry. It also gave a … …Current Research in Biostatistics, Vol. 1, Issue 1 · 30 Jun 2010 · 7,621 accessesView PDFCite
Research ArticleOpen accessDecomposition of Marginal Homogeneity into Logit and Mean Ridits Equality for Square Contingency TablesKiyotaka Iki, Kouji Tahata, Sadao TomizawaProblem statement: For square contingency tables with ordered categories, if the Marginal Homogeneity (MH) model holds, then the probability that X selected at random from the row marginal distribution is less than Y selected independently at random from the column marginal distribution equals the probability that X is greater than Y. However, the converse does not hold. We are interested … …Journal of Mathematics and Statistics, Vol. 6, Issue 1 · 31 Mar 2010 · 7,297 accessesView PDFCite