1998
DOI: 10.2188/jea.8.24
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The Utility of Hayashi's Quantification Theory Type 2 for The Rapid Assessment of The Epidemiological Survey in The Developing Countries -In a Case of The Vaccine Coverage Survey in Yunnan Province, China -

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Cited by 5 publications
(2 citation statements)
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“…www.md-journal.com Category scores were obtained by applying Hayashi's quantification theory type 2 [20][21][22] with the respondent's background as the explanatory variable and "(E) Overall grade on patient safety" as the objective variable to examine the impact of the respondent's background on patient safety culture. The range of scores defined as the difference between the maximum and minimum of the category scores obtained for each explanatory variable was calculated, [23] and the influence on patient safety culture was estimated. Hayashi's quantification theory type 2 is a linear discriminant analysis of categorical data.…”
Section: Discussionmentioning
confidence: 99%
“…www.md-journal.com Category scores were obtained by applying Hayashi's quantification theory type 2 [20][21][22] with the respondent's background as the explanatory variable and "(E) Overall grade on patient safety" as the objective variable to examine the impact of the respondent's background on patient safety culture. The range of scores defined as the difference between the maximum and minimum of the category scores obtained for each explanatory variable was calculated, [23] and the influence on patient safety culture was estimated. Hayashi's quantification theory type 2 is a linear discriminant analysis of categorical data.…”
Section: Discussionmentioning
confidence: 99%
“…Hayashi's Quantification Theory II.-HQT-II is one of four methods of quantification introduced by a Japanese statistician, Chikio Hayashi, who also coined the now widely used term "data science" in 1996. He developed his methods to deal with qualitative data, and they are widely used in Asia in many fields, such as the geologic, environmental, and medical sciences and civil engineering (Hayashi 1950;Matsuba et al 1998;Li et al 2005;Takasawa et al 2010). HQT-II aims at discrimination and classification of samples by establishing discrimination functions based on several variables of known types.…”
Section: Methodsmentioning
confidence: 99%