ABC 法による一問一答形式の質的研究の飽和率と遭遇率の推定

Translated title of the contribution: Estimating degree of saturation for qualitative research data in question-and-answer format using the ABC method

Jinghao Ma, Hideki Toyoda, Kotaro Ohashi

Research output: Contribution to journalArticlepeer-review

Abstract

In qualitative data analysis, comprehensive knowledge collection is considered important, and the degree of saturation serves as one of the indicators. The Zipf distribution method can be used for the quantitative estimation of the degree of saturation in question-and-answer format qualitative data. However, this method may overestimate the degree of saturation. To address this issue, this paper proposes a new approach using the approximate Bayesian computation (ABC) method, which reduces the bias in saturation estimation. Furthermore, through simulations, we compared the bias between this new estimation method and the existing one, demonstrating that the estimation using the ABC method has a higher accuracy. Moreover, we compared the differences and similarities between the two methods through case studies in practical operational settings.

Translated title of the contributionEstimating degree of saturation for qualitative research data in question-and-answer format using the ABC method
Original languageJapanese
Pages (from-to)372-381
Number of pages10
JournalShinrigaku Kenkyu
Volume95
Issue number6
DOIs
Publication statusPublished - 2025

ASJC Scopus subject areas

  • General Psychology

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