An empirical study on the prediction of accountability and transparency score of charities: based on binary logistic regression model

Xinyu Song

doi:10.1117/12.2672685

28 March 2023 An empirical study on the prediction of accountability and transparency score of charities: based on binary logistic regression model

Xinyu Song

Author Affiliations +

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125971A (2023) https://doi.org/10.1117/12.2672685
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

In recent years, charities around the world have experienced frequent trust crises. As the country with the most advanced philanthropy, the United States has experienced many crises of confidence in its history. This paper selects the detailed information of 8,408 different American charities as research samples, conducts data exploration through factor analysis and comparative analysis, and uses binary logistic regression analysis to construct a linear model to obtain the correlation between various financial indicators and Accountability & Transparency Score. The relationship and correlation coefficient have good predictability. At the same time, according to the model results, reminding the financial indicators that charities need to focus on to improve accountability and transparency has certain guiding significance for the development of charities.

Citation Download Citation

Xinyu Song "An empirical study on the prediction of accountability and transparency score of charities: based on binary logistic regression model", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125971A (28 March 2023); https://doi.org/10.1117/12.2672685

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