• Journal of Agricultural Extension & Community Development
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• v.30 no.3
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• pp.157-170
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• 2023

This study aims to identify factors that affect the quality of life of rural residents. Data were collected from 4,000 rural residents living in rural areas. Raw data was procured from the 'Survey on Rural Well-being in 2022 in Rural Development Administration'. The main results of the ordinal logit regression analysis are as follows. First, in the case of non-farm households, female, immigrants, more educated, more healthy are more likely to be highly perceived quality of life. In the case of full-time farm households, more healthy are more likely to be highly perceived quality of life. In the case of part-time farm households, younger, married, more healthy are more likely to be highly perceived quality of life. Second, for all rural housholds(non-farmers, full-time farmers, and part-time farmers), local amenities and safety also had positive impact on perception of quality of life.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.313-322
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• 2005

In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.591-597
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• 2022

As social anxiety is increasing due to the spread of the COVID-19 epidemic, the responses at the level of local governments are also changing depending on the characteristics. We analyzed the factors influencing perceptions of social safety as they relate to the trustworthiness of local governments. Based on a 2020 social survey of 16 cities, counties, and districts in Busan Metropolitan City, the effects of householder characteristics, economic characteristics, local attachment characteristics, and social safety perception characteristics on the reliability of the local government were analyzed through an ordinal logistic regression analysis. It was found that the more vulnerable the class was and the safer the region was, the higher the trust was in the basic local government. In order to respond and preemptively recover damage in natural and social disaster situations, continuous efforts are needed to strengthen the capabilities of basic local governments.