• 보건행정학회지
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• 제25권1호
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• pp.31-39
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• 2015

Background: The purpose of this study is comparison of the results between regression and multi-level analysis to find out factors influencing outcome indicators (in-hospital death, length of stay, and medical charges) of stroke patients. Methods: By using patient sample data of Health Insurance Review & Assessment Service, patients admitted with stroke were selected as survey target and 15,864 patients and 762 hospitals were surveyed. Results: For the results of existing regression analysis and multi-level analysis, models were assessed through model suitability index value and as a result, the value of results of multi-level analysis decreased compared to the results of regression, showing it is a better model. Conclusion: Factors influencing in-hospital death of stroke patients were analyzed and as a result, intra-class correlation (ICC) was 13.6%. In factors influencing length of stay, ICC was 11.4%, and medical charges, ICC was 17.7%. It was found that factors influencing the outcome indicators of stroke patients may vary in every hospital. This study could carry out more accurate analysis than existing research findings through analysis of reflecting structure at patient level and hospital level factors and analysis on random effect.

• Genomics & Informatics
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• 제20권4호
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• pp.48.1-48.7
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• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• 보건행정학회지
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• 제30권3호
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• pp.355-365
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• 2020

Background: This study is aimed to verify individual and regional-level factors affecting the depression of Koreans and to develop social programs for improving the depressive status. Methods: This study used individual-level variables from the Korean Community Health Survey (2018) and used the e-regional index of the Korean Statistical Information Service as the regional-level variable. A multi-level logistic regression was executed to identify individual and regional-level variables that were expected to affect the extent of depressive symptoms and to draw the receiver operating characteristic curve to compare the volume of impact between variables from both levels. Results: The results of the multi-level logistic regression analysis in regards to individual-level factors showed that older age, female gender, a lower income level, a lower education level, not having a spouse, the practice of walking, the consumption of breakfast higher levels of stress, and having high blood pressure or diabetes were associated with a greater increase in depressive symptoms. In terms of regional factors, areas with fewer cultural facilities and fewer car registration had higher levels of depressive symptoms. The comparison of area under the curve showed that individual factors had a greater influence than regional factors. Conclusion: This study showed that while both, individual and regional-level factors affect depression, the influence of the latter was relatively weaker as compared to the first. In this sense, it is necessary to develop programs focused on the individual, such as social prescribing at the local or community-level, rather than the city and nation-level approach that are currently prevalent.

• 보건행정학회지
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• 제30권3호
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• pp.399-408
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• 2020

Background: The purpose of this study was to examine the impact of the regional characteristics on the accessibility of emergency care and the impact of emergency medical accessibility on the patients' prognosis and the emergency medical expenditure. Methods: This study used the 13th beta version 1.6 annual data of Korea Health Panel and the statistics from the Korean Statistical Information Service. The sample included 8,119 patients who visited the emergency centers between year 2013 and 2017. The arrival time, which indicated medical access, was used as dependent variable for multi-level analysis. For ordinal logistic regression and multiple regression, the arrival time was used as independent variable while patients' prognosis and emergency medical expenditure were used as dependent variables. Results: The results for the multi-level analysis in both the individual and regional variables showed that as the number of emergency medical institutions per 100 km² area increased, the time required to reach emergency centers significantly decreased. Ordinal logistic regression and multiple regression results showed that as the arrival time increased, the patients' prognosis significantly worsened and the emergency medical expenses significantly increased. Conclusion: In conclusion, the access to emergency care was affected by regional characteristics and affected patient outcomes and emergency medical expenditure.

• 한국건축시공학회지
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• 제4권4호
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• pp.63-70
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• 2004

The objective of this study is to evaluate the compressive strength of recycled aggregate concrete by the non-destructive testing. Main experimental variables were the replacement level of recycled aggregate and blast-furnace slag, which were divided into two series according to recycled aggregate maximum size. Test results showed that a recycled aggregate had a significant influence on the non-destructive testing results, such as rebound number, Ultrasonic pulse velocity, and frequency. A prediction model of compressive strength considering the replacement level of recycled aggregate was suggested by multi-regression analysis and was compared with test results.

• 한국병원경영학회지
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• 제27권2호
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• pp.44-52
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• 2022

Purposes: This study tried to extract variables affecting patient-experience satisfaction level in hospital situation, using a multiple-regression analysis and ISA(Revised Importance-Satisfaction Analysis), and to explore variables needed to be improved. Methodology: A mobile-based online patient-experience survey was conducted in eleven general hospitals in A city. To test the validity of this test, this data was compared with the data from Health-Insturance Review and Assessment Service. Then, the standardized regression coefficients extracted from a multiple-regression analysis were used as the importance scale to be used in ISA. Finding: Taken together, the areas with the highest contribution for the in-hospital patient-experience satisfaction level were medication and treatment process and hospital environment. In conclusion, the revised ISA which can show satisfaction and importance both with simultaneously and multi-axis way would be useful in hospital improvement activities. Practical Implications: This study tried to develop a mobile-based patient-experience survey, and to extract the major variables affecting patient-satisfaction level and to identify variables need to be improved. Finally, this should help hostipals to prepare the assessment process with various improvement activities.

• 대한토목학회논문집
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• 제42권4호
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• pp.571-579
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• 2022

본 연구는 부산·울산·경남 지역의 관광호텔을 대상으로 에너지사용량과 이들의 개별적인 호텔특성 및 입지특성 간의 관계를 실증분석하였다. 복합적인 관계식 도출을 위해 다중회귀모형에서부터 다수준회귀분석(multi-level regression analysis)으로 모형을 확장하였고, 이를 통해 건축물의 개별적인 특성만을 고려한 대부분의 선행연구에서 나아가 호텔이 위치한 지역의 입지적 특성과 호텔-지역 간 위계적 구조를 고려하여 좀 더 개선된 모형을 도출하였다. 분석결과에 따르면, 호텔의 규모, 연한, 서비스 등급과 같은 개별적인 특성은 에너지사용량을 설명하는 주요 변수이고, 그들의 영향은 지역적으로 유의한 차이를 보이는 것으로 나타났다. 또한, 중심상업지에 인접하거나 다수의 관광호텔이 밀집한 지역에 위치할수록 에너지사용량은 달라지는 것으로 나타났으며, 이러한 입지특성 또한 개별호텔의 에너지사용량을 설명함에 있어 주요한 요인임을 확인하였다. 이와 같은 결과는 건축물단위의 에너지정책과 소비수준이 높고 에너지 집약시설이 밀집한 지역에 대한 지역단위의 에너지정책이 함께 고려될 필요성을 시사하며, 관광산업의 지속가능성을 높이기 위한 지역적 책임을 제언한다.

• 물과 미래
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• 제27권3호
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• pp.55-69
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• 1994

홍수시 한강 인도교에 대한 단기간 예보의 정확도를 제고하기 위한 통계학적 홍수예보모형으로 '인도교수위와 영향인자간의 다중회귀분석에 의한 다변수 모형(MM 모형)'과 '수위구간별 다중회귀분석에 의한 다수준 다변수 모형(MMP 모형)' 그리고 '수위의 증감추세에 따른 2 수준 다변수 모형(2MP 모형)'을 제시하였다. 연구대상으로는 분석된 세가지 모형 중, 'MM 모형'은 4시간예측시 평균오차가 35cm 이내의 정도를 나타내며 'MMP 모형'은 모형개발시에 구분한 각 수위구간에 대해서는 매우 작은 평균오차를 나타내지만 실제 홍수사상에 적용시에는 뚜렷한 정도의 향상을 나타내지 못하는 것으로 보인다. 이것은 실제홍수시 수위가 각 구간내에만 머물지 않기 때문인 것으로 보인다. 한편 '2MP 모형'은 예측정도가 가장 높으나 드물게 발산현상이 나타나고 있어 안정도가 떨어지며, 'MMP 모형'은 '2MP 모형'과 비교하여 예측정도는 약간 떨어지나 안정된 예측결과를 보여준다.

• Journal of Preventive Medicine and Public Health
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• 제55권2호
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• pp.153-163
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• 2022

Objectives: This study divided the factors that affect participation in health screenings into individual, household, and regional levels and conducted a multi-level analysis to identify the factors related to participation in health screenings. Methods: Participants from the 2017 Community Health Survey were classified into 2 groups (under 40 and 40 or older). A multi-level logistic regression analysis was conducted to identify the factors that affected participation in health screenings. Results: The screening rate of the participants was 69.7%, and it was higher among participants aged 40 and older (80.3%) than it was among participants younger than 40 (49.8%). At the individual level, the factors that influenced participation in health screenings included age, economic activity, smoking status, physician-diagnosed hypertension, and a moderate or high physical activity level. At the household level, the odds ratio of participation in health screenings was high for participants who lived in single-person households, lived with a spouse, earned a high monthly household income, and were not beneficiaries of national basic livelihood security. At the regional level, the odds ratio at the 95% confidence interval level of participation in health screenings was high for participants who had trust in the local community and lived in an area with a proportionally high social welfare budget. Conclusions: This study analyzed nationalwide data and confirmed that individual, household, and regional characteristics affected participation in health screenings. Therefore, policies that prioritize the improvement of regional level factors and especially household level factors are likely to be the most effective for improving the screening rate.

• 지역연구
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• 제36권4호
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• pp.57-67
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• 2020

최근 대도시를 중심으로 주택가격의 급격한 상승에 따라 서민들의 주거안정도 크게 위협받고 있다. 본 연구는 대도시 거주자들의 주거불안정성에 주목하여 이에 영향을 미치는 요인을 분석하였다. 특히, 기존의 선행연구들이 주거비부담능력이 낮은 가구들의 주거불안 경험과 이에 따른 그들의 삶의 변화를 보여주는 데 주목해온 것과 달리, 본 연구에서는 거주지역의 공간적 개방성, 커뮤니티 특성 등 지역특성이 거주자들의 주거불안 경험을 완화 또는 심화시킬 수 있다는 점에 주목하여 이에 대한 영향력을 실증분석하였다. 대도시 거주자들의 주거불안정 영향요인을 분석하기 위한 자료로 2017년도 주거실태조사를 활용하여 다층로짓모형(Multi-level Logistic Model)을 통해 분석하였다. 분석 결과는 가구의 주거비 부담능력과 같은 가구특성뿐만 아니라 주택 재고, 저렴한 주택 가격, 사회적 관계망 등 지역 특성의 영향력 또한 확인하였다. 이러한 결과는 지역의 공간적 포용성 증진이 주민들의 주거불안정을 완화하는 데 긍정적인 영향을 미칠 것임을 시사한다. 논의를 바탕으로 본 연구는 주거불안정을 도시정책 차원에서 주목하고, 이를 완화해나가기 위한 정책적 노력이 필요함을 제안한다.