• Journal of Korean Academy of Nursing
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• v.37 no.3
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• pp.414-421
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• 2007

Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.

• Health Policy and Management
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• v.25 no.1
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• pp.3-10
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• 2015

Background: Previous studies showed differences in healthcare utilization among insurance types. This study aimed to analyze the difference in healthcare utilization for percutaneous transluminal coronary angioplasty inpatients by insurance types after controlling factors affecting healthcare utilization using propensity score matching (PSM). Methods: The 2011 national inpatient sample based on health insurance claims data was used for analysis. PSM was used to control factors influencing healthcare utilization except insurance types. Length of stay and total charges were used as healthcare utilization variables. Patients were divided into National Health Insurance (NHI) and Medical Aid (MA) patients. Factors representing inpatients (gender, age, admission sources, and Elixhauser comorbidity index) and hospitals (number of doctors, number of beds, and location of hospitals) were used as covariates in PSM. Results: Tertiary hospitals didn't show significant difference in length of stay and total charges after PSM between two insurance types. However, MA patients showed significantly longer length of stay than that of NHI patients after PSM in general hospitals. Multivariate regression analysis provided that admission sources, Elixhauser comorbidity index, insurance types, number of doctors, and location of hospitals (province) had significant influences on the length of stay in general hospitals. Conclusion: Study results provided evidences that healthcare utilization was differed by insurance types in general hospitals. Health policy makers will need to prepare interventions to influence the healthcare utilization differences between insurance types.

• Health Policy and Management
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• v.26 no.4
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• pp.343-351
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• 2016

Background: This study aims to analyze the effects of insurance types on the medical service uses for heart failure inpatients using propensity score matching (PSM). Methods: 2014 National inpatient sample based on health insurance claims data was used in the analysis. PSM was applied to control factors influencing the service uses except insurance types. Negative binomial regression was used after PSM to analyze factors that had influences on the service uses among inpatients. Subjects were divided by health insurance type, national health insurance (NHI) and medical aid (MA). Total charges and length of stay were used to represent the medical service uses. Covariance variables in PSM consist of sociodemographic characteristics (gender, age, Elixhauser comorbidity index) and hospital characteristics (hospital types, number of beds, location, number of doctors per 50 beds). These variables were also used as independent variables in negative binomial regression. Results: After the PSM, length of stay showed statistically significant difference on medical uses between insurance types. Negative binomial regression provided that insurance types, Elixhauser comorbidity index, and number of doctors per 50 beds were significant on the length of stay. Conclusion: This study provided that the service uses, especially length of stay, were differed by insurance types. Health policy makers will be required to prepare interventions to narrow the gap of the service uses between NHI and MA.

• Korean Journal of Social Welfare Studies
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• v.44 no.3
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• pp.5-30
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• 2013

The aim of this study is to identify the influence of public housing on depression of its residents by analyzing the 7th Korea welfare panel study. To reduce the selection bias which arise from the public housing is selected by personal choice, we used PSM(propensity score matching). In addition, we merged the result of PSM and OLS regression to control the other variables which can affect depression of the resident of public housing. Final result revealed that the statistical significance which was observed when we compared the level of depression between the residents of public housing and general community by independent t-test was not observed when we used the merged result from PSM and regression. These results suggest that the high level of depression in the residents of public housing might be related with their demographic characteristics or earned income not with the public housing itself. This study can be the evidence supporting the policy of providing public housing because living in public housing did not give negative influence on its residents. Considering that this study also showed that there were no observable positive influences of public housing, we can suggest that public housing policy for majority of people not limited to people with low income.

• Journal of the Korean School Mathematics Society
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• v.18 no.1
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• pp.149-167
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• 2015

In this study, we estimate the effect of ability grouping on mathematics achievement empirically. We use propensity score matching(PSM) method to minimize selection bias and estimate the effect of ability grouping on the mathematics standard score of Scholastic Ability Test with the KELS(Korea Education Longitudinal Study) 6th stage data. The result indicated that relationship between ability grouping and mathematics achievement is positive and Policy efforts is needed to operate ability grouping effectively.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.65-78
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• 2017

Objectives : Obesity is a worldwide health concern due to an increasing obese population. This study proposed to analyze the differences in medical costs and care utilization between obese and normal group using propensity score matching. Methods : Data were collected from the sample cohort database by the Korea National Health Insurance Corporation. Propensity score matching(PSM) was applied to control selection bias, and factors affecting obesity were used as covariates in PSM. Results : The results showed higher medical costs and care utilization in the obese group than the normal group. According to gender and medical type, there were differences in the relationships between obesity and medical charges and utilization. In particular, the differences in the female population were larger in both outpatients and inpatients than the male population. Conclusions : It is important to manage obesity, because obesity has a negative effect on national health insurance costs. These findings suggest directions for future research.

• Journal of Korean Traditional Oncology
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• v.27 no.1
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• pp.25-36
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• 2022

The Randomized Control Trial (RCT) is the most well-established and widely used statistical methodology in clinical research; however, applying thorough RCT to cancer patients presents challenges such as ethical concerns, high costs, short clinical periods, and limitations in collecting various side effects. To address this issue, the propensity score matching method, which takes advantage of the benefits of observational research while compensating for the drawbacks of randomized control trials, is used in a variety of fields. In recent years, 28 studies on the effectiveness of Korean medicine on tumors have been conducted abroad using the Propensity Score Matching Method, but none have been conducted in Korea. The majority of studies have focused on liver cancer, colon cancer, lung cancer, and stomach cancer, with endpoints such as survival time, incidence rate, quality of life, and treatment outcomes revealing statistical differences in how Korean medicine intervention affects treatment outcomes. As a result, well-established studies using the propensity matching score methodology should be useful in evaluating the impact of Korean medicine in oncology treatments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.1
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• pp.200-208
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• 2009

Trend of R&D expenditure in Korea during the last 10 years, the R&D expenditure has been constantly increasing at an average rate of 10%. The government R&D ekpenditures or subsidies are increasing rapidly But the studies of evaluating impact of government R&D subsidies are few. This study attempts to empirically investigate the effects of government R&D subsidies on private firm's R&D investment in Korean industry by using Propensity score matching method which sign as to whether the relationship between government subsidies and private R&D investments is on stimulating or displacing private R&D expenditures. Empirically, a firm with government R&D subsidy are 733 million dollar more expenditure then don't receive any government R&D funding. Also Government R&D subsidies greatly increase (statistically significant) company financed R&D expenditures only for large firms but had no effect on the R&D expenditures of small & medium sized firms and venture firms.

• Korean Journal of Social Welfare Studies
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• no.37
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• pp.171-197
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• 2008

This study focuses on the following question; self-supporting training program increases participants' income compare to non-participants who have similar characteristics. This question is based on counterfactual assumption. In other words, this study concentrates on what the outcomes would have been if the participants were to be absent. This study adopts a quasi-experimental design. To overcome previous study's methodological weaknesses, especially selection bias, I applied matching procedure based on a propensity-score matching. Matching process was performed by using 'MatchIt' software. The major findings are as follows From Least Squares Regression analysis, I found the poor's income are significantly different according to age, pre-intervention earning, material status, and participation of training. Since the poor have homogeneous education level, education variable was not statistically significant. From the Simulation Quantities of Interest analysis, I also found that treatment group's expected incomes are lower than control's expected incomes. In other words, participation of training has a negative effect on the participants' earnings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1829-1837
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• 2010

During the last year, public expenditures which provided the central and local governments for boosting research and development (R&D) activities of the private sector has been constantly increasing. 17 percent of public total R&D expenditure supported to private sector and 9 percent of R&D expenditure in service sector were public R&D funding. However, studies evaluating the impact of public R&D subsidies are quite few. The aim of this study empirically investigate the average effects of public R&D subsidies on the innovation activities in private sector, specifically those engaged in Korean service firms by using Propensity Score Matching(PSM) method. The effect of R&D subsidies is derived from either qualitative and quantitative outcomes of innovation activities, which is defined as the difference between innovation outcome of the treatment group (receiving R&D subsidies) and that of the control group (non receiving R&D subsidies) after the matching method. As a result of empirical analysis, government R&D grants stimulate only firm-first innovation outcomes in service firms. It is represent that public R&D subsidies cannot be contributed to level of national innovation and the total amount of national innovation activities but can enhance firm competitiveness from increasing firm-first innovation activities.