• Survey Research
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• v.10 no.1
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• pp.169-186
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• 2009

The propensity score method is used to minimize the bias level in social survey, which comes from nonresponse. The theoretical concept and the background of the propensity score method is discussed first. The propensity score method was first applied in the epidemiology observational study. I have summarized the process of the three propensity score methods that were used to reduce estimation bias in this study. Matching by propensity score is applied to the relatively large control group. Subclassification has the advantage of using whole control group data and regression adjustment is applied to multiple covariates as well as propensity score of each unit is computable and usable. Lastly, the application procedures of propensity score method to reduce the nonresponse bias is suggested and its applicability to real situation is reviewed with the existing data.

• Korean Journal of Culture and Social Issue
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• v.19 no.3
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• pp.367-388
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• 2013

This study examined how drivers of different cultural orientations(individualism vs. collectivism) attribute the cause(dispositional vs. situational) of four simulated driving situations which were varied in types(cutting-in and sudden-stop by the other driver) and differential emphasis on other the other driver's driving attitude or situational factor. The results showed the followings. First, the drivers generally showed higher attribution scores on the dispositional factor than the situational factor, except for the 'sudden-stop: situation emphasis' scenario condition. Second, when drivers' cultural orientation and attribution styles were considered together, it was found that, except for the 'cutting-in: disposition emphasis' scenario condition. the drivers of collectivism tended to attribute more to situational factor than the drivers of individualism, In contrast, the drivers of individualism showed higher attribution scores on dispositional factor than situational factor in all driving scenario conditions. Implication and suggestion were discussed.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.91-100
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• 2016

Fuzzy matching is proposed to make propensities of two groups similar with their propensity scores and a way to select control variable to make propensity scores with a process that shows how to acquire propensity scores using logic regression analysis, is presented. With such scores, it was a method to obtain an experiment group and a control group that had similar propensity employing the Fuzzy Matching. In the study, it was proven that the two groups were the same but with a different distribution chart and standardization which made edge tolerance different and we realized that the number of chosen cases decreased when the edge tolerance score became smaller. So with the idea, we were able to determine that it is possible to merge groups using fuzzy matching without a precontrol and use them when data (big data) are used while to check the pros and cons of Fuzzy Matching were made possible.

• Journal of Technology Innovation
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• v.32 no.2
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• pp.1-21
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• 2024

This study aims to estimate policy effects that appear heterogeneously within the beneficiary group by matching the beneficiary and non-beneficiary groups based on propensity score quartiles and analyzing the effect of policy benefits on sales growth. To achieve this, 239 SMEs that participated in R&D support program for the manufacturing of materials, components, and equipment in 2020 were selected as the beneficiary group. The propensity scores of these companies were calculated and divided into eight quartiles for matching between the non-beneficiary and beneficiary groups. Subsequently, double difference analysis was used to calculate the sales growth rate attributable to policy support. The study found that the largest policy effect was observed in the lowest quartile group, and companies with high patent application rates and 3-year sales growth rates experienced significant policy effects. These findings suggest that propensity score quartile-based analysis can be effectively utilized to refine the criteria for selecting beneficiary companies and the scope of industrial policy support.

• Survey Research
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• v.10 no.3
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• pp.21-36
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• 2009

This study suggests the applicability of web surveys regarding elections in order to contact a great number of young people. The propensity weighting model was estimated using the demographic variables and the covariate variables collected during the 2007 presidential election surveys. In order to adjust the internet survey to the telephone survey, we used the propensity score method. Propensity score weighting made the internet survey results closer to the telephone survey results. This shows that an internet survey with propensity weighting model is a potential alternative survey method in the prediction of elections.

• Child Health Nursing Research
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• v.20 no.4
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• pp.294-303
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• 2014

Purpose: The purpose of this study was to identify the correlation of critical thinking disposition and problem solving process, and the simulation- based assessment of clinical competence based on a survey of college nursing students. Methods: In this descriptive correlation study, data for 214 nursing students were analyzed using t-test and Pearson correlation coefficients. Results: Critical thinking disposition, problem solving process, and simulation-based assessment of clinical competence averaged $3.76{\pm}0.46$ (out of 5), $3.67{\pm}0.47$ (5), and $1.51{\pm}0.17$ (2), respectively. A significant difference in scores for simulation-based assessment of clinical competence was found between the high-scoring group and low-scoring group in critical thinking disposition. A significant positive correlation was found between critical thinking disposition and nursing assessment, a sub-domain of clinical competence. Conclusion: The results suggest that success in simulation-based learning requires critical thinking disposition in the nursing students, and their critical thinking disposition plays a positive role in nursing assessment, which evaluates the patient's status in a complex situation. Simulation-based learning programs help assess the students' levels in their clinical judgement and performance, and identify their strengths and weaknesses so that the instructor can evaluate and improve the current teaching method.

• Journal of Gifted/Talented Education
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• v.24 no.6
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• pp.961-974
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• 2014

We analyzed the relationship between the brain Dominance and the scientific creative problem solving utilizing propensity to target Science-Gifted Student (n=159). Brain dominance is divided into left upper brain (LUB), left lower brain (LLB), right lower brain (RLB), and right upper brain (RUB). Creative problem solving skill in science included validity, scientific characteristics, sophistication, originality, and fluency. Analysis of the results of this study showed a high frequency among the four types of the brain dominance is the highest score of LUB in science gifted group. This point was found that the tendency of the analytical and critical thinking that is characteristic of the LUB is strong scientific gifted group. When total sample was divided into high and low groups by scientific creative problem solving scores, in the analysis of the brain dominance score difference between the two groups of students who take advantage of the results of score RUB is compared to the high fluency group score higher than the low group found (p<0.05). The analysis of the correlation between brain dominance and scientific creative problem solving showed that originality and fluency had statistically significant correlation with RUB propensity score (p<0.05). This result suggests that the imaginative and challenging RUB propensity may be related to produce many and original ideas in scientific creative problem solving.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.127-133
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• 2016

The objective of this study is to investigate the association between MBTI personality types of potential investors and their cognitive behavioral investment disposition. Three questionnaires related with MBTI, cognitive investment disposition, and behavioral one from 400 subjects were collected and analyzed. Based on both cognitive and behavioral investment disposition scores, potential investors having E(Extroversion), S(Sensing), and F(Feeling) types tend to put up with the risk resulting from their investment better than ones who having I(Introversion), N(Intuition), and T(Thinking) types. However, the difference between J(Judging) and P(Perceiving) types was not significant. Also investor group with ENF combination had the most aggressive investment disposition among other groups. On the contrary the group with ISF had an tendency to avoid the investment risk. In addition the correlation between cognitive and behavioral investment dispositions was 0.86. This study is expected to be used as basic data with which investment companies and banks recommend adequate financial instruments to consumers.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.187-198
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• 2011

Researches on children's traffic behavior have only focused on traffic accidents and the number of accidents, and therefore it's been impossible to deal with more broad field of study. In this research we can review the possibility of traffic accidents of children and provide them with traffic education. The goal of this research is to develop a device for measuring possibility of children in terms of traffic behavior. Around 600 elementary students of two schools involved in the pretest with 259 questions and about 3,500 students(junior level 53 questions & senior level 72 questions) involved in practical test. At the result of the research, junior level extracted 4 factors(Lack of behavioral control, Aggressive, Self-regulation, Impulsive Instinct) and 44 questions, and senior level extracted 4 factors(Lack of behavioral control, Depression, Sense-oriented, Aggressive) and 69 questions. We take the gender consideration in separate the groups whether the group has traffic behavioral problem or not. In these series of research, we got the standard score such as junior male student, 63 & female student, 50 and senior male student, 110 & female student, 99.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.453-462
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• 2017

Double propensity score adjustment is an analytic solution to address bias due to incomplete matching. However, it is difficult to estimate the standard error of the estimated treatment effect when using double propensity score adjustment. In this study, we propose two bootstrap methods to estimate the standard error. The first is a simple bootstrap method that involves drawing bootstrap samples from the matched sample using the propensity score as well as estimating the standard error from the bootstrapped samples. The second is a complex bootstrap method that draws bootstrap samples first from the original sample and then applies the propensity score matching to each bootstrapped sample. We examined the performances of the two methods using simulations under various scenarios. The estimates of standard error using the complex bootstrap were closer to the empirical standard error than those using the simple bootstrap. The simple bootstrap methods tended to underestimate. In addition, the coverage rates of a 95% confidence interval using the complex bootstrap were closer to the advertised rate of 0.95. We applied the two methods to a real data example and found also that the estimate of the standard error using the simple bootstrap was smaller than that using the complex bootstrap.