• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Korean Journal of Applied Biomechanics
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• v.27 no.1
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• pp.67-74
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• 2017

Objective: The purpose of this study was to apply a general linear model in statistics to marker position vectors used to study human joint rotational motion in biomechanics. Method: For this purpose, a linear model that represents the effect of the center of hip joint rotation and the rotation of the marker position on the response was formulated. Five male subjects performed hip joint functional motions, and the positions of nine markers attached on the thigh with respect to the pelvic coordinate system were acquired at the same time. With the nine marker positions, the center of hip joint rotation and marker positions on the thigh were estimated as parameters in the general linear model. Results: After examining the fitted model, this model did not fit the data appropriately. Conclusion: A refined model is required to take into account specific characteristics of longitudinal data and other covariates such as soft tissue artefacts.

• Journal of Biomedical Engineering Research
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• v.6 no.1
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• pp.55-64
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• 1985

The cardiac activation process using three dimensional ventricular model is simulated.To study this theme, we constructed a cardiac ventricular model and simulated the cardiac activation process using the action potential duration and the activation time. The cardiac ventricular model is generated by the logical combination of the elliptic equations. The action potential duration could be obtained from the fact that it is linearly distributed between model cells. The cardiac activation process was simulated by the law of "all-or-none" Based on the activation time and the action potential do-ration the cardiac potential at the arbitrary time after the activation of the model cell was computed. To test the validity of model, the comparison of the results of model simulation with the physiological data was performed. In conclusion, this model shows the simular results which is comparable to the real conduction of the cardiac excitation.xcitation.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.63-76
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• 2006

Marine production forecasting in fisheries is a crucial factor for managing and maintaining fishery resources. Thus this paper aims to generate a forecasting model of total marine production. The most generally method of time series model is to generate the most optimal single forecasting model. But the method could induce a different forecasting results when it does not properly infer a model To overcome the defect, I am trying to propose a single forecasting through multiple time series model. In other word, by comparing and integrating the output resulted from ARIMA and VAR model (which are typical method in a forecasting methodology), I tried to draw a forecasting. It is expected to produce more stable and delicate forecasting prospect than a single model. Through this, I generated 3 models on a yearly and monthly data basis and then here I present a forecasting from 2006 to 2010 through comparing and integrating 3 models. In conclusion, marine production is expected to show a decreasing tendency for the coming years.

• Journal of Korean Academy of Nursing
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• v.33 no.3
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• pp.376-385
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• 2003

Purpose: This study was conducted to develop gerontological curriculum model which reflects the need of Korean society. Method: Three round Delphi survey method was applied to find consensus of gerontological nursing competencies (knowledge, attitudes and skills) for graduates of nursing schools from the panel of gerontological nursing practice experts. Important concepts in gerontological nursing were delineated from literature review and discussions of gerontological nursing educators. Based on these results the gerontological nursing curriculum model was developed and course structure outlined by the researchers as a group. Result: As the result of delphi survey, 32 items of knowledge, 29 items of attitude, and 21 items of skill were identified. The curriculum model constructed around a cube with three plane- functional capacity levels, settings, and nursing practice. Specific knowledge, attitudes and skills for gerontological theory and practicum course were suggested. Competency items were assigned to theory and/or practice. Conclusion: A curriculum model for gerontological nursing has been developed by a group of gerontological nursing educators. The curriculum model should be further tested and developed with detailed theory and practicum course outline and textbooks.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.6 no.1
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• pp.27-33
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• 2000

PURPOSE; The main purpose of this study is to develop a new learning model of Orthopedic Manual Therapy. METHOD; From 1997 to 1999, this survey was made of 318 students who had attended in Orthopedic Manual Therapy subject. RESULT; Results show that regard satisfaction with lecture was as 'good' by 235 person(73.3%). And the most interest subject among the therapists was orthopedic manual therapy(44.63%), next NDT(25.62%). CONCLUSION; This study suggest a new learning model of orthopedic manual therapy used by Role-play model and Coner study model. So we can be lecture effectively to focus students.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2885-2887
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• 2005

We introduce a hybrid identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of HCM clustering help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the GAs and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.9-11
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• 2005

We propose a optimal identification of information granulation(IG)-based fuzzy model to carry out the model identification of complex and nonlinear systems. To optimally identity we use genetic algorithm (GAs) sand Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the selected input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.

• Journal of Korean Academy of Nursing
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• v.41 no.2
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• pp.204-213
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• 2011

Purpose: This study was done to identify fundamental data on competency reinforcement programs to prevent adolescent risk behavior by developing and examining a competency model. Methods: In this study, competences on prevention of adolescent risk behavior were identified through competency modeling, and a competency model was developed and tested for validity. Results: Competences for prevention of adolescent risk behavior defined by the competency model included the following: self-control, positive mutual understanding between parents and adolescents, and positive connectedness with peer group. Validation of the competency model showed the model to be appropriate. Conclusion: The competency model for prevention of adolescent risk behavior through competency modeling is expected to be the foundation of an integral approach to enhance competency in adolescents and prevent adolescent risk behavior. This kind of approach can be a school-centered, cost-efficient strategy, which not only reduces adolescent risk behavior but also improves quality of adolescent resources.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.289-298
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• 1999

We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.