• Journal of muscle and joint health
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• v.5 no.2
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• pp.206-221
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• 1998

The purpose of this study was to validate translated Multidimensional Assessment of Fatigue(MAF) scale. The scale is a 16-item scale that measures four dimensions of fatigue : severity, distress, impact, timing. Fourteen items are numerical rating scales and 2 items have multiple choice responses. Data were collected from the 137 patients with rheumatoid arthritis after content validation. Criterion validity was tested by correlation coefficient with Piper Fatigue Scale, which resulted in 0.7573(p<.0000). Construct validity was tested by item analysis and factor analysis. Corrected item-total correlation coefficients were 0.63-0.88. And factor analysis showed 2 factors : fatigue degree factor and fatigue impact factor. These two factors explained 73.5% of total variance. Reliability of internal consistency was 0.96 in Cronbach's alpha. Further validation study is necessary in each factor in other settings with other subjects.

• Journal of Korean Academy of Nursing
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• v.45 no.6
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• pp.783-801
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• 2015

Purpose: The purpose of this study is to provide a comprehensive overview of the various measures available for assessment of oxaliplatin-induced peripheral neuropathy (OXLIPN) and to evaluate the measurement properties of each assessment tool. Methods: A systematic review was conducted to identify existing measures for OXLIPN found in the databases of PubMed, Cochrane Library, Embase, RISS and KoreaMed. The quality of the 24 identified tools was evaluated based on their properties of measurement including content validity, internal consistency, criterion validity, construct validity, reproducibility, responsiveness, floor-ceiling effects and interpretability. Results: Ten (41.7%) of the 24 tools were identified as specific measures for assessing OXLIPN and the most popular type of measures were clinical grading systems by clinicians (58.3%) and only 29.2% of measures were identified as patient reported outcomes. The most frequently used tool was National Cancer Institute-Common Toxicity Criteria (NCI-CTC), but the validity of NCI-CTC has not been reported appropriately. Overall, the Neuropathic Pain Symptom Inventory (NPSI) received the best psychometric scores, and the Chemotherapy-induced Peripheral Neuropathy Assessment Tool (CIPNAT) and Functional Assessment of Cancer Therapy/Gynaecologic Oncology Group-neurotoxicity-12 (FACT/GOG-Ntx-12) followed NPSI. Conclusion: To select appropriate measure, evidences should be accumulated through the clinical use of tools. Therefore, practitioner and researchers are urged to report relevant statistics required for the validation of the currently used measures for assessment of OXLIPN.

• Korean Journal of Social Welfare
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• v.66 no.2
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• pp.255-286
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• 2014

This study aimed at developing and validating two standardized measures, 'power controllability', and 'power desirability', which can be utilized to categorize power relationships among the school youth. In order to identify initial items for the measures researchers conducted individual as well as focus group interviews with middle and high school students. School teachers and other school related professionals involved in ensuring both the face validity and the content validity of the initial items. For the finally selected items both exploratory and confirmatory factor analyses have been executed with the sample of 1,822 students attending elementary, middle, and high schools in the metropolitan area of Seoul, Korea. To test the validity of the confirmed factor structure of the measures the new sample of 348 middle school students were employed from the metropolitan area. Both construct validity and reliability were calculated from the validity test sample. Based on the two developed measures 4 types of power relationship were identified among the students. The four types of power relationship turned out to predict well the roles that students take in the field of school violence.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• The Pure and Applied Mathematics
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• v.27 no.2
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• pp.71-81
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• 2020

Multicollinearity is a common problem in linear regression models when two or more regressors are highly correlated, which yields some serious problems for the ordinary least square estimates of the parameters as well as model validation and interpretation. In this paper, first the problem of multicollinearity and its subsequent effects on the linear regression along with some important measures for detecting multicollinearity is reviewed, then the role of eigenvalues and eigenvectors in detecting multicollinearity are bolded. At the end a real data set is evaluated for which the fitted linear regression models is investigated for multicollinearity diagnostics.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.2040-2044
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• 2008

Recently, many safety measures are developing for the prevention of human error, which is main factors of railway accident. For the efficient management of human factors, many expertise on design, conditions, safety culture and staffing are required. But current safety management activities on safety critical works are focused on training, due to the limited resource and information. In order to establish railway human factors management, a systematic review model is required. Based on system engineering and nuclear industry model, a program review model is proposed in this study. The model includes operating experience review, task analysis, staffing and qualification, human reliability analysis, huma-system interface design, procedure development, training program, verification and validation, implementation and monitoring. Results can be applied for the review of safety measures relating to human factors.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.47-56
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• 2019

Although the weapon systems are becoming more diverse and complex, they are progressing in a short development period and a longer test and evaluation period. The more difficult the given environment is, the more efforts and performance of quantitative target values can be made by development agencies to carry out stable projects. However, these target values of the Integrated Logistics Support are not specified in the requirements and being set during the system development phase. In this paper, application of MOEs, MOPs and TPMs for ILS are presented and provided the basis for carrying out systematic Verification & Validation activities. As a result that MOEs of the ILS were chosen as Availability and MOPs as Mission Reliability, Logistics Reliability, Maintainability and Supportability and TPMs as MTBF, MTBCF, MTTR and so on. In particular, it is appropriate tailoring and apply the TPMs considering the cost, schedule, scope of work and characteristics of the project.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.101-113
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• 2013

Although the methodological literature is replete with advice regarding the development and validation of multi-item scales based on reflective measures, the issue of index construction using formative measures has received little attention. The aim of this paper is to enhance researchers' understanding of formative measures of high-order factor and assist them in their index construction efforts. This article is also to provide some insights into the nature of formative indicators for researchers to reach an informed choice as to the appropriate high order formative measurement model for their needs. We first provide a brief background on formative indicators, drawing from the limited and fragmented literature on the topic. Next we give an example of constructing an index based on actual survey data and highlight the procedures used to assess its quality. We conclude the article with some thoughts about the use of indexes in empirical studies.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.45-55
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• 2022

The size of the cryptocurrency market is growing. For example, market capitalization of bitcoin exceeded 500 trillion won. Accordingly, many studies have been conducted to predict the price of cryptocurrency, and most of them have similar methodology of predicting stock prices. However, unlike stock price predictions, machine learning become best model in cryptocurrency price predictions, conceptually cryptocurrency has no passive income from ownership, and statistically, cryptocurrency has at least three times higher liquidity than stocks. Thats why we argue that a methodology different from stock price prediction should be applied to cryptocurrency price prediction studies. We propose Reverse Walk-forward Validation (RWFV), which modifies Walk-forward Validation (WFV). Unlike WFV, RWFV measures accuracy for Validation by pinning the Validation dataset directly in front of the Test dataset in time series, and gradually increasing the size of the Training dataset in front of it in time series. Train data were cut according to the size of the Train dataset with the highest accuracy among all measured Validation accuracy, and then combined with Validation data to measure the accuracy of the Test data. Logistic regression analysis and Support Vector Machine (SVM) were used as the analysis model, and various algorithms and parameters such as L1, L2, rbf, and poly were applied for the reliability of our proposed RWFV. As a result, it was confirmed that all analysis models showed improved accuracy compared to existing studies, and on average, the accuracy increased by 1.23%p. This is a significant improvement in accuracy, given that most of the accuracy of cryptocurrency price prediction remains between 50% and 60% through previous studies.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.391-401
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• 2020

This study verified the reliability and validity of the Korean version of the Student Career Construct Inventory(K-SCCI) that was translated into Korean language from the Student Career Construct Inventory (SCCI) developed by Savickas et al.(2018). To achieve this, this study conducted item content analysis, exploratory factor analysis, confirmatory factor analysis, and criterion-related validity in 530 university students. As a result of item content analysis and exploratory factor analysis, it was found that 4 factor models and 18 items were the most appropriate in K-SCCI. The 4 factors were named as crystallizing a vocational self-concept, exploring to gather information about occupations, deciding to commit to an occupational choic, and preparing to implement that choice. As a result of confirmatory factor analysis to verify the goodness-of-fit of the 4 factor models, it appeared to be appropriate. As a result of analyzing the correlation with related measures to verify the criterion-related validity of measures, it was found that student career construct was negatively correlated with employment anxiety but positively correlated with career adaptability.