• Journal of Preventive Medicine and Public Health
• /
• 제46권2호
• /
• pp.96-104
• /
• 2013

Objectives: The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures. Methods: This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010. Results: Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses. Conclusions: Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.

• Communications for Statistical Applications and Methods
• /
• 제7권3호
• /
• pp.945-953
• /
• 2000

Since early 1960s, when the telephone survey was used in the research area for he first tie, there has been existed various methods to gather the information by survey. The existing survey methodology called PAPI(Paper-And-Pen Interveiw), due to the appearance of Personal Computer, might well be developed progressively. Mid-1980s, Internet was advanced remarkably in terms of technology. from early 1990s, in addition it served as a stepping-stone for progressive collecting method. Internet Survey is now called WWW Survey and expected that it will substitute for most surveys from now on. We explain the role and the characteristics for Internet Survey as one of he various data collecting methods. Furthermore, we draw the futures about questionnaires, data collecting and statistical analysis with it.

• 가족자원경영과 정책
• /
• 제6권1호
• /
• pp.35-51
• /
• 2002

This study is the basic step of including the economical value of household labor into the existing GDP. Therefore this study analyzes statistical data; $\mathbb{\ulcorner}$Economical Active Population Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Time Used Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Basic Wage Structural Survey$\mathbb{\lrcorner}$, and $\mathbb{\ulcorner}$City Household Survey$\mathbb{\lrcorner}$ for that step and will help people to reconsider the importance of the economical value household work. Economical Active Population Survey classifies housework as economically nonoproductive activity Time Use Survey does not have an clear classification for action. Basic Wage Structural Survey must give subdividable information on wage. City Household Survey should include more details and more data of household durables.

• 한국BIM학회 논문집
• /
• 제12권1호
• /
• pp.72-80
• /
• 2022

It has become mandatory to designs by BIM in construction. It is urgent to make accurate decisions through the linkage between complex and various types of data in projects. In particular, block-chain based data sharing process (using BIM files, general construction submitted files) is essential to support reliable decision making in complex data flood systems. Prior to developing data sharing system based on block-chain, in this paper, a data linkage method is proposed so that practitioners can simultaneously utilize existing construction information and BIM data. Examples are shown based on the construction classification system and file expression, and incentive strategies are explored through a survey so that heterogeneous information can be used at the same time in overall projects.

• 웰빙융합연구
• /
• 제4권4호
• /
• pp.1-14
• /
• 2021

Purpose: This study aims to measure the level of satisfaction with the overall education of current students, who are major consumers of education by department at the Health Care Convergence University, and to establish development strategies such as improving education quality and satisfaction by deriving problems and improvements. Research design, data and methodology: This study drew conclusions through secondary data analysis based on data surveyed by the Educational Performance Management Center of a university in the academic year of 2020. The target of the education consumer satisfaction survey was 470 students of the College in the academic year 2020. Frequency analysis and correlation analysis were applied to the data using the statistical package program SPSS 25 version. Results: In the major curriculum satisfaction survey, the department with the highest score was optics and optics, 4.11, and the department with the lowest score was medical IT, 3.29. Conclusions: The department with the highest correlation in the correlation analysis result of the demand survey by department was the Department of Medical Management and the Department of Medical IT, with a correlation coefficient r=0.984, and the lowest correlation in the correlation analysis result of the demand survey by department was the Department of Medical IT and Dental Hygiene, with a correlation coefficient r= -0.085.

• 한국BIM학회 논문집
• /
• 제10권3호
• /
• pp.33-42
• /
• 2020

Recently, in the smart construction field, it is possible to construct spatial information of 3D data base quickly and accurately using drones, LiDARs and ARs,. Most public ordering institutions are pushing for the efficiency of construction work through establishing and announcing road maps and guidelines for utilizing BIM for the entire life cycle of construction. However, in most policies, the impact of 3D data on the entire life cycle is limited by only partially constructing and utilizing 3D data or by being mentioned. In addition, many public institutions, construction companies and planning companies did not actively utilize survey information during the actual construction phase, despite the possibility of using 3D survey information. In order to confirm the utilization of survey information, a total of eight private construction companies were selected and interviewed by experts. The analysis shows that most of companies lack the performance of drone measurements or have a lack of awareness of advantages, and among them, construction companies are relatively active. Based on these opinions, this study examined the usability of surveying information and examined measures to expand the utilization of survey information in legal and institutional aspects, technology development aspects and industrial development.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2001년도 봄 학술발표회 논문집
• /
• pp.81-88
• /
• 2001

Electrical resistivity is one of physical property of the earth and measured by electrical resistivity survey, electrical resistivity logging and laboratory test. Recently, electrical resistivity is widely used in determination of rock quality in road and railway tunnel design. To get more reliable rock quality data from electrical resistivity, it needs a lot of test and study on correlation of resistivity and rock quality. Firstly, we did rock property test in laboratory, such as uniaxial compressive strength(UCS), p wave velocity, Young's modulus and electrical resistivity. We correlate each test results and we found out that electrical resistivity has exponentially related to UCS and P wave velocity and linearly related to Young's modulus. And we accomplished electrical resistivity survey in field site and carried out electrical resistivity logging at in-situ area. Also we peformed rock classification, such as RQD, RMR and Q-system and we correlate electrical resistivity to rock classification results. We found out that electrical resistivity logging data are highly correlate to RQD, Q and RMR. Also we found out that electrical resistivity survey data are lower than electrical resistivity logging data when there are faults or fractures. And it cause electrical resistivity survey data to lowly correlate to RQD, Q and RMR.

• Communications for Statistical Applications and Methods
• /
• 제9권3호
• /
• pp.853-864
• /
• 2002

In the analysis of categorical data subject to misclassification errors, the observed cell proportions are adjusted by a misclassification probabilities and estimates of variances are adjusted accordingly. In this case, it is important to determine the extent to which misclassification probabilities are homogeneous within a population. This paper considers methods to evaluate the power of chi-squared tests for homogeneity with complex survey data subject to misclassification errors. Two cases are considered: adjustment with homogeneous misclassification probabilities; adjustment with heterogeneous misclassification probabilities. To estimate misclassification probabilities, logistic regression method is considered.

• Journal of the Korean Data and Information Science Society
• /
• 제18권4호
• /
• pp.1179-1189
• /
• 2007

In this paper, we estimate the proportion of individuals having health insurance in a given year for several small domains cross-classified by age, sex and other demographic characteristics using the data provided by the National Center for Health Statistics(NCHS). We employ Bayesian as well as frequentist methodology to obtain small domain estimates and the associated measures of precision. One of the new features of our study is that we utilize the survey weights along with the model to derive the small domain estimates.

• Journal of Computing Science and Engineering
• /
• 제5권3호
• /
• pp.257-268
• /
• 2011

Machine learning and data mining have found many applications in biological domains, where we look to build predictive models based on labeled training data. However, in practice, high quality labeled data is scarce, and to label new data incurs high costs. Transfer and multitask learning offer an attractive alternative, by allowing useful knowledge to be extracted and transferred from data in auxiliary domains helps counter the lack of data problem in the target domain. In this article, we survey recent advances in transfer and multitask learning for bioinformatics applications. In particular, we survey several key bioinformatics application areas, including sequence classification, gene expression data analysis, biological network reconstruction and biomedical applications.