• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.424-427
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• 2022

A retrospective record-linkage study (RLS) based on medical records containing drug prescription histories involves immortal time bias (ITB). Thus, it is necessary to control for this bias in the research planning and analysis stages. Furthermore, a summary of a meta-analysis including RLSs that did not control for ITB showed that specific drugs had a preventive effect on the occurrence of the disease. Previous meta-analytic results of three systematic reviews evaluating the association between statin intake and gastric cancer risk showed that the summary hazard ratio (sHR) of the RLSs was lower than 1 and was statistically significant. We should consider the possibility of ITB in the sHR of RLSs and interpret the results carefully.

• Survey Research
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• v.12 no.3
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• pp.25-48
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• 2011

In this paper, we overview the sample design, sampling error, non-response rate and prediction errors of the exit poll conducted for 2010 local elections and discusses how to detect a prediction bias in exit poll. To investigate the bias problem in exit poll in regional(Si-Do) level, we analyze exit poll data for 2007 presidential election and 2006 local elections as well as 2010 local elections in Korea. The measure of predictive accuracy A proposed by Martin et al.(2005) is used to assess the exit poll bias. The empirical studies based on three exit polls clearly show that there exits systematic bias in exit poll and the predictive bias of candidates affiliated to conservative party (such as Hannara-Dang) is serious in the specific regions. The result of this study on systematic bias will be very useful to improving the exit poll methodology in Korea.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.30 no.2
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• pp.1-18
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• 2017

Objectives : This review aims to evaluate a risk of bias by risk of bias tool and RoBANS(Risk of Bias Assessment tool for Non-randomized Study) tool for clinical trial papers proving treatment effect of Korean medicines to alopecia and provides the newest reason of effectiveness of herbs to alopecia. Methods : Data were collected through electronic database including NDSL, KISS, KMBASE, Koreantk, OASIS, KoreaMed, KISTI, Pubmed, Cochrane CENTRAL and CINAHL. Two experts in Oriental Medicine assessed risk of bias of randomized controlled trials by Cochrane group's Risk of Bias tool and non-randomized controlled trials by RoBANS tool after searching, reviewing and selecting papers. Results : Total number of selected trials is 20 including 4 randomized controlled trial, 13 non-randomized controlled trials and 3 case reports. This study evaluate the risk of bias of 17 papers including 4 randomized controlled trials and 13 non-randomized controlled trials except 3 case reports by risk of bias tool and RoBANS tool. All papers of randomized controlled trials are evaluated unclear for random sequence generation and allocation concealment as there are no word on them. And all papers of non-randomized controlled trials are evaluated unclear for blinding of outcome assessments and relatively low for others. Conclusions : Korean medicine intervention can be an effective for treatment in alopecia. It was evaluated by hair density, thickness and expert panel assessment of photographs and all results are statistically significant. But enhancing levels of evidence, we must try to reduce bias in researches and report a safety, protocol and IRB.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.589-601
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• 2019

Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.453-462
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• 2021

As the frequency of localized heavy rainfall has increased during recent years, the importance of high-resolution radar data has also increased. This study aims to correct the bias of Dual Polarization radar that still has a spatial and temporal bias. In many studies, various statistical techniques have been attempted to correct the bias of radar rainfall. In this study, the bias correction of the S-band Dual Polarization radar used in flood forecasting of ME was implemented by a Convolutional Autoencoder (CAE) algorithm, which is a type of Convolutional Neural Network (CNN). The CAE model was trained based on radar data sets that have a 10-min temporal resolution for the July 2017 flood event in Cheongju. The results showed that the newly developed CAE model provided improved simulation results in time and space by reducing the bias of raw radar rainfall. Therefore, the CAE model, which learns the spatial relationship between each adjacent grid, can be used for real-time updates of grid-based climate data generated by radar and satellites.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.94-101
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• 2016

Satellite data for remote sensing technology has limitations, especially with visible range sensor, cloud and/or other environmental factors cause missing data. In this study, using land surface temperature data from the MODerate resolution Imaging Spectro-radiometer(MODIS), we developed retrieving methods for satellite missing data and developed three methods; mean bias, regression analysis and local variation method. These methods used the previous day data as reference data. In order to validate these methods, we selected a specific measurement ratio using artificial missing data from 2014 to 2015. The local variation method showed low accuracy with root mean square error(RMSE) more than 2 K in some cases, and the regression analysis method showed reliable results in most cases with small RMSE values, 1.13 K, approximately. RMSE with the mean bias method was similar to RMSE with the regression analysis method, 1.32 K, approximately.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.425-433
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• 2011

Reject inference in credit scoring is a statistical approach to adjust for nonrandom sample bias due to rejected applicants. Function estimation approaches are based on the assumption that rejected applicants are not necessary to be included in the estimation, when the missing data mechanism is missing at random. On the other hand, the density estimation approach by using mixture models indicates that reject inference should include rejected applicants in the model. When mixture models are chosen for reject inference, it is often assumed that data follow a normal distribution. If data include missing values, an application of the normal mixture model to fully observed cases may cause another sample bias due to missing values. We extend reject inference by a multivariate normal mixture model to handle incomplete characteristic variables. A simulation study shows that inclusion of incomplete characteristic variables outperforms the function estimation approaches.

• Journal of the Korea Computer Graphics Society
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• v.17 no.2
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• pp.1-9
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• 2011

In recent researches, several LOD techniques are used for real-time visualization of large sized terrain data. However, during mesh simplification, geometry popping may occur in consecutive frames, because of the geometric error. We propose an efficient method for reducing the geometry popping using roughness map and bias map. A roughness map and a bias map are used to move vertices of the terrain mesh to appropriate position where they minimize the geometry errors. A roughness map and a bias map are represented as a texture suitable for GPU processing. Moving vertices using bias map is processed on the GPU, so the high-speed visualization can be possible.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.1-8
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• 2014

The positions, attitudes, and internal orientation parameters of three line scanners are critical factors in order to acquire the accurate location of objects on the ground. Based on the assumption that positions and attitudes of the sensors are derived either from direct geo-referencing which of using Global Positioning Systems (GPS) and Inertial Navigation Systems (INS), or from indirect geo-referencing which of using Ground Control Points (GCPs), this paper describes on biased effects of Internal Orientation Parameter (IOP) on the ground. The research concentrated on geometrical explanations of effects from different focal length biases on the ground. The Synthetic data was collected by reasonable flight trajectories and attitudes of three line scanners. The result of experiments demonstrated that the focal length bias in case of indirect geo-referencing does not have critical influences on the quality of reconstructed ground space. Also, the relationships between IO parameters and EO parameters were found by the correlation analysis. In fact, the focal length bias in case of the direct geo-referencing caused significant errors on coordinates of reconstructed objects. The RMSE values along the vertical direction and the amount of focal length bias turned out to be almost perfect linear relationship.

• Journal of Haehwa Medicine
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• v.24 no.1
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• pp.15-24
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• 2015

Objectives : This study was carried out to assess the risk of bias of clinical trials on acne treatment with herbal medicine that have been published in Korea. Methods : 7 electronic databases in Korea were searched for clinical trials on acne treatment. Two independent reviewers selected clinical trials on herbal medicine treatment for acne. Selected studies are categorized according to DAMI(Study Design Algorithm for Medical literature of Intervention). RCTs are assessed according to Cochrane RoB(Risk of Bias), non-randomized studies(Before-after studies) are assessed according to RoBANS(Risk of Bias Assessment tool for Non-randomized Study). Results : After selection process, 25 articles are left. Among 25 articles, 3 RCTs and 4 before-after studies are finally included. In RCTs, the proportion of 'unclear' is high in criteria of 'random sequence generation', 'allocation concealment', and 'blinding'. In before-after studies, 'high' is high in criteria of 'blinding for outcome assessment' and 'incomplete outcome data'. Conclusions : Considering the above results of the assessment, it is necessary to conduct more well designed clinical trials on acne treatment with herbal medicine.