• Survey Research
• /
• v.11 no.3
• /
• pp.33-55
• /
• 2010

In this study, we newly define the Total Survey Error(TSE) in exit poll and investigate the TSEs of the exit poll survey for the 18th general election of 2008 to analyse the cause of the exit poll prediction error. To explore the main cause and effect of the total survey error, the total survey error was divided by the sampling error which comes from sampling process of poll stations and the non-sampling error which comes from selecting voter and collecting responses from sampled voters in each electoral district. We consider the relationship between non-response rates and total survey error as well as non-sampling error. Also, we study the representativeness of the exit poll sample by comparing the sex/age distribution of the exit poll data and the National Election Commission poll data.

• The Korean Journal of Applied Statistics
• /
• v.35 no.4
• /
• pp.485-499
• /
• 2022

Controlling the total survey error including sampling error and non-sampling error is very important in sampling design. Non-sampling error caused by non-response accounts for a large proportion of the total survey error. Many studies have been conducted to handle non-response properly. Recently, a lot of non-response imputation methods using machine learning technique and traditional statistical methods have been studied and practically used. Most imputation methods assume MCAR(missing completely at random) or MAR(missing at random) and few studies have been conducted focusing on MNAR (missing not at random) or NN(non-ignorable non-response) which cause bias and reduce the accuracy of imputation. In this study, we propose a non-response imputation method that can be applied to non-ignorable non-response. That is, we propose an imputation method to improve the accuracy of estimation by removing the bias caused by NN. In addition, the superiority of the proposed method is confirmed through small simulation studies.

• Journal of Korean Society on Water Environment
• /
• v.30 no.6
• /
• pp.585-595
• /
• 2014

The temporal trends of the prioritized toxic water pollutants generated and discharged from the industrial facilities in the Geum-River basin, Korea were analyzed with the results of the nationwide Water Pollution Source Survey conducted in 2001 - 2012. The statistical results indicated rapid increase in the volume of raw toxic wastewaters whereas the amount of each toxic pollutant kept fluctuating for 12 years. Serious discrepancies in the survey data of the same type of industries demonstrated a low reliability of the survey result, which stemmed from several error factors. A unit-load for each type of industrial facility was devised to estimate the amount of prioritized toxic water pollutant based on the total volume of industrial wastewater generated from the same type of industrial facilities. The supplementary measures with an effective permit issuance policy and adding survey parameters of terminal wastewater treatment plants to use them as references to the Water Pollution Source Survey were suggested as means to minimize the errors associated with the false reports from the industries.

• Quality Improvement in Health Care
• /
• v.18 no.1
• /
• pp.57-70
• /
• 2012

Background : The purpose of this study was to understand healthcare workers' perception of patient safety culture and medical error reporting to provide basic resources for the settlement of patient safety culture in medical institutions in Korea. Methods : For this purpose, convenience sampling by self-selection was applied to healthcare workers at a university hospital in Gyeonggi-do and a total of 482 people responded. The survey used the translated version of AHRQ in Korean and distributed through the Intranet system of the hospital. Result : The ratio of positive response was low overall. Among the responses, the response for 'Nonpunitive Response to Error' was the lowest at 17.7%, followed by the responses for 'Staffing' at 21.3%, 'Handoffs & Transitions' at 32.9%, and 'Communication Openness' at 44.3%. In result of surveying whether the responders have reported patient safety incidents during the past 12 months, 68.3% responded 'not once.' Conclusion : The perception of healthcare workers' patient safety culture and medical error reporting, when compared to AHRQ, was lower overall. It is important for healthcare workers to pay greater attention to patient safety to create a safe hospital culture where they do not punish or criticize related individuals or departments.

• Quality Improvement in Health Care
• /
• v.22 no.2
• /
• pp.75-90
• /
• 2016

Objectives: This study measures the level of cognition of employee's patient safety culture and evaluates the current level through comparing the results to external levels. Ultimately it is performed to construct a strategic improvement plan through the basic database for patient's safety culture. Methods: A questionnaire survey of self reporting type was carried out using structured questionnaire of the patient's safety culture for employees currently employed in a hospital. Total responders was 1,129 and a response rate was 54.6%. The survey results were calculated with a percent positive response, and the current level was evaluated by comparing with the survey results of a hospital (2009 and 2014) and the survey result of The Agency for Healthcare Research and Quality(2014). Results: Sub-dimension of high percent positive response for each area were 'teamwork within hospital units' (80%), 'feedback & communication about error' (73%) and 'supervisor/manager expectations & actions promoting safety' (67%). Meanwhile, 'teamwork across hospital units' (31%), 'hospital management support for patient safety' (29%), 'staffing' (27%) and 'non-punitive response to error' (17%) were relatively low percent positive response. Compared to the survey results of AHRQ (2014) for each area, 'teamwork within hospital units' (80%), 'feedback & communication about error' (73%), 'frequency of event reporting' (66%) were at the top 50% percentile level and the remaining sub-dimensions showed a very low level in the lower 10% percentile area. Conclusion: In order to establish a system for patient safety culture within the hospital and evaluate the effect on this, it is necessary to periodically evaluate the patient's safety culture and establish regulations on hospital safety culture to comply with this.

• Korean Journal of Clinical Laboratory Science
• /
• v.37 no.2
• /
• pp.65-70
• /
• 2005

Those specifications of the CLIA analytical tolerance limits are consistent with the performance goals in Six Sigma Quality Management. Six sigma analysis determines performance quality from bias and precision statistics. It also shows if the method meets the criteria for the six sigma performance. Performance standards calculates allowable total error from several different criteria. Six sigma means six standard deviations from the target value or mean value and about 3.4 failures per million opportunities for failure. Sigma Quality Level is an indicator of process centering and process variation total error allowable. Tolerance specification is replaced by a Total Error specification, which is a common form of a quality specification for a laboratory test. The CLIA criteria for acceptable performance in proficiency testing events are given in the form of an allowable total error, TEa. Thus there is a published list of TEa specifications for regulated analytes. In terms of TEa, Six Sigma Quality Management sets a precision goal of TEa/6 and an accuracy goal of 1.5 (TEa/6). This concept is based on the proficiency testing specification of target value +/-3s, TEa from reference intervals, biological variation, and peer group median mean surveys. We have found rules to calculate as a fraction of a reference interval and peer group median mean surveys. We studied to develop total error allowable from peer group survey results and CLIA 88 rules in US on 19 items TP, ALB, T.B, ALP, AST, ALT, CL, LD, K, Na, CRE, BUN, T.C, GLU, GGT, CA, phosphorus, UA, TG tests in chematology were follows. Sigma level versus TEa from peer group median mean CV of each item by group mean were assessed by process performance, fitting within six sigma tolerance limits were TP ($6.1{\delta}$/9.3%), ALB ($6.9{\delta}$/11.3%), T.B ($3.4{\delta}$/25.6%), ALP ($6.8{\delta}$/31.5%), AST ($4.5{\delta}$/16.8%), ALT ($1.6{\delta}$/19.3%), CL ($4.6{\delta}$/8.4%), LD ($11.5{\delta}$/20.07%), K ($2.5{\delta}$/0.39mmol/L), Na ($3.6{\delta}$/6.87mmol/L), CRE ($9.9{\delta}$/21.8%), BUN ($4.3{\delta}$/13.3%), UA ($5.9{\delta}$/11.5%), T.C ($2.2{\delta}$/10.7%), GLU ($4.8{\delta}$/10.2%), GGT ($7.5{\delta}$/27.3%), CA ($5.5{\delta}$/0.87mmol/L), IP ($8.5{\delta}$/13.17%), TG ($9.6{\delta}$/17.7%). Peer group survey median CV in Korean External Assessment greater than CLIA criteria were CL (8.45%/5%), BUN (13.3%/9%), CRE (21.8%/15%), T.B (25.6%/20%), and Na (6.87mmol/L/4mmol/L). Peer group survey median CV less than it were as TP (9.3%/10%), AST (16.8%/20%), ALT (19.3%/20%), K (0.39mmol/L/0.5mmol/L), UA (11.5%/17%), Ca (0.87mg/dL1mg/L), TG (17.7%/25%). TEa in 17 items were same one in 14 items with 82.35%. We found out the truth on increasing sigma level due to increased total error allowable, and were sure that the goal of setting total error allowable would affect the evaluation of sigma metrics in the process, if sustaining the same process.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.117-123
• /
• 2013

The purpose of this research is to suggest the reasonable method of Network RTK surveying in future cadastral re-survey project through the accuracy analysis about Network RTK surveying achievement and the conventional TS-based confirmation surveying. To achieve it, we selected the experiment places and succeeded in achieving the result by Network RTK surveying about total of 307 parcel boundary point. We compared it with the result of confirmation surveying for cadastral, and it was shown that total connection errors of RMSE was ${\pm}0.1028m$ and total 48 places exceeded in the cadastral re-survey allowable error tolerance. The research suggested the practical alternatives in cadastral re-survey project after the comprehensive evaluation of those analysis results. Therefore, the author suggested development and adoptation of integrated electronic plane table surveying method. Moreover, we suggested unifying the first parcel boundary point method into the total station surveying and adopt the Network RTK surveying on the cadastral surveying inspection.

• Journal of Ecology and Environment
• /
• v.41 no.4
• /
• pp.114-119
• /
• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• The Korean Journal of Applied Statistics
• /
• v.31 no.5
• /
• pp.587-597
• /
• 2018

Procedures, such as sampling technique, survey method, and questionnaire preparation, are required in order to obtain sample data in accordance with the purpose of a survey. An important procedure is the decision of the sample size formula. The sample size formula is determined by setting the target error and total cost according to the sampling method. In this paper, we propose a sample size formula using population changes over time, estimation error of the previous time and response rate of past data when the target error and the expected response rate are given in the simple random sampling. In actual research, we use estimators that apply complex weights in addition to design-based weights. Therefore, we induce a sample size formula for estimators using design-based weights and nonresponse adjustment coefficients, that can be a formula that reflects differences in response rates when survey methods are changed over time. In addition, we use simulations to compare the proposed formula with the existing sample size formula.

• Journal of Fisheries and Marine Sciences Education
• /
• v.28 no.6
• /
• pp.1812-1821
• /
• 2016

The purpose of this study is to survey input data error of ship automatic identification system (AIS) and suggest its improvement. The effects of AIS were observed. Input data error of AIS was investigated by dividing it into dynamic data, static data by targeting actual ships and its improvement method was suggested. The findings are as follows. Looking into accidents before and after AIS is enforced to install on the ship, total collision were decreased after AIS installed. Static data error of AIS took place mainly in the case that ship name, call sign, MMSI, IMO number, ship type, location of antenna (ship length and width) were wrongly input or those data were not input initially. Dynamic data error of AIS was represented by input error of ship's heading. As errors of voyage related data take place as well, confusion is made in sailing or ship condition. Counter measures against the above are as follows. First, reliability of AIS data information should be improved. Second, incessant concern and management should be made on the navigation officers.