• Title/Summary/Keyword: Probability and statistics

Search Result 1,187, Processing Time 0.03 seconds

Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM0 III

  • Ko, Mihye;Shim, Miyoung;Lee, Sang-Min;Kim, Yujin;Yoon, Soyoung
    • Acute and Critical Care
    • /
    • v.33 no.4
    • /
    • pp.216-221
    • /
    • 2018
  • Background: In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model $(MPM)_0$ III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients. Methods: The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and $MPM_0$ III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis. Results: For the APACHE IV, SAPS 3, $MPM_0$ III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for $MPM_0$ III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and $MPM_0$ III (chi-square, 11.128; P=0.133). Conclusions: APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients.

Analysis of Sexual Behaviors among Adults in Korea: Results from the "Korean National Survey on Sexual Consciousness"

  • Sun Tae Ahn;Jong Wook Kim;Hong Seok Park;Hyun Jung Kim;Heung Jae Park;Hyeong Sik Ahn; Sung Won Lee;Du Geon Moon
    • The World Journal of Men's Health
    • /
    • v.39 no.2
    • /
    • pp.366-375
    • /
    • 2021
  • Purpose This study aimed to understand the characteristics of sexual behaviors among Korean adults to facilitate the development of strategies and policies focused on sexual health in groups categorized by sociodemographic characteristics. Materials and Methods A nationally representative probability sample of 2,500 individuals (1,273 men and 1,227 women) aged 18-69 years obtained using a stratified multiple-stage sampling method based on Statistics Korea (KOSTAT) participated in a cross-sectional online survey. The survey consisted of structured questionnaires comprising questions on demographic information, lifetime sexual behavior, and sexual behavior in the previous 12 months. The mean age at first sexual intercourse was lower in men than in women (21.9±4.4 vs. 24.1±4.4 years, p=0.001). The overall prevalence rate of sexual events with casual partners within previous 12 months was 13.1% (95% confidence interval [CI], 11.6%-14.5%). It was found to more commonly exist among lower age groups and men. The overall regular condom use rates with relationship partner and casual partner were 14.8% (95% CI, 13.2%-16.4%) and 39.6% (95% CI, 33.9%-45.3%), respectively. Condom use rate with casual partners among 20s and 30s men was 51.2%. Overall, only 10.4% of the respondents had received sexual education about sexually transmitted infections. This study provided contemporary sexual behaviors in Korean adults, and identified socio-demographic factors that seem to influence sexual behaviors. Low condom use rates and low rate of receiving sexual education were concerns. The result of this study would be useful to health professionals to formulate policies and strategies related to sexual health.

An analysis on marine casualties of fishing vessel by FTA method (결함수 분석 (FTA) 기법을 이용한 어선 해양 사고 분석)

  • KIM, Su-Hyung;KIM, Hyung-Suk;KANG, Il-Kwon;KIM, Wook-Sung
    • Journal of the Korean Society of Fisheries and Ocean Technology
    • /
    • v.53 no.4
    • /
    • pp.430-436
    • /
    • 2017
  • The most frequent occurring and the serious marine casualties in fishing vessels are the collision in statistics from Korea Maritime Safety Tribunal (2008-2015). Collisions are is given a great deal of weight in all marine casualties, and the main cause of collisions is the negligence of watching. From this point of view, this study deals with the collision and its immediate cause, the negligence of watching which are main factors on the indirect causes. Basic analyzing data was gathered from the questionnaire made by experts of sea service part, and analyzed by using the fault tree analysis (FTA). From the result of the study, the occurrent probability of the negligence of watching in the collision due to the indirect causes occupied 64.9%, and its probability caused by the man factors was less than the other factors; i.e. the media factors and the management factors. For the reduction of the negligence of watching in the collision from this study, it needs an effort to remove not only the man factors, but also the media factors and management factors.

Study on Timber Yield Regulation Method using Probability Density Function (확률밀도함수를 이용한 목재수확조절법 연구)

  • Park, Jung-Mook;Lee, Jung-Soo;Lee, Ho-Sang;Park, Jin-Woo
    • Journal of Korean Society of Forest Science
    • /
    • v.109 no.4
    • /
    • pp.504-511
    • /
    • 2020
  • This study estimated planned felling volumes to set targets for management planning of nationwide country-owned forests. Estimates were made using timber harvest prediction methods that use probability density functions, including area weighting (AW), area ratio weighting (ARW), and sample area change ratio weighting (SCRW). Country-owned forest areas in 2010 and 2015 were used to estimate planned felling volumes, as shown in basic forest statistics, and calculations were made assuming that the felling areas were the changes in the forest area over the 5-year period. For the age classes of V-VI, the average felling ages for AW, ARW, and SCRW were 5.41, 5.56, and 5.37, respectively, and the felling areas were 594,462, 586,704, and 580,852 ha, respectively, with ARW reaching closest to the actual changes. The actual changes in the areas and chi-squared test results were most stable with the SCRW method. This study showed that SCRW was more adequate than AW and ARW as a method to predict timber harvests for forest management planning.

Analysis of Research Trends in SIAM Journal on Applied Mathematics Using Topic Modeling (토픽모델링을 활용한 SIAM Journal on Applied Mathematics의 연구 동향 분석)

  • Kim, Sung-Yeun
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.21 no.7
    • /
    • pp.607-615
    • /
    • 2020
  • The purpose of this study was to analyze the research status and trends related to the industrial mathematics based on text mining techniques with a sample of 4910 papers collected in the SIAM Journal on Applied Mathematics from 1970 to 2019. The R program was used to collect titles, abstracts, and key words from the papers and to analyze topic modeling techniques based on LDA algorithm. As a result of the coherence score on the collected papers, 20 topics were determined optimally using the Gibbs sampling methods. The main results were as follows. First, studies on industrial mathematics were conducted in a variety of mathematics fields, including computational mathematics, geometry, mathematical modeling, topology, discrete mathematics, probability and statistics, with a focus on analysis and algebra. Second, 5 hot topics (mathematical biology, nonlinear partial differential equation, discrete mathematics, statistics, topology) and 1 cold topic (probability theory) were found based on time series regression analysis. Third, among the fields that were not reflected in the 2015 revised mathematics curriculum, numeral system, matrix, vector in space, and complex numbers were extracted as the contents to be covered in the high school mathematical curriculum. Finally, this study suggested strategies to activate industrial mathematics in Korea, described the study limitations, and proposed directions for future research.

Spatial Analysis for Mean Annual Precipitation Based On Neural Networks (신경망 기법을 이용한 연평균 강우량의 공간 해석)

  • Sin, Hyeon-Seok;Park, Mu-Jong
    • Journal of Korea Water Resources Association
    • /
    • v.32 no.1
    • /
    • pp.3-13
    • /
    • 1999
  • In this study, an alternative spatial analysis method against conventional methods such as Thiessen method, Inverse Distance method, and Kriging method, named Spatial-Analysis Neural-Network (SANN) is presented. It is based on neural network modeling and provides a nonparametric mean estimator and also estimators of high order statistics such as standard deviation and skewness. In addition, it provides a decision-making tool including an estimator of posterior probability that a spatial variable at a given point will belong to various classes representing the severity of the problem of interest and a Bayesian classifier to define the boundaries of subregions belonging to the classes. In this paper, the SANN is implemented to be used for analyzing a mean annual precipitation filed and classifying the field into dry, normal, and wet subregions. For an example, the whole area of South Korea with 39 precipitation sites is applied. Then, several useful results related with the spatial variability of mean annual precipitation on South Korea were obtained such as interpolated field, standard deviation field, and probability maps. In addition, the whole South Korea was classified with dry, normal, and wet regions.

  • PDF

Color Image Segmentation Based on Morphological Operation and a Gaussian Mixture Model (모폴로지 연산과 가우시안 혼합 모형에 기반한 컬러 영상 분할)

  • Lee Myung-Eun;Park Soon-Young;Cho Wan-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.43 no.3 s.309
    • /
    • pp.84-91
    • /
    • 2006
  • In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

Predicting Construction Project Cost using Sensitivity Analysis in Stochastic Project Scheduling Simulation (SPSS) (확률 통계적 일정 시뮬레이선 - 민감도 분석을 이용한 최종 공사비 예측)

  • Lee Dong-Eun;Park Chan-Sik
    • Korean Journal of Construction Engineering and Management
    • /
    • v.6 no.4 s.26
    • /
    • pp.80-90
    • /
    • 2005
  • Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

BAYES EMPIRICAL BAYES ESTIMATION OF A PROPORT10N UNDER NONIGNORABLE NONRESPONSE

  • Choi, Jai-Won;Nandram, Balgobin
    • Journal of the Korean Statistical Society
    • /
    • v.32 no.2
    • /
    • pp.121-150
    • /
    • 2003
  • The National Health Interview Survey (NHIS) is one of the surveys used to assess the health status of the US population. One indicator of the nation's health is the total number of doctor visits made by the household members in the past year, There is a substantial nonresponse among the sampled households, and the main issue we address here is that the nonrespones mechanism should not be ignored because respondents and nonrespondents differ. It is standard practice to summarize the number of doctor visits by the binary variable of no doctor visit versus at least one doctor visit by a household for each of the fifty states and the District of Columbia. We consider a nonignorable nonresponse model that expresses uncertainty about ignorability through the ratio of odds of a household doctor visit among respondents to the odds of doctor visit among all households. This is a hierarchical model in which a nonignorable nonresponse model is centered on an ignorable nonresponse model. Another feature of this model is that it permits us to "borrow strength" across states as in small area estimation; this helps because some of the parameters are weakly identified. However, for simplicity we assume that the hyperparameters are fixed but unknown, and these hyperparameters are estimated by the EM algorithm; thereby making our method Bayes empirical Bayes. Our main result is that for some of the states the nonresponse mechanism can be considered non-ignorable, and that 95% credible intervals of the probability of a household doctor visit and the probability that a household responds shed important light on the NHIS.

An Imputation for Nonresponses in the Survey on the Rural Living Indicators (농촌생활지표조사에서 무응답 대체 : 사례)

  • Cho, Young-Sook;Chun, Young-Min;Hwang, Dae-Yong
    • The Korean Journal of Applied Statistics
    • /
    • v.21 no.1
    • /
    • pp.95-107
    • /
    • 2008
  • Survey on the rural living indicators was the statistic approved from National Statistical Office and the survey executed by rural resources development institute. This study was used the raw data of survey on the rural living indicators in 2005. After editing procedure for raw data, we were studied 1,582 households which is acquired through elimination of case included nonresponses, and imputed a nonresponses of 15 item selected from 146 item. The imputation methods and efficiency of imputation for simulation was adapted differently from type of data. For continuous data, we imputed the nonresponses with mean imputation, regression imputation, adjusted grey-based k-NN imputation(DU, DW, WU, WW) and compared the results with RMSE. For categorical data, we imputed the nonresponses with mode method, probability imputation, conditional mode method, conditional probability method, hot-deck imputation, and compared the results with Accuracy. By the results, regression imputation and adjusted grey-based k-NN imputation appropriated for continuous data and hot-deck imputation appropriated for categorical data.