• Title, Summary, Keyword: logistic curve

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A Logistic Model Including Risk Factors for Lymph Node Metastasis Can Improve the Accuracy of Magnetic Resonance Imaging Diagnosis of Rectal Cancer

  • Ogawa, Shimpei;Itabashi, Michio;Hirosawa, Tomoichiro;Hashimoto, Takuzo;Bamba, Yoshiko;Kameoka, Shingo
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.2
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    • pp.707-712
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    • 2015
  • Background: To evaluate use of magnetic resonance imaging (MRI) and a logistic model including risk factors for lymph node metastasis for improved diagnosis. Materials and Methods: The subjects were 176 patients with rectal cancer who underwent preoperative MRI. The longest lymph node diameter was measured and a cut-off value for positive lymph node metastasis was established based on a receiver operating characteristic (ROC) curve. A logistic model was constructed based on MRI findings and risk factors for lymph node metastasis extracted from logistic-regression analysis. The diagnostic capabilities of MRI alone and those of the logistic model were compared using the area under the curve (AUC) of the ROC curve. Results: The cut-off value was a diameter of 5.47 mm. Diagnosis using MRI had an accuracy of 65.9%, sensitivity 73.5%, specificity 61.3%, positive predictive value (PPV) 62.9%, and negative predictive value (NPV) 72.2% [AUC: 0.6739 (95%CI: 0.6016-0.7388)]. Age (<59) (p=0.0163), pT (T3+T4) (p=0.0001), and BMI (<23.5) (p=0.0003) were extracted as independent risk factors for lymph node metastasis. Diagnosis using MRI with the logistic model had an accuracy of 75.0%, sensitivity 72.3%, specificity 77.4%, PPV 74.1%, and NPV 75.8% [AUC: 0.7853 (95%CI: 0.7098-0.8454)], showing a significantly improved diagnostic capacity using the logistic model (p=0.0002). Conclusions: A logistic model including risk factors for lymph node metastasis can improve the accuracy of MRI diagnosis of rectal cancer.

Comparative Study on Statistical Packages for Analyzing Logistic Regression - MINITAB, SAS, SPSS, STATA -

  • Kim, Soon-Kwi;Jeong, Dong-Bin;Park, Young-Sool
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.367-378
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    • 2004
  • Recently logistic regression is popular in a variety of fields so that a number of statistical packages are developed for analyzing the logistic regression. This paper briefly considers the several types of logistic regression models used depending on different types of data. In addition, when four statistical packages (MINTAB, SAS, SPSS and STATA) are used to apply logistic regression models to the real fields respectively, their scope and characteristics are investigated.

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Estimation of growth curve in Hanwoo steers using progeny test records

  • Yun, Jae-Woong;Park, Se-Yeong;Park, Hu-Rak;Eum, Seung-Hoon;Roh, Seung-Hee;Seo, Jakyeom;Cho, Seong-Keun;Kim, Byeong-Woo
    • Korean Journal of Agricultural Science
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    • v.43 no.4
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    • pp.623-633
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    • 2016
  • A total of 6,973 steer growth records of Hanwoo breeding bull's progeny test data collected from 1989 to 2015 were analyzed to identify the most appropriate growth curve among three growth curve models (Gompertz, Logistic and von Bertalanffy). The Gompertz growth curve model equation was $W_t=990.5e^{{-2.7479e}^{-0.00241t}}$, the Logistic growth curve model equation was $W_t=772(1+8.3314e^{-0.00475t})^{-1}$, and the von Bertalanffy growth curve model equation was $W_t=1,196.4(1-0.646e^{-0.00162t})^3$. The Gompertz model parameters A, b, and k were estimated to be $990.5{\pm}10.27$, $2.7479{\pm}0.0068$, and $0.00241{\pm}0.000028$, respectively. The inflection point age was estimated to be 421 days and the weight of inflection point was 365.3 kg. The Logistic model parameters A, b, and k were estimated to be $772.0{\pm}4.12$, $8.3314{\pm}0.0453$, and $0.00475{\pm}0.000033$, respectively. The inflection point age was estimated to be 445 days and the weight of inflection point was 385.0 kg. The von Bertalanffy model parameters A, b, and k were estimated to be $1196.4{\pm}18.39$, $0.646{\pm}0.0010$, and $0.00162{\pm}0.000027$, respectively. The inflection point age was estimated to be 405 days and the weight of inflection point was 352.0 kg. Mature body weight of the von Bertalanffy model was 1196.4 kg, the Gompertz model was 990.5 kg, and the Logistic model was 772.0 kg. The difference between actual and estimated weights was similar in the Logistic model and the von Bertalanffy model. The difference between market weight and estimated market weight was the lowest in the Gompertz model. The growth curve using the von Bertalanffy model showed the lowest mean square error.

Reasonability of Logistic Curve on S/W (로지스틱 곡선을 이용한 타당성)

  • Kim, Sun-Il;Che, Gyu-Shik;Jo, In-June
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.1
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    • pp.1-9
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    • 2008
  • The Logistic cone is studied as a most desirable for the software testing effort. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull cure as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing- effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

Comparative Analysis of Predictors of Depression for Residents in a Metropolitan City using Logistic Regression and Decision Making Tree (로지스틱 회귀분석과 의사결정나무 분석을 이용한 일 대도시 주민의 우울 예측요인 비교 연구)

  • Kim, Soo-Jin;Kim, Bo-Young
    • The Journal of the Korea Contents Association
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    • v.13 no.12
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    • pp.829-839
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    • 2013
  • This study is a descriptive research study with the purpose of predicting and comparing factors of depression affecting residents in a metropolitan city by using logistic regression analysis and decision-making tree analysis. The subjects for the study were 462 residents ($20{\leq}aged{\angle}65$) in a metropolitan city. This study collected data between October 7, 2011 and October 21, 2011 and analyzed them with frequency analysis, percentage, the mean and standard deviation, ${\chi}^2$-test, t-test, logistic regression analysis, roc curve, and a decision-making tree by using SPSS 18.0 program. The common predicting variables of depression in community residents were social dysfunction, perceived physical symptom, and family support. The specialty and sensitivity of logistic regression explained 93.8% and 42.5%. The receiver operating characteristic (roc) curve was used to determine an optimal model. The AUC (area under the curve) was .84. Roc curve was found to be statistically significant (p=<.001). The specialty and sensitivity of decision-making tree analysis were 98.3% and 20.8% respectively. As for the whole classification accuracy, the logistic regression explained 82.0% and the decision making tree analysis explained 80.5%. From the results of this study, it is believed that the sensitivity, the classification accuracy, and the logistics regression analysis as shown in a higher degree may be useful materials to establish a depression prediction model for the community residents.

A study on the parameter estimation of S-Shaped Software Reliability Growth Models Using SAS JMP (SAS JMP를 이용한 S형 소프트웨어 신뢰도 성장모델에서의 모수 추정에 관한 연구)

  • 문숙경
    • Journal of the Korean Society for Quality Management
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    • v.26 no.3
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    • pp.130-140
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    • 1998
  • Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

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Development of Traffic Accident Forecasting Model in Pusan (부산시 교통사고예측모형의 개발)

  • 이일병;임현정
    • Journal of Korean Society of Transportation
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    • v.10 no.3
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    • pp.103-122
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    • 1992
  • The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.

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Comparison of Germination Characteristics, and of Logistic and Weibull Functions to Predict Cumulative Germination of Grasses Under Osmotic Water Stress (수분장애시 목초 발아특성 및 누적 발아율 곡선 예측을 위한 Sigmoid 함수들 간의 비교)

  • 이석하;윤선강;백성범;박현구
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.11 no.4
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    • pp.209-214
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    • 1991
  • The germination of seeds is developmentally complex process requiring water uptake, which is regulated by both genotypic and environmental factors. The present study was undertaken to determine the difference in germination characteristics, and to compare the ability of the logistic and Weibull functions to describe the cumulative germination curve when two levels of osmotic potential(0, -5 bar) were put to seeds of alfalfa, tall fescue, orchardgrass, and Kentucky bluegrass. The effects of grass type, osmotic potential, and their interaction on the total germination and coefficient of germination velocity were significant(P<0.01). The Weibull equation for predicting percent cumulative germination curve of alfalfa had significantly lower residuals than the logistic equation regardless of osmotic potential(P<0.01), indicating that the Weibull equation was more efficient than the logistic equation to fit the data of the percent cumulative germination of alfalfa. The rate parameter from the logistic equation was decreased under water stress, whereas the scale and shape parameters were increased. There were significant differences in days to 20% germination estimated from the logistic and Weibull equations.

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Size selectivity of round traps for greenling (Hexagrammos otakii) in the western sea of Korea (원통형 통발에 대한 서해안 쥐노래미 (Hexagrammos otakii)의 망목선택성)

  • 신종근;박해훈
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.39 no.3
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    • pp.174-180
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    • 2003
  • This study investigated the size selectivity of the round traps for greenling (Hexagrammos otakii) in the western sea of Korea. The selection curve for the greenling from the experiments on Oct. 2000 and Ar. 2001 was fitted by Kitahara's method to a polynomial equation and two parameter logistic selection curve. The selectio curve of the latter was more reasonable than that of the former. The equation of selectivity curve obtained using a logistic function with least square method was , s(R)=1/1+exp(-1.1169R+6.4565), where R=1/m, and 1 and m are total length and mesh size, respectively. The size selectivity curve showed that the current regulated mesh size(35mm) in case of the round trap was close to the L50 (37.0mm) of the selection curve for the biological minimum length (21.4cm) of the greenling.