• Title/Summary/Keyword: logit transformation

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Modified LOGIT(MLOGIT) Transformation: Prediction of $IC_{50}$ Value from Two Arbitrary Concentration Data

  • 유성은;차옥자
    • Bulletin of the Korean Chemical Society
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    • v.16 no.2
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    • pp.110-112
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    • 1995
  • A LOGIT transformation is a method to estimate IC50 values with two arbitrary concentration data when complete dose response curves(DRCs) are not available. We propose a modified LOGIT transformation (MLOGIT) which predicts IC50 values more accurately than the conventional LOGIT method.

Analysis of binary data by empirical logit transformation and the type of Freeman-Tukey inverse sine transformation (경험로지트변환과 Freeman-Tukey형 역정현 변환에 의한 계수치 자료의 해석)

  • 김홍준;채규용;이상용
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.42
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    • pp.1-8
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    • 1997
  • In case of analysis of discrete data, it shows by way of example orthogonal array experiment for o, 1 data. This paper introduced expirical logit transformation and the type of Freeman-Tukey inverse sine transformation. As the result of analysis of variance, empirical logit transformation turned out a mistake in application but it is possible for graphical analysis by normal probability paper.

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Applying Response Surface Methodology to Predict the Homogenization Efficiency of Milk (우유 균질 조건 예측을 위한 반응표면방법론의 활용)

  • Sungsue Rheem;Sejong Oh
    • Journal of Dairy Science and Biotechnology
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    • v.41 no.1
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    • pp.1-8
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    • 2023
  • Response surface methodology (RSM) is a statistical approach widely used in food processing to optimize the formulation, processing conditions, and quality of food products. The homogenization process is achieved by subjecting milk to high pressure, which breaks down fat globules and disperses fat more evenly throughout milk. This study focuses on an application of RSM including the logit transformation to predict the efficiency of milk homogenization, which can be maximized by minimizing the relative difference in fat percentage between the top part and the remainder of milk. To avoid a negative predicted value of the minimum of this proportion, the logit transformation is used to turn the proportion into the logit, whose possible values are real numbers. Then, the logit values are modeled and optimized. Subsequently, the logistic transformation is used to turn the predicted logit into the predicted proportion. From our model, the optimum condition for the maximized efficiency of milk homogenization was predicted as the combination of a homogenizer pressure of 30 MPa, a storage temperature of 10℃, and a storage period of 10 days. Additionally, with a combination of a homogenizer pressure of 30 MPa, a storage temperature of 10℃, and a storage period of 50 days, the level of milk homogenization was predicted to be acceptable, even with the problem of extrapolation taken into account.

A Consideration of Logit Transformation for Estimating the Dosage-Mortality Regression Equation (약량 반응곡선의 추정에 있어서 Logit 변환법의 이용)

  • 송유한
    • Journal of Sericultural and Entomological Science
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    • v.20 no.2
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    • pp.36-39
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    • 1978
  • With the current advances in insect toxicant bioassay, the need for easy methods of estimating the dosage-mortality regression equation has become vital. The Probit analysis seems to be not convenient for estimating the dosage-mortality regression equation and median lethal dose(LD50) because of its complexity in calculation. This study presents a comparision between Probit and Losit transformation for the estimation from bioassay results. Validation of the two methods is presented for the pathogenecity of nuclear polyhedrosis virus to the larva of fall web worm, Hyphantria cunea D.

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The Confidence Intervals for Logistic Model in Contingency Table

  • Cho, Tae-Kyoung
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.997-1005
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    • 2003
  • We can use the logistic model for categorical data when the response variables are binary data. In this paper we consider the problem of constructing the confidence intervals for logistic model in I${\times}$J${\times}$2 contingency table. These constructions are simplified by applying logit transformation. This transforms the problem to consider linear form which called the logit model. After obtaining the confidence intervals for the logit model, the reverse transform is applied to obtain the confidence intervals for the logistic model.

An Analysis of the Transformation of Over-depopulated Rural Villages (농촌 과소화마을의 변화 분석)

  • Park, Jen-Woo;Lee, Taeho;An, Donghwan
    • Journal of Korean Society of Rural Planning
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    • v.24 no.2
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    • pp.79-89
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    • 2018
  • The main purpose of this study is to explore the factors that affect the transformation of over-depopulated rural villages. Specifically, we investigated the reasons of the rapid decrease in the number of over-populated rural villages shown by recent census data in spite of the continuing decrease of population in rural area. We used a binary-logit model and the Census of Agriculture, Forestry and Fisheries data(2010, 2015). The main results are summarized as followed: First, the over-depopulated rural villages with strong agronomic base are more likely to exit from over-depopulation. Second, returners from urban to rural have a positive impacts on the revival of over-depopulated rural areas. Thirds, improving the basic services accessibility of rural residents is also critical for keeping rural community more sustainable. These findings can be used to make effective strategies to revive the depopulated rural villages.

An Introduction to Logistic Regression: From Basic Concepts to Interpretation with Particular Attention to Nursing Domain

  • Park, Hyeoun-Ae
    • Journal of Korean Academy of Nursing
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    • v.43 no.2
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    • pp.154-164
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    • 2013
  • Purpose: The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature. Methods: Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twenty-three articles published between 2010 and 2011 in the Journal of Korean Academy of Nursing were analyzed for proper use and reporting of LR models. Results: Logistic regression from basic concepts such as odds, odds ratio, logit transformation and logistic curve, assumption, fitting, reporting and interpreting to cautions were presented. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, sample size was not sufficiently large to call into question the accuracy of the regression model. Additionally, only one study reported validation analysis. Conclusion: Nursing researchers need to pay greater attention to guidelines concerning the use and reporting of LR models.

Application of Rasch Analysis to the Korean Berg Balance Scale (한국판 버그 균형척도 평가도구의 라쉬분석)

  • Lee, Jung-Ah;Yi, Chung-Hwi;Park, So-Yeon;Hwang, Su-Jin
    • Physical Therapy Korea
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    • v.13 no.3
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    • pp.49-56
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    • 2006
  • This study was designed to examine, using Rasch analysis, the rating scale performance of the Korean version of the Berg Balance Scale (BBS). The subjects were 95 elderly people at community dwelling. Subjects (19 men, 76 women) ranged in age from 65 to 91 years. Rasch analysis was then done by means of the Winsteps program to determine the validity and reliability of the Korean version of the BBS evaluation tools for elderly people. The results were as follows: Twenty-one elderly people were excluded for misfit persons. Three items were found to be misfits and the order of item difficulty of the remaining 11 items was arranged. Elderly people BBS ability is indicated by -.94~7.41 logit, and the transformation formula is score=(logit score+.94)/$(.94+7.41){\times}100$. This transformation formula can be applied to Korean elderly people for balance ability. In the order of difficulty of evaluation items, the most difficult item was "Standing on one foot" and the easiest item was "Standing to Sitting". In conclusion, the Korean version of BBS evaluation tool for the elderly people has been proved valid and will be useful in clinical practice and research in Korea.

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Application of Rasch Analysis to the Activities-Specific Balance Confidence (ABC) Scale (Activities-Specific Balance Confidence(ABC)척도에 대한 라쉬분석의 적용)

  • Hwang, Su-Jin;Yi, Chung-Hwi;Park, So-Yeon
    • Physical Therapy Korea
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    • v.14 no.1
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    • pp.37-45
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    • 2007
  • This study was designed to examine, applying Rasch analysis based on item response theory, the questionnaires of the Activities-Specific Balance Confidence (ABC) scale for the elderly. The subjects were 99 institutional older adults and clients of social welfare facilities. The subjects (17 men, 72 women) ranged in age from 65 to 94 years (mean age 76.5 yrs). The Winsteps software was used to assess whether the ABC scale fits the Rasch model, to estimate the score and to refine the rating scale. The results are as follows. Twenty-two subjects were excluded as misfit persons. Four items were found to be misfits and the order of difficulty of the remaining 12 items was rearranged. Their balance confidence is indicated by -.64~1.12 logit, and the transformation formula is score=[(logit score+2.76)/(2.76+3.48)]${\times}$100. The most difficult item was "Walk outside in icy sidewalks" and the easiest item was "Walk around house." In conclusion, the ABC scale for the elderly has been proven reliable and valid. Therefore, it is expected to be used as an effective examination tool for treatment planning and screening for older adults.

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Bankruptcy Prediction Model with AR process (AR 프로세스를 이용한 도산예측모형)

  • 이군희;지용희
    • Journal of the Korean Operations Research and Management Science Society
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    • v.26 no.1
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    • pp.109-116
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    • 2001
  • The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

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