• Title/Summary/Keyword: Logit Models

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Physical Distribution Channel Choice according to Commodity Types (제품특성에 따른 물적유통경로선택 분석)

  • Park, Min-Yeong;Kim, Chan-Seong;Kim, Eun-Mi;Park, Dong-Ju;Pattanamekar, Parichart
    • Journal of Korean Society of Transportation
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    • v.28 no.1
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    • pp.77-86
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    • 2010
  • The study developed physical distribution channel choice models reflecting decision making of the firms and studied how choice decision factors influence selection of distribution channel. The distribution channel survey data in Korea was used to do empirical study. As a choice set, distribution channels were classified into two main choice channels: direct and indirect channels. In addition, indirect channels were classified into other three channels according to the type of intermediate point: distribution center, wholesale store, and agency. This study developed choice models by applying both binary and multinomial logit model with various set of factors. The results showed that the developed logit models seemingly reflect distribution channel choice behaviors. The hypothesis tests on how each factor influences choice of distribution channel were performed and discussed as well.

Parameter estimation of linear function using VUS and HUM maximization (VUS와 HUM 최적화를 이용한 선형함수의 모수추정)

  • Hong, Chong Sun;Won, Chi Hwan;Jeong, Dong Gil
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.6
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    • pp.1305-1315
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    • 2015
  • Consider the risk score which is a function of a linear score for the classification models. The AUC optimization method can be applied to estimate the coefficients of linear score. These estimates obtained by this AUC approach method are shown to be better than the maximum likelihood estimators using logistic models under the general situation which does not fit the logistic assumptions. In this work, the VUS and HUM approach methods are suggested by extending AUC approach method for more realistic discrimination and prediction worlds. Some simulation results are obtained with both various distributions of thresholds and three kinds of link functions such as logit, complementary log-log and modified logit functions. It is found that coefficient prediction results by using the VUS and HUM approach methods for multiple categorical classification are equivalent to or better than those by using logistic models with some link functions.

Economic Valuation of the Taehwa Field Ecological Park: An Application of a Contingent Valuation Method with Preferance Uncertainly (태화들 생태공원의 경제적 가치추정에 관한 연구: 선호불확실성을 고려한 조건부가치측정법의 적용)

  • Kim, Jae-Hong
    • Journal of Environmental Policy
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    • v.9 no.1
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    • pp.109-135
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    • 2010
  • This study estimated the social benefits of establishment 01 the Taehwa Field Ecology Park in Ulsan Metropolitan City, using CVM(Contingent Valuation Method) with multiple choices in consideration of respondent's uncertainty. The estimation results 01 lour logit models show that the probability of willingness-to-pay increases significantly with higher income, higher evaluation on the relevancy of establishment of the Park, and male gender, and decreases significantly with the bidding price. Truncated mean household WTP is estimated as 2,409.4 KRW in the MBYES model with the most efficient estimates of WTP among four models. On the basis of the WTP estimates, the present values of total social benefits in Ulsan Metropolitan City are estimated as 236.5 bill ion KRW when applying the 5% discount rate. This result shows that the present values of total social benefits are greater than the total costs in all models, and thus may prove the economic relevancy of the investment for the ecology park establishment.

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Effect of Attitudinal Factors on Stated Preference of Low-carbon Transportation Services (개인성향 요인이 탄소저감형 교통서비스 잠재선호에 미치는 영향에 관한 연구)

  • Yoonhee Lee;Gyeongjae Lee;Sangho Choo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.49-65
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    • 2023
  • In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.

Mode Choice Models for Freight Transportation Using SP Data (SP자료를 이용한 화물수송수단 선택모형의 개발 -컨테이너 내륙운송을 중심으로-)

  • 하원익;남기찬
    • Journal of Korean Society of Transportation
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    • v.14 no.1
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    • pp.81-99
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    • 1996
  • This study aims to assess the potential competition among road, rail, and coastal transport under various scenarios concerning the future inland container transport systems in Pusan-KyungIn corridor. For this SP approaches are adopted to collect data from shippers and carriers, and multinomial logit models are estimated at disaggragate level. The results of the analysis indicate that the SP data are reliable, and that the mode choice models estimated are valid. The results also indicate that the most effective policy to divert the freight volume from road to other modes is to reduce freight rates for the railway, and is to transport time for the coastal water with improved reliability.

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Goodness-of-Fit Tests for the Ordinal Response Models with Misspecified Links

  • Jeong, Kwang-Mo;Lee, Hyun-Yung
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.697-705
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    • 2009
  • The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

Collapsibility and Suppression for Cumulative Logistic Model

  • Hong, Chong-Sun;Kim, Kil-Tae
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.313-322
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    • 2005
  • In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

A Study on One Factorial Longitudinal Data Analysis with Informative Drop-out

  • Lee, Ki-Hoon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1053-1065
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    • 2006
  • This paper proposes a method in one-way layouts for longitudinal data with informative drop-out. When dropouts are informative, that is, correlated with unobserved data and/or the previous observed data, the simple imputation methods such as 'last observation carried forward' (LOCF) methods would arise the bias of the testing models. The maximum likelihood procedure combined with a logit model for the drop-out process is proposed to test treatment effects for one factorial designs and compared with LOCF method in two examples.

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Validity of Gravity Models for Individual Choies (개인별 선택행위에서의 동력모형의 유효성)

  • 음성직
    • Journal of Korean Society of Transportation
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    • v.1 no.1
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    • pp.43-47
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    • 1983
  • Within the conventional transportation planning process, "trip distribution" has a significant role to play. The most widely applied trip distribution model is the gravity model, for which Wilson provided the theoretical basis in 1967. The concept of the gravity model, however, still remains ambiguous if we analyze the "trip distribution" with a disaggregate data set. Thus, this paper hypothesizes that the gravity technique is still valid even with the disaggregate data set, by proving that the estimated coefficients of the gravity model, which is derived under the principle of entropy maximization, are identical with those of the multinomial logit model, which is derived under the principle of individual utility maximization.tility maximization.

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Outpatient Antibiotic Prescription Patterns for Respiratory Tract Infections of Infants (소아 호흡기감염 외래환자에 대한 항생제 처방양상)

  • Kim, Yejee;Lee, Suehyung;Park, Sylvia;Na, Hyen Oh;Tchoe, Byongho
    • Health Policy and Management
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    • v.25 no.4
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    • pp.323-332
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    • 2015
  • Background: Antibiotic resistance has been becoming serious challenge to human beings. Overuse of antibiotics, especially, for infants is concerned, but studies are very few for the prescribing pattern of antibiotic use for infants. This study analyzes prescribing patterns of antibiotics in outpatients of preschool children with acute respiratory tract infections in South Korea. Methods: Data are used from 2011 Health Insurance Review & Assessment Services-pediatric patients sample. Inclusion criteria is outpatient children (0 to 5 years) with top five frequent diseases. Prescription rates are analyzed by types of disease, provider, specialty, region, and ages. Binary or multinomial logit models are used to analyze determinants of providers' prescription pattern. Results: The main findings are as follows. First, distributions of prescription rates are shown as L-shape or M-shape depending on the types of disease. Second, the prescription variation is so large among providers, where providers are polarized as a group with low prescription rates and the other group with high prescription rates, though the shapes are shown diversified across types of disease. Third, prescription rates appear to be lower in pediatrics and higher in ENT (ear-nose-throat). Fourth, broad spectrum antibiotics are widely used among children. Finally, the logit analysis shows similar results with descriptive statistics, but partly different results across types of disease. Conclusion: Antibiotics for respiratory tract infections of infants are used excessively with a large variation among providers, and especially broad spectrum antibiotics are used. The prescription guideline for antibiotics should be provided for each specific disease to reduce antibiotic resistance in the future.