• Title/Summary/Keyword: Mixed Logit Model

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A generalized logit model with mixed effects for categorical data (다가자료에 대한 혼합효과모형)

  • Choi, Jae-Sung
    • 한국데이터정보과학회:학술대회논문집
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    • 2001.10a
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    • pp.25-33
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    • 2001
  • This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but condisered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

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Two Stage Small Area Estimation (이단계 소지역추정)

  • Lee, Sang-Eun;Shin, Key-Il
    • The Korean Journal of Applied Statistics
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    • v.25 no.2
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    • pp.293-300
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    • 2012
  • When Binomial data are obtained, logit and logit mixed models are commonly used for small area estimation. Those models are known to have good statistical properties through the use of unit level information; however, data should be obtained as area level in order to use area level information such as spatial correlation or auto-correlation. In this research, we suggested a new small area estimator obtained through the combination of unit level information with area level information.

A Proportional Odds Mixed - Effects Model for Ordinal Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.471-479
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    • 2007
  • This paper discusses about how to build up mixed-effects model for analysing ordinal response data by using cumulative logits. Random factors are assumed to be coming from the designed sampling scheme for choosing observational units. Since the observed responses of individuals are ordinal, a proportional odds model with two random effects is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

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A Mixed Model for Oredered Response Categories

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.339-345
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    • 2004
  • This paper deals with a mixed logit model for ordered polytomous data. There are two types of factors affecting the response varable in this paper. One is a fixed factor with finite quantitative levels and the other is a random factor coming from an experimental structure such as a randomized complete block design. It is discussed how to set up the model for analyzing ordered polytomous data and illustrated how to estimate the paramers in the given model.

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A Continuation-Ratio Logits Mixed Model for Structured Polytomous Data

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.187-193
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    • 2006
  • This paper shows how to use continuation-ratio logits for the analysis of structured polytomous data. Here, response categories are considered to have a nested binary structure. Thus, conditionally nested binary random variables can be defined in each step. Two types of factors are considered as independent variables affecting response probabilities. For the purpose of analyzing categorical data with binary nested strutures a continuation-ratio mixed model is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed in detail by an example.

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Bayesian modeling of random effects precision/covariance matrix in cumulative logit random effects models

  • Kim, Jiyeong;Sohn, Insuk;Lee, Keunbaik
    • Communications for Statistical Applications and Methods
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    • v.24 no.1
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    • pp.81-96
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    • 2017
  • Cumulative logit random effects models are typically used to analyze longitudinal ordinal data. The random effects covariance matrix is used in the models to demonstrate both subject-specific and time variations. The covariance matrix may also be homogeneous; however, the structure of the covariance matrix is assumed to be homoscedastic and restricted because the matrix is high-dimensional and should be positive definite. To satisfy these restrictions two Cholesky decomposition methods were proposed in linear (mixed) models for the random effects precision matrix and the random effects covariance matrix, respectively: modified Cholesky and moving average Cholesky decompositions. In this paper, we use these two methods to model the random effects precision matrix and the random effects covariance matrix in cumulative logit random effects models for longitudinal ordinal data. The methods are illustrated by a lung cancer data set.

Study on the Selection of Suitable Resident for C.B.D. Living by Using the Logit Model -The Case of Taegu City- (로짓 模型을 利用한 都心居住의 適住者 選定에 관한 硏究 - 大邱市를 中心으로 -)

  • 임준홍;김한수
    • Journal of the Korean housing association
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    • v.10 no.1
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    • pp.11-19
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    • 1999
  • This study is for the development of C.B.D. residential land that is available in the changeable housing market and urban planning paradigm. The results are as follows. First, we developed a Logit model to analyzed the suitable resident for living downtown and we used several variables in the model such as their living place, the location of their works, in come according to sex and age, and whether they have a car or not. Second, in analysis for the suitable residents using the Logit model, the main demanders who live in C.B.D. or have a job there and the young and old were chosen, Third, it shows that the suitable residents prefer semi-C.B.D. because it has convenient accessibility to C.B.D. rater quickly (in ten minutes). They prefer apartment and Mixed-Use building. Fourth, there are much residential land in semi-C.B.D. (63.7%) so as to support enough land in ease of redevelopment. The land price is tremendously low compared to that of land for business or for C.B.D.

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Analysing Korean Residential House Tenure Choice by Mixed Logit Panel Model

  • Jeong, Ki-Ho;Lee, Sang-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.2
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    • pp.559-568
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    • 2008
  • This paper analyzes Korean residential tenure choice for house which is the most important in Korean households' assets. Data used in the analysis is the data of Korean Labor and Income Panel Study for the period from 1998 to 2006 and with 2341 households. In this paper, a household chooses a housing tenure mode, either by renting or by owing house. We use a mixed-logit panel model as an estimation model to take into consideration household's heteroscedasticity of preference in tenure choice. It turns out that the heteroscedasticity is significant in households' tenure choice behavior, implying that Korean housing policy emphasizing supply side should consider the demand side.

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A Study on Preference Heterogeneity of Economic Valuation for the Washland of Upo Wetland - Development of Waterfront Resources - (우포늪 천변저류지의 경제적 가치평가에 대한 선호이질성 연구 - 수변관광자원의 선택적 개발 -)

  • Yoo, Byong Kook;Kim, Hung Soo;Ju, Dug
    • Journal of Wetlands Research
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    • v.15 no.3
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    • pp.357-366
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    • 2013
  • This study investigates to explain preference heterogeneity of respondents for economic valuation in washland of Upo wetland using Mixed Logit Model and Latent Class Model. Mixed Logit Model showed respondent heterogeneity in the attributes of wetland area and funds as well as some alternatives violated IIA assumption. 2-class Latent Class Model for respondents were used to explain the sources of the heterogeneity. Class 1 respondents who are located relatively close to Upo wetland had more experience and knowledge of Upo wetland and better understood the information suggested in the questionnaire than class 2 respondents in mostly metropolitan area of Seoul, Incheon.

Impacts of Local Land Use on Individual Modal Choice

  • Yang, Hee Jin
    • Journal of Urban Science
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    • v.9 no.2
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    • pp.63-68
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    • 2020
  • In recent years, the planning of livable communities has emerged as a new paradigm. The concept of livable communities is related to both the spatial balance of working, playing, and living and the promotion of green modes of transportation, such as walking and biking. This study uses a disaggregate travel survey conducted by the Seoul Metropolitan Area in 2006. I applied a multi-level random intercept logit model to estimate the effects of land-use characteristics on the choice of green modes, holding a traveler's socio-demographic characteristics constant. The empirical results show that higher density and more mixed land-use development encourages people to walk and bike even when individuals have the same socio-economic characteristics. This paper demonstrates that land-use planning by itself can play a role in the creation of livable cities and the decline of greenhouse gas production.