• Title/Summary/Keyword: Multinomial model

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Multinomial Logit Framework to Evaluate the Impact of Seating Position on Senior Occupant Injury Severity in Traffic Accidents (고령탑승자의 좌석별 상해정도에 관한 연구)

  • Choi, Jaesung
    • Journal of the Korean Society of Safety
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    • v.32 no.3
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    • pp.141-150
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    • 2017
  • A rapid increase in traffic accidents involving senior vehicle occupants has been an issue in Korea because of the aging of the population occurring at one of the fastest rates in the world; unfortunately, few studies beyond several looking at the effect of senior occupants on the level of accident injury severity can be found in the literature. A Multinomial logit model was estimated with Newton-Raphson algorithm to perform bias-reducing penalized likelihood optimization. Model covariates integral to developing the model were included, but the main focus was on the interaction of seating position and injury to senior vehicle occupants. It was found that the likelihood of an accident resulting in a fatality increased: 2.2 times for the driver seat, 2.7 times for the front passenger seat, and even 6.7 times for the rear seat. A mandatory seatbelt law to be extended to the rear seat needs to pass the assembly as soon as possible, and government, industry, and safety groups should be encouraged to join forces to strongly carry out targeted campaigns for the wearing of seatbelts in all vehicle seats to enhance the safety of senior occupants as well as other occupants who are vulnerable to road traffic accidents.

Inferring the Causal Relationship between Three Events (세 사건간의 인과관계 판단)

  • Do, Kyung-Soo;Choi, Jae-Hyuk
    • Korean Journal of Cognitive Science
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    • v.21 no.1
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    • pp.47-75
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    • 2010
  • Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

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Severity Analysis for Occupational Heat-related Injury Using the Multinomial Logit Model

  • Peiyi Lyu;Siyuan Song
    • Safety and Health at Work
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    • v.15 no.2
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    • pp.200-207
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    • 2024
  • Background: Workers are often exposed to hazardous heat due to their work environment, leading to various injuries. As a result of climate change, heat-related injuries (HRIs) are becoming more problematic. This study aims to identify critical contributing factors to the severity of occupational HRIs. Methods: This study analyzed historical injury reports from the Occupational Safety and Health Administration (OSHA). Contributing factors to the severity of HRIs were identified using text mining and model-free machine learning methods. The Multinomial Logit Model (MNL) was applied to explore the relationship between impact factors and the severity of HRIs. Results: The results indicated a higher risk of fatal HRIs among middle-aged, older, and male workers, particularly in the construction, service, manufacturing, and agriculture industries. In addition, a higher heat index, collapses, heart attacks, and fall accidents increased the severity of HRIs, while symptoms such as dehydration, dizziness, cramps, faintness, and vomiting reduced the likelihood of fatal HRIs. Conclusions: The severity of HRIs was significantly influenced by factors like workers' age, gender, industry type, heat index , symptoms, and secondary injuries. The findings underscore the need for tailored preventive strategies and training across different worker groups to mitigate HRIs risks.

Part-time Jobs of Korean Married Women -The recent change in their state dependence- (기혼여성 시간제일자리의 상태의존성(state dependence) 변화)

  • Chung, Min Su
    • Journal of Labour Economics
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    • v.41 no.3
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    • pp.95-128
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    • 2018
  • This study tries to measure the change in the state dependence of the three labor supply choices (part-time, full-time, and the state of unemployed) in Korean married women's labor market by estimating the dynamic multinomial logit model based on MSL (maximum simulated likelihood) method. A component representing individual's unobserved characteristics has been introduced, because it is crucial to control for unobserved heterogeneity in assessing the state dependence. Estimation results show that the state dependences of the three alternatives have strengthened recently. Therefore, part-time job has become more likely to be functioning as an extra option to participate in labor market rather than a bridge(stepping stone) or shelter between unemployment and full-time job.

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Use of a multinomial logistic regression model to evaluate risk factors for porcine circovirus type 2 infection on pig farms in the Republic of Korea

  • Kim, Eu-Tteum;Pak, Son-Il
    • Journal of Preventive Veterinary Medicine
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    • v.41 no.3
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    • pp.129-132
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    • 2017
  • The current study identified risk factors associated with porcine circovirus type 2 (PCV2) infection on pig farms in the Republic of Korea using a multinomial logistic regression model to evaluate the PCV2 infection status of pigs at different growth stages. Compulsory disinfection of visitors (odds ratio [OR]: 0.019, 95% confidence interval [CI]: <0.001-0.378, p=0.0095), compulsory registration of visitors (OR: 0.002, 95% CI: <0.001-0.184, p=0.0070), regular blood testing (OR: 0.012, 95% CI: <0.001-0.157, p=0.0007), and running on-farm biosecurity learning programs for workers (OR: 0.156, 95% CI: 0.040-0.604, p=0.0072 and OR: 0.201, 95% CI: 0.055-0.737, p=0.0155, respectively) were identified as factors which could reduce the risk of PCV2 infection. However, visitation by a regular veterinarian (OR: 32.733, 95% CI: 3.768-284.327, p=0.0016) was associated with PCV2 infection.

Correlated damage probabilities of bridges in seismic risk assessment of transportation networks: Case study, Tehran

  • Shahin Borzoo;Morteza Bastami;Afshin Fallah;Alireza Garakaninezhad;Morteza Abbasnejadfard
    • Earthquakes and Structures
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    • v.26 no.2
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    • pp.87-96
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    • 2024
  • This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

Estimation of a Structural Equation Model Including Brand Choice Probabilities (브랜드 선택확률 분석을 위한 구조방정식 모형)

  • Lee, Sang-Ho;Lee, Hye-Seon;Kim, Yun-Dae;Jun, Chi-Hyuck
    • Journal of Korean Institute of Industrial Engineers
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    • v.36 no.2
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    • pp.87-93
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    • 2010
  • The partial least squares (PLS) method is popularly used for estimating the structural equation model, but the existing algorithm may not be directly implemented when probabilities are involved in some constructs or manifest variables. We propose a structural equation model including the brand choice as one construct having brand choice probabilities as its manifest variables. Then, we develop a PLS-based algorithm for the structural equation model by utilizing the multinomial logit model. A case is introduced as an application and simulation studies are performed to validate the proposed algorithm.

Comparison of Multinomial Logit and Logistic Regression on Disability Pensioners' Characteristic (다범주 자료의 다항로짓 모형과 로지스틱 회귀모형 비교;장애연금 특성분석 중심으로)

  • Kim, Mi-Jung
    • The Korean Journal of Applied Statistics
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    • v.21 no.4
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    • pp.589-602
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    • 2008
  • This article studies on disability pensioners' characteristic with multinomial logit and logistic regression model. Seven factors are examined on whether each factor is reflected in degree of disability in the disability pension. By incorporating multinomial logit and logistic regression model, effectiveness and characteristic of the seven factors are investigated on the degree of disability. Result shows all the seven factors are significant on the degree of disability, while among the seven, five factors, age, sex, type of coverage, type of category, insured duration show a trend in degree of disability and the other two, cause of disability and class of standard monthly income are not effective on trend in degree of disability. Results from analyses might be useful for disability pension management.

A Dynamic Market Potential Model for Forecasting the Mobile Telecommunication Service Market in Korea (국내 이동전화 서비스 시장 예측을 위한 동적 포화시장모형)

  • Jun, Duk-Bin;Park, Yoon-Seo;Kim, Seon-Kyoung;Park, Myoung-Hwan
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.2
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    • pp.176-180
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    • 2001
  • In Korea, the mobile telecommunication service market is expanding rapidly and becoming more competitive. For service providers in such a dynamic environment, it is very important to accurately forecast demand including market potential in order to work out marketing strategies. In this paper, we suggest a general approach to forecast the market potential using a multinomial logit model, which is applied to individual-level market survey data. Then we develop a dynamic market potential model that can adapt to changes in the external environment without requiring further market survey. The proposed model is applied to the mobile telecommunication service market in Korea.

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Multinomial Group Testing with Small-Sized Pools and Application to California HIV Data: Bayesian and Bootstrap Approaches

  • Kim, Jong-Min;Heo, Tae-Young;An, Hyong-Gin
    • Proceedings of the Korean Association for Survey Research Conference
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    • 2006.06a
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    • pp.131-159
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    • 2006
  • This paper consider multinomial group testing which is concerned with classification each of N given units into one of k disjoint categories. In this paper, we propose exact Bayesian, approximate Bayesian, bootstrap methods for estimating individual category proportions using the multinomial group testing model proposed by Bar-Lev et al (2005). By the comparison of Mcan Squre Error (MSE), it is shown that the exact Bayesian method has a bettor efficiency and consistency than maximum likelihood method. We suggest an approximate Bayesian approach using Markov Chain Monte Carlo (MCMC) for posterior computation. We derive exact credible intervals based on the exact Bayesian estimators and present confidence intervals using the bootstrap and MCMC. These intervals arc shown to often have better coverage properties and similar mean lengths to maximum likelihood method already available. Furthermore the proposed models are illustrated using data from a HIV blooding test study throughout California, 2000.

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