• 제목/요약/키워드: Poisson Regression Analysis

검색결과 149건 처리시간 0.027초

비선형 회귀분석과 구조방정식을 이용한 지방부 4지 신호교차로의 사고요인분석 (A Causation Study for car crashes at Rural 4-legged Signalized Intersections Using Nonlinear Regression and Structural Equation Methods)

  • 오주택;권일;황정원
    • 대한교통학회지
    • /
    • 제31권1호
    • /
    • pp.65-76
    • /
    • 2013
  • 사고발생의 주요지점인 신호교차로 교통사고 발생건수는 해마다 증가하고 있어 교통사고를 감소시키기 위한 원인 규명이 매우 필요하다. 국내에서 연구되어진 기존의 교통사고예측 모형들은 대부분 Poisson 모형 등의 비선형 회귀분석을 이용한 사고원인분석이 주를 이루고 있다. 비선형 Econometrics 분석기법들이 사고의 성격을 분석하는데 가장 중요한 통계적 기법이기는 하지만, 도로에서 발생하는 교통사고의 원인분석적 차원에서 접근하면 이런 사고예측 모형들만 가지고 사고발생의 설명변수들을 규명하는데 구조적인 한계가 발생한다. 이는 이러한 통계적 방법들이 사고의 예측력을 높이는데 중점을 두고, 이를 위해 소수의 유효한 설명변수들만을 모형식에 포함시키기 때문이다. 따라서 사고에 대해 보다 구체적인 원인규명을 위해서는 비선형회귀분석모형의 개발과 동시에 비선형 Econometrics 분석기법의 단점을 보완하는 또 다른 통계적 노력이 필요하다. 이에 본 연구에서는 Poisson기법을 이용하여 지방부 4지 신호교차로의 사고예측모형을 개발하였고, 동시에 복합적인 인과관계를 증명하는데 다중변수관계를 포괄적으로 측정하여 탐색하는 구조방정식을 이용하여 사고모형을 개발하여 Poisson 모형의 결과값과 비교 분석하였다.

신호교차로 안전성 향상을 위한 사고심각도 모형개발 (A Development of Models for Analyzing Traffic Accident Injury Severity for Signalized Intersections)

  • 하오근;허억;원제무
    • 한국안전학회지
    • /
    • 제23권2호
    • /
    • pp.65-71
    • /
    • 2008
  • As the interest in traffic safety has been increasing recently, social movement is being made to reduce the number of traffic accidents and the view on improving the mobility of the existing roads is being converted into on establishing traffic safety as a priority. The increase of traffic accidents related to an intersection in a state that traffic accidents are decreasing overall may suggests the necessity to investigate the specific causes. In addition, we have to consider them when establishing the measures against traffic accidents in a intersection by investigating and analyzing the influences and factors that may affect traffic accidents. To induce the accident severity model, we collected the factors that affect accidents and then applied the Poisson Regression Model among nonlinear regression analysis by verifying the distribution of variables. As a result of the analysis, it turned out that the volume of traffic on main roads, the right turn ratio on sub-roads, the number of ways out on sub-roads, the number of exclusive roads for a left turn, the signals for a right turn on main roads, and an intersect angle were the factors that affect the accident severity.

지방부 신호교차로 사고특성분석 및 모형개발 (청주.청원을 중심으로) (Analysis of Accident Characteristics and Development of Accident Models in the Signalized Intersections of Cheongju and Cheongwon)

  • 박병호;유두선;양정모;이영민
    • 대한교통학회지
    • /
    • 제26권2호
    • /
    • pp.35-46
    • /
    • 2008
  • 본 연구는 지방부의 교통사고 특성을 분석하고 사고모형을 개발하는데 그 목적이 있다. 이를 위해 본 연구에서는 청주시와 청원군의 신호교차로를 중심으로 다중선형, 포아송 및 음이항회귀모형을 개발하는데 중점을 두고 있다. 분석된 주요 연구결과는 다음과 같다. 첫째, 사고특성 분석을 통해 지방부 교통사고의 특성이 요인별로 파악되었다. 둘째, 통계적으로 설명력이 높은 4개의 사고모형이 개발되었다. 마지막으로 평균차로폭차($X_2$)와 교차로간거리 ($X_{11}$)가 지방부의 특성을 반영할 수 있는 특정변수로 밝혀졌다.

차량유형에 따른 교통사고심각도 분석모형 개발 (Developing the Traffic Accident Severity Models by Vehicle Type)

  • 김경환;박병호
    • 한국안전학회지
    • /
    • 제25권3호
    • /
    • pp.131-136
    • /
    • 2010
  • This study deals with the accident models of arterial link sections by vehicle type. The objectives are to analyze the characteristics of accidents, and to develop the models by type. In pursuing the above, this study uses the data of 414 accidents occurred on 24 major arterial links in 2007. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 47% in passenger car, 15% in SUV and 10% in trucks. Second, 3 Poisson regression models which are all statistically significant are developed using passenger car, SUV and truck as dependant variables. Finally, AADT and the number of traffic islands as common variables, and the number of pedestrian crossings, lanes, connecting roads, intersections(4-Leg), rate of medians and the number of bus stops as specific variables of the models are selected.

차로수별 간선도로구간 사고모형 - 청주시를 사례로 - (Traffic Accident Models of Arterial Road Sections by Number of Lane in the Case of Cheongju)

  • 임진강;나희;박병호
    • 한국안전학회지
    • /
    • 제26권5호
    • /
    • pp.130-135
    • /
    • 2011
  • This study deals with the accident models of arterial road sections. The objectives is to develop the models by number of lane. In pursuing the above, this study gives particular emphasis to dividing the 474 small link sections, collecting the accident data of 2007, and applying the statistical programs of SPSS17.0 and NLOGIT4.0. The main results are as follows. First, the number of accidents of two-lane roads were analyzed to be 59.9% of totals and to be the most of all. Second, one Poisson and two negative binomial regression models which were all statistically significant were developed. Finally, the common variables of all models were evaluated to be ADT and number of exit/entry which were all positive to the accidents.

A Bayesian joint model for continuous and zero-inflated count data in developmental toxicity studies

  • Hwang, Beom Seuk
    • Communications for Statistical Applications and Methods
    • /
    • 제29권2호
    • /
    • pp.239-250
    • /
    • 2022
  • In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

국내 회전교차로의 추돌사고 모형 개발 (Developing Rear-End Collision Models of Roundabouts in Korea)

  • 박병호;백태헌
    • 한국안전학회지
    • /
    • 제29권6호
    • /
    • pp.151-157
    • /
    • 2014
  • This study deals with the rear-end collision at roundabouts. The purpose of this study is to develop the accident models of rear-end collision in Korea. In pursuing the above, this study gives particular attention to developing the appropriate models using Poisson, negative binomial model, ZAM, multiple linear and nonlinear regression models, and statistical analysis tools. The main results are as follows. First, the Vuong statistics and overdispersion parameters indicate that ZIP is the most appropriate model among count data models. Second, RMSE, MPB, MAD and correlation coefficient tests show that the multiple nonlinear model is the most suitable to the rear-end collision data. Finally, such the independent variables as traffic volume, ratio of heavy vehicle, number of circulatory roadway lane, number of crosswalk and stop line are adopted in the optimal model.

중소기업 청년인턴 이직횟수 결정요인 분석 (The study on the determinants of the number of job changes)

  • 박성익;류장수;김종한;조장식
    • Journal of the Korean Data and Information Science Society
    • /
    • 제26권2호
    • /
    • pp.387-397
    • /
    • 2015
  • 본 연구에서는 청년인턴 DB와 고용보험 DB를 사용하여 중소기업 청년인턴의 이직횟수에 영향을 미치는 요인을 분석하였다. 이직횟수는 음수가 아닌 정수 값만 가지는 계수 데이터 (count data)이므로 일반적인 선형회귀모형을 적용하는 것은 문제가 있다. 따라서 계수 데이터에 적합한 회귀모형으로 포아송 회귀모형, 영과잉 포아송 회귀모형, 음이항 회귀모형, 영과잉 음이항 회귀모형 등 4개의 회귀모형을 적용하였다. 분석결과 최적모형으로 영과잉 음이항 회귀모형이 선택되었다. 주요 분석결과를 정리하면 다음과 같다. 첫째, 통제집단 (비인턴집단)에 비해서 처리집단 (인턴집단)이 통계적으로 유의하게 이직경험이 낮게 나타났다. 둘째, 연령이 작을수록 통계적으로 유의하게 이직경험이 낮게 나타났다. 셋째, 여자에 비해서 남자가 유의하게 이직횟수가 높게 나타났다. 마지막으로 기업규모가 클수록 이직횟수가 유의하게 감소하는 것으로 나타났다.

Analysis of Differences in Preterm Birth Rates According to Household Occupation in Japan From 2007 to 2019

  • Okui, Tasuku;Nakashima, Naoki
    • Journal of Preventive Medicine and Public Health
    • /
    • 제55권4호
    • /
    • pp.371-378
    • /
    • 2022
  • Objectives: No studies have examined the association between preterm birth rates and socioeconomic factors in Japan using nationwide statistical data. We analyzed the association between preterm birth rates and household occupation using Vital Statistics data. Methods: Aggregated Vital Statistics data from Japan from 2007 to 2019 were obtained from the Ministry of Health, Labour and Welfare. From the data, the number of births according to year, age group, gestational period, number of pregnancies, and household occupation were used in this study. Crude preterm birth rates and preterm birth rates adjusted by maternal age according to household occupation were calculated for each year. Poisson regression analysis was conducted to evaluate the association between household occupation and preterm births. Results: Unemployed households had the highest preterm birth rate, and households with an occupation classification of "full-time worker 2" (an employee at a large company, civil servant, or board member) had the lowest preterm birth rate throughout each period. Poisson regression analysis revealed that unemployed households were statistically significantly associated with a high preterm birth risk. In contrast, the preterm birth rate adjusted by maternal age remained stable throughout each period regardless of household occupation, and preterm birth rates were found not to have increased in recent years in Japan. Conclusions: Unemployed households had higher preterm birth rates than other household occupations. Further studies investigating the characteristics of unemployed households are needed to identify the reasons for this disparity.

규제 순응도와 산업재해 발생 수준간의 관계 분석 - 로지스틱 회귀분석과 포아송 회귀분석을 중심으로 - (Analysis of the relationship between regulation compliance and occupational injuries - Focusing on logistic and poisson regression analysis -)

  • 이경용;김기식;윤영식
    • 대한안전경영과학회지
    • /
    • 제15권2호
    • /
    • pp.9-20
    • /
    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.