Since through trips can be a significant portion of travel in a study area, estimating them is an important part of travel demand modeling. In the past, through trips have been estimated using external surveys. Recently, external surveys were suspended in Texas, so Texas transportation planners need a way to estimate through trips without using external surveys. Other research in the area has focused on study areas with a population of less than 200,000, but many Texas study areas have a population of more than 200,000. This research developed a set of two logit models to estimate through trips for a wide range of study area sizes, including larger study areas. The first model estimates the portion of all trips at an external station that are through trips. The second model distributes those through trips at one external station to the other external stations. The models produce separate results for commercial and noncommercial vehicles, and these results can be used to develop through trip tables. For predictor variables, the models use results from a very simple gravity model; the average daily traffic (ADT) at each external station as a proportion of the total ADT at all available external stations; the number of turns on the routes between external station pairs; and whether the route is valid, where a valid route is one that passes through the study area and does not pass through any other external stations. Evaluations of the performance of the models showed that the predictions fit the observations reasonably well; at least 68 percent of the absolute prediction errors for each model and for the models combined were less than 10 percent. These results indicate that the models can be useful for practical applications.

The aim of this research was to construct a freight mode choice model, from the perspective of New Zealand freight shippers, identifying the possibility of mode substitution effects. Shipper’s freight modal choice depends on freight demand and infrastructure as well as the quality of service characteristics of alternative modes, such as transport cost, delivery time, reliability, damage and loss and frequency of service. Freight logistics characteristics, such as the attributes of the shipper, the attributes of the commodities to be transported, and the spatial attributes of shipments, strongly influence modal choice. In New Zealand, due to the heterogeneity of firms and issues of confidentiality and reliability of data, relatively little research has been done on modelling freight mode choice. This research involved revealed preference (RP) and stated preference (SP) surveys of representative freight shippers and agents. User-specific data make it possible to better identify the dependence between shipper’s mode shift behaviour and freight logistics in New Zealand circumstances. Moreover, by applying a discrete choice approach, the possibility of mode substitution effects was investigated. This research approach was prompted by substantial changes in New Zealand’s freight transport patterns due to the increasing use of logistic processes, and previously developed models using a four-stage approach fail to model elements of firms’ characteristics (i.e. size of shipments, delivery distance, export volume, product shelf-life, size and location of firm, number of road fleets, and relationship with contracted carriers). The outcomes of this research have shown that many of the operational and logistical influences that affect mode choice vary with the shipper and the industry. As a result, public policy makers should recognize that effective policy must consider both the needs of the transportation service provider and user. In particular, the public policy maker should recognize that freight transport mode choice results from an array of interactions among transportation characteristics, logistics characteristics and product characteristics.

Paired comparison models in loglinear form are generalised linear models and can be fitted using the IWLS algorithm. Unfortunately, the design matrices can become very large and thus a method is needed to reduce computational load (relating to both space and time). This paper discusses an algorithm for fitting loglinear paired comparison models in the presence of many nuisance parameters which is based on partition rules for symmetric matrices and takes advantage of the special structure of the design matrix in Poisson loglinear models. The algorithm is implemented as an R function. Some simple examples illustrate its use for fitting both paired comparison models and (multinomial) logit models. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

There has been a noticeable swing towards school pupils being driven to and from school, and away from active modes like walking and cycling, in recent decades. This has had a number of side effects. Less reliance on active modes of transport has been a contributing factor in the reducing levels of physical activity for school children. Traffic volumes associated with school trips have also increased. This increased has tended to contribute to an increase in traffic congestion, adverse environmental effects and reductions in levels of sustainability. School trip traffic contributes specifically to congestion at school gates. Schools have been identified as having significant effects on the transportation system adjacent to them. Schools which seek Resource Consents for new or changed activities are often being required to take measures to mitigate their adverse effects The purpose of this study is to explore the factors contributing to primary school pupils' travel choices. This will help to identify travel choice patterns which may, in turn, be useful in developing policies and planning initiatives which contribute to achieving an efficient and sustainable transport system. A range of literature relevant to school and general commuting travel demand was reviewed. A case study involving the pupils of twenty two Christchurch primary schools was carried out. Pupils and their parents were surveyed to establish mode choices and the factors influencing those choices. The study found that between 55% and 60% of pupils surveyed travel to and from school by car. 30% to 35% walk or scooter, and 5% to 7% cycle. This compares with 34% travelling by car in the late 1980s. In addition, a greater proportion of those pupils who walk, scooter or cycle to school are accompanied by an adult than in the past. The results of the study also suggested that School Travel Plans, when combined with the energy and commitment to implement them can have a significant effect on school travel choices. As part of the case study, parents were asked to rank the importance of a number of factors which could influence choices regarding their children's school travel. The responses from parents identified safety concerns, regarding both road and personal safety, as the major factor behind decisions regarding their children's travel choices. Time constraints coupled with the complexity of travel requirements of many families were identified as significant factors. Multinomial Logit Models for both mode choice and pupils travel independence were then produced for both the journey to and from school. These models were based on the results of the case study. The models produced indicate that, at a school level, there is a correlation between increasing school roll and an increasing proportion of pupils travelling by car. A slight negative correlation between school decile and car usage was also indicated. This is contrary to the normally accepted understanding that in most transport situations there is a positive correlation between increasing affluence and car usage. Superior model results were obtained at a disaggregated individual level, using nine variables relating to the school, the neighbourhood, and the home, than the results obtained using the school based variables of. However, it is not considered that the effort required to obtain information on the additional variables is justified when estimating mode choices of pupils at an individual school. It is therefore recommended that a model using Decile, Average Age, and School Roll variables be used to estimate mode choices at an individual school. At a family level, there was a strong positive correlation between distance from school, age of the pupils, and the number of major roads between school and home, and car usage. It became apparent that the decisions made regarding children's school travel are very complex. Families juggle a number of factors, many of which are in conflict with one another. For example a desire to care for the environment may be in conflict with the demand to get the children to school, and get to work on time. This complex interrelationship between factors has resulted in some instances where normally accepted "Rules of Thumb", such as the understanding that increased car usage is generally associated with increasing wealth, do not appear to be applicable to school travel. The complexity of interrelationships has further meant that it has not been possible to quantify the impact of any one factor on its own.

This project deals with exploring 1) travel-related health risk perception, and 2) actions taken to mitigate that health risk. Ordered logistic regression models were used to identify factors associated with the perceived risk of contracting influenza at work, school, daycare, stores, restaurants, libraries, hospitals, doctor’s offices, public transportation, and family or friends’ homes. Based on the models, factors influencing risk perception of contracting influenza in public places for discretionary activities (stores, restaurants, and libraries) are consistent but differ from models of discretionary social visits to someone’s home. Mandatory activities (work, school, daycare) seem to have a few unique factors (e.g., age, gender, work exposure), as do different types of health-related visits (hospitals, doctors’ offices). Across all of the models, recent experience with the virus, of either an individual or a household member, was the most consistent set of factors increasing risk perception. Using such factors in examining transportation implications will require tracking virus outbreaks for use in conjunction with other factors. Subsequently, social-health risk mitigation strategies were studied with the objective of understanding how risk perception influences an individual’s protective behavior. For this objective, this study analyzes travel-actions associated with two scenarios during an outbreak of influenza: 1) A sick person avoiding spreading the disease and 2) A healthy person avoiding getting in contact with the disease. Ordered logistic regression models were used to identify factors associated with mitigation behavior in the first scenario: visiting a doctor’s office, avoiding public places, avoiding public transit, staying at home; and in the second scenario: avoiding public places, avoiding public transit, staying at home. Based on the models for Scenario 1, the factors affecting the decision of avoiding public places, avoiding public transit, and staying at home were fairly consistent but differ for visiting a doctor’s office. However, Scenario 2 models were consistent with their counterpart mitigation models in Scenario 1 except for two factors: gender and household characteristics. Across all the models from Scenario 1, gender was the most significant factor, and for Scenario 2, the most significant factor was the ratio of household income to the household size. / Master of Science

Os modelos para dados categorizados ordinais são extensões dos Modelos Lineares Generalizados e suas suposições e inferências são fundamentadas por esta classe de modelos. Os Modelos de Logitos Cumulativos, em que a função de ligação é constituída de probabilidades acumuladas, são muito utilizados para este tipo de variável, sendo uma de suas simplificações, os Modelos de Chances Proporcionais, em que para todas as covaríaveis no modelo há um crescimento linear nas razões de chances, porém, neste caso, é necessária a verificação da suposição de paralelismo. Outros modelos como o Modelo de Chances Proporcionais Parciais, o Modelo de Categorias Adjacentes e o Modelo Logito de Razão Contínua também podem ser utilizados. Em diversos estudos deste tipo, é necessário a utilização de modelos mistos, seja pelo tipo de um fator ou a dependência entre observações da variável resposta. Objetivou-se, neste trabalho, o estudo de modelos para variável resposta ordinal com a inclusão de um ou mais efeitos aleatórios. Esses modelos são ilustrados com a utilização de dados reais de análise sensorial, cuja variável resposta é constituída de uma escala ordinal e deseja-se saber dentre duas variedades de tomates desidratados (Italiano e Sweet Grape), qual teve melhor aceitação pelos consumidores. Nesse experimento os provadores avaliaram uma única vez cada uma das variedades, sendo as repetições constituídas pelas avaliações dadas por diferentes provadores. Nesse caso, é necessária a inclusão de um efeito aleatório por provador, para que o modelo consiga capturar as diferenças entre esses provadores não treinados. O Modelo de Chances Proporcionais ajustou-se de maneira satisfatória aos dados, podendo-se fazer uso das estimativas de probabilidades e razões de chances para a interpretação dos resultados e concluindo-se que o sabor da variedade Sweet Grape foi o que mais agradou os provadores, independente do sexo. / Models for ordinal categorical data are extensions of the Generalized Linear Models and their assumptions and inferences are based on this class of models. The Cumulative Logit Models in wich the link function consists of accumulated probabilities are more used for this type of variable, with one of its simplifications are the Proportional Odds Model, in wich for all covariates in the model there is a linear growth in odds ratios, but in this case, checking the parallelism assumption is required. Other models such as the Partial Proportional Odds Model, the Adjacent-Categories Logits and Continuation-Ratio Logits model can also be used. In several of such studies, the use of mixed models is required, either by type of factor or dependence between the response variable observations. The aim of this work is studying models for ordinal variable response with the inclusion of one or more random effects. These models are illustrated by using real data of sensory analysis, the response variable consists of an ordinal scale and we want to know from two varieties of dried tomatoes, Italian and Sweet Grape, which had better acceptance by consumers. In this experiment, the panelists evaluated each variety once, and the repetitions constituted by the ratings given by different tasters. In this case, the inclusion of a random effect by taster is required so that the model can capture the difference between these untrained tasters. The Proportional Odds Model fitted satisfactorily to the data and it is possible to make use of the estimates of probabilities and odds ratios for the interpretation of results and concluding that the taste of the variety Sweet Grape was the one that most pleased the tasters regardless of sex.

Uma das grandes dificuldades na mensuração monetária dos bens e serviços naturais, ou ambientais, reside na valoração do não-uso dos mesmos. Enquanto que o valor de uso de um recurso ambiental pode ser obtido através do mercado, que revela as preferências do consumidor, o valor de não-uso somente pode ser apropriado através do uso de mercados hipotéticos. Dentre as técnicas utilizadas, o método de valoração contingente (CVM) é o mais tradicional mas na última década, diversos economistas têm se voltado para novas abordagens evoluídas das áreas de marketing e transportes. Esses métodos, classificados como de análise conjunta (conjoint analysis) que podem ser, ainda, subdivididos em rating contingent e ranking contingent, são o estudo desse trabalho. O objetivo principal foi comparar os resultados, obtidos por um mesmo conjunto de observações, para as principais estatísticas referentes a precisão dos métodos, quando sujeitas a várias formas funcionais de utilidade, distintos graus de preferência ambiental dos consumidores e diferentes métodos de estimação. Além disso, é apresentada uma síntese crítica dos métodos em análise e os procedimentos metodológicos para o desenvolvimento e aplicação dos mesmos. Para a realização dessa análise, primeiramente foram definidos coeficientes para as utilidades dos bens – ambiental, não ambiental e monetário. Posteriormente, fez-se uso da técnica de Monte Carlo para a simulação da situação/problema e, ao final, foram utilizados os modelos de variável dependente discreta (probit ou logit ordenados) para a estimação final dos parâmetros definidos ex-ante. Constatou-se que o uso do modelo logit ordered para a estimação dos verdadeiros parâmetros mostrou-se mais preciso para a estimação dos coeficientes do que o uso do probit ordenado. Dentre as técnicas em análise, o método de valoração denominado rating contingente apresentou melhores resultados do que o ranking. No que tange às formas funcionais da utilidade e preferências dos consumidores, não foi possível constatar uma relação entre a qualidade das estimativas e a forma funcional. Foi possível, ainda, verificar que os métodos rating e ranking contingente estão bem fundamentados na teoria microeconômica, contudo, verifica-se a dificuldade de se encontrar um valor econômico total a todas as situações que envolvem bens ambientais, pois existem dificuldades a serem vencidas, não especificas aos métodos de valoração mas comum à economia ambiental. / The difficulties in giving monetary values on natural services and goods comes from valuing the non-use of them. Although the use value of environmental resources can be appropriated from the market that indicates the consumer preferences, the non-use value can only be appropriated through the hypothetic market. The contingent valuation method (CVM) is the most traditional of the techniques in use, but in the last decade, some economists have directed themselves toward new approaches in the marketing and transport areas. The goal of this work are the methods classified as conjoint analysis, which may be separated into rating contingent and ranking contingent. The main objective is the analysis of the statistics to compare the precision of the methods when submitted to different utility function forms, distinct levels of environmental preferences and diverse estimation methods. It presents, also, a synthesis of the analyzed methods and the methodological procedure to the development and application of the methods. The execution of that work was defined ex-ante the coefficients for the utilities of the goods – being monetary, environmental and non-environmental. Later it was necessary the use of Monte Carlo Method to simulate the situation that was posteriorly solved – being the coefficients estimated - with the use of discrete dependent variable models – ordered probit and ordered logit. Ordered logit model showed to be the most precise in estimating real parameters than ordered probit. The rating contingent get the best results when compared to the ranking contingent. It was not possible to get a good relation between the goods estimates and the functional form of consumer preference. In closing, it was possible to verify that the rating and ranking contingent methods have basis in the microeconomic theory although the difficulties into getting the total economic value of ambiental sources was cleared, as the problems aren´t specified to the methods studied but are general to the environmental economy.

Uma das grandes dificuldades na mensuração monetária dos bens e serviços naturais, ou ambientais, reside na valoração do não-uso dos mesmos. Enquanto que o valor de uso de um recurso ambiental pode ser obtido através do mercado, que revela as preferências do consumidor, o valor de não-uso somente pode ser apropriado através do uso de mercados hipotéticos. Dentre as técnicas utilizadas, o método de valoração contingente (CVM) é o mais tradicional mas na última década, diversos economistas têm se voltado para novas abordagens evoluídas das áreas de marketing e transportes. Esses métodos, classificados como de análise conjunta (conjoint analysis) que podem ser, ainda, subdivididos em rating contingent e ranking contingent, são o estudo desse trabalho. O objetivo principal foi comparar os resultados, obtidos por um mesmo conjunto de observações, para as principais estatísticas referentes a precisão dos métodos, quando sujeitas a várias formas funcionais de utilidade, distintos graus de preferência ambiental dos consumidores e diferentes métodos de estimação. Além disso, é apresentada uma síntese crítica dos métodos em análise e os procedimentos metodológicos para o desenvolvimento e aplicação dos mesmos. Para a realização dessa análise, primeiramente foram definidos coeficientes para as utilidades dos bens – ambiental, não ambiental e monetário. Posteriormente, fez-se uso da técnica de Monte Carlo para a simulação da situação/problema e, ao final, foram utilizados os modelos de variável dependente discreta (probit ou logit ordenados) para a estimação final dos parâmetros definidos ex-ante. Constatou-se que o uso do modelo logit ordered para a estimação dos verdadeiros parâmetros mostrou-se mais preciso para a estimação dos coeficientes do que o uso do probit ordenado. Dentre as técnicas em análise, o método de valoração denominado rating contingente apresentou melhores resultados do que o ranking. No que tange às formas funcionais da utilidade e preferências dos consumidores, não foi possível constatar uma relação entre a qualidade das estimativas e a forma funcional. Foi possível, ainda, verificar que os métodos rating e ranking contingente estão bem fundamentados na teoria microeconômica, contudo, verifica-se a dificuldade de se encontrar um valor econômico total a todas as situações que envolvem bens ambientais, pois existem dificuldades a serem vencidas, não especificas aos métodos de valoração mas comum à economia ambiental. / The difficulties in giving monetary values on natural services and goods comes from valuing the non-use of them. Although the use value of environmental resources can be appropriated from the market that indicates the consumer preferences, the non-use value can only be appropriated through the hypothetic market. The contingent valuation method (CVM) is the most traditional of the techniques in use, but in the last decade, some economists have directed themselves toward new approaches in the marketing and transport areas. The goal of this work are the methods classified as conjoint analysis, which may be separated into rating contingent and ranking contingent. The main objective is the analysis of the statistics to compare the precision of the methods when submitted to different utility function forms, distinct levels of environmental preferences and diverse estimation methods. It presents, also, a synthesis of the analyzed methods and the methodological procedure to the development and application of the methods. The execution of that work was defined ex-ante the coefficients for the utilities of the goods – being monetary, environmental and non-environmental. Later it was necessary the use of Monte Carlo Method to simulate the situation that was posteriorly solved – being the coefficients estimated - with the use of discrete dependent variable models – ordered probit and ordered logit. Ordered logit model showed to be the most precise in estimating real parameters than ordered probit. The rating contingent get the best results when compared to the ranking contingent. It was not possible to get a good relation between the goods estimates and the functional form of consumer preference. In closing, it was possible to verify that the rating and ranking contingent methods have basis in the microeconomic theory although the difficulties into getting the total economic value of ambiental sources was cleared, as the problems aren´t specified to the methods studied but are general to the environmental economy.

Uma das grandes dificuldades na mensuração monetária dos bens e serviços naturais, ou ambientais, reside na valoração do não-uso dos mesmos. Enquanto que o valor de uso de um recurso ambiental pode ser obtido através do mercado, que revela as preferências do consumidor, o valor de não-uso somente pode ser apropriado através do uso de mercados hipotéticos. Dentre as técnicas utilizadas, o método de valoração contingente (CVM) é o mais tradicional mas na última década, diversos economistas têm se voltado para novas abordagens evoluídas das áreas de marketing e transportes. Esses métodos, classificados como de análise conjunta (conjoint analysis) que podem ser, ainda, subdivididos em rating contingent e ranking contingent, são o estudo desse trabalho. O objetivo principal foi comparar os resultados, obtidos por um mesmo conjunto de observações, para as principais estatísticas referentes a precisão dos métodos, quando sujeitas a várias formas funcionais de utilidade, distintos graus de preferência ambiental dos consumidores e diferentes métodos de estimação. Além disso, é apresentada uma síntese crítica dos métodos em análise e os procedimentos metodológicos para o desenvolvimento e aplicação dos mesmos. Para a realização dessa análise, primeiramente foram definidos coeficientes para as utilidades dos bens – ambiental, não ambiental e monetário. Posteriormente, fez-se uso da técnica de Monte Carlo para a simulação da situação/problema e, ao final, foram utilizados os modelos de variável dependente discreta (probit ou logit ordenados) para a estimação final dos parâmetros definidos ex-ante. Constatou-se que o uso do modelo logit ordered para a estimação dos verdadeiros parâmetros mostrou-se mais preciso para a estimação dos coeficientes do que o uso do probit ordenado. Dentre as técnicas em análise, o método de valoração denominado rating contingente apresentou melhores resultados do que o ranking. No que tange às formas funcionais da utilidade e preferências dos consumidores, não foi possível constatar uma relação entre a qualidade das estimativas e a forma funcional. Foi possível, ainda, verificar que os métodos rating e ranking contingente estão bem fundamentados na teoria microeconômica, contudo, verifica-se a dificuldade de se encontrar um valor econômico total a todas as situações que envolvem bens ambientais, pois existem dificuldades a serem vencidas, não especificas aos métodos de valoração mas comum à economia ambiental. / The difficulties in giving monetary values on natural services and goods comes from valuing the non-use of them. Although the use value of environmental resources can be appropriated from the market that indicates the consumer preferences, the non-use value can only be appropriated through the hypothetic market. The contingent valuation method (CVM) is the most traditional of the techniques in use, but in the last decade, some economists have directed themselves toward new approaches in the marketing and transport areas. The goal of this work are the methods classified as conjoint analysis, which may be separated into rating contingent and ranking contingent. The main objective is the analysis of the statistics to compare the precision of the methods when submitted to different utility function forms, distinct levels of environmental preferences and diverse estimation methods. It presents, also, a synthesis of the analyzed methods and the methodological procedure to the development and application of the methods. The execution of that work was defined ex-ante the coefficients for the utilities of the goods – being monetary, environmental and non-environmental. Later it was necessary the use of Monte Carlo Method to simulate the situation that was posteriorly solved – being the coefficients estimated - with the use of discrete dependent variable models – ordered probit and ordered logit. Ordered logit model showed to be the most precise in estimating real parameters than ordered probit. The rating contingent get the best results when compared to the ranking contingent. It was not possible to get a good relation between the goods estimates and the functional form of consumer preference. In closing, it was possible to verify that the rating and ranking contingent methods have basis in the microeconomic theory although the difficulties into getting the total economic value of ambiental sources was cleared, as the problems aren´t specified to the methods studied but are general to the environmental economy.

Os modelos para dados categorizados ordinais são extensões dos Modelos Lineares Generalizados e suas suposições e inferências são fundamentadas por esta classe de modelos. Os Modelos de Logitos Cumulativos, em que a função de ligação é constituída de probabilidades acumuladas, são muito utilizados para este tipo de variável, sendo uma de suas simplificações, os Modelos de Chances Proporcionais, em que para todas as covaríaveis no modelo há um crescimento linear nas razões de chances, porém, neste caso, é necessária a verificação da suposição de paralelismo. Outros modelos como o Modelo de Chances Proporcionais Parciais, o Modelo de Categorias Adjacentes e o Modelo Logito de Razão Contínua também podem ser utilizados. Em diversos estudos deste tipo, é necessário a utilização de modelos mistos, seja pelo tipo de um fator ou a dependência entre observações da variável resposta. Objetivou-se, neste trabalho, o estudo de modelos para variável resposta ordinal com a inclusão de um ou mais efeitos aleatórios. Esses modelos são ilustrados com a utilização de dados reais de análise sensorial, cuja variável resposta é constituída de uma escala ordinal e deseja-se saber dentre duas variedades de tomates desidratados (Italiano e Sweet Grape), qual teve melhor aceitação pelos consumidores. Nesse experimento os provadores avaliaram uma única vez cada uma das variedades, sendo as repetições constituídas pelas avaliações dadas por diferentes provadores. Nesse caso, é necessária a inclusão de um efeito aleatório por provador, para que o modelo consiga capturar as diferenças entre esses provadores não treinados. O Modelo de Chances Proporcionais ajustou-se de maneira satisfatória aos dados, podendo-se fazer uso das estimativas de probabilidades e razões de chances para a interpretação dos resultados e concluindo-se que o sabor da variedade Sweet Grape foi o que mais agradou os provadores, independente do sexo. / Models for ordinal categorical data are extensions of the Generalized Linear Models and their assumptions and inferences are based on this class of models. The Cumulative Logit Models in wich the link function consists of accumulated probabilities are more used for this type of variable, with one of its simplifications are the Proportional Odds Model, in wich for all covariates in the model there is a linear growth in odds ratios, but in this case, checking the parallelism assumption is required. Other models such as the Partial Proportional Odds Model, the Adjacent-Categories Logits and Continuation-Ratio Logits model can also be used. In several of such studies, the use of mixed models is required, either by type of factor or dependence between the response variable observations. The aim of this work is studying models for ordinal variable response with the inclusion of one or more random effects. These models are illustrated by using real data of sensory analysis, the response variable consists of an ordinal scale and we want to know from two varieties of dried tomatoes, Italian and Sweet Grape, which had better acceptance by consumers. In this experiment, the panelists evaluated each variety once, and the repetitions constituted by the ratings given by different tasters. In this case, the inclusion of a random effect by taster is required so that the model can capture the difference between these untrained tasters. The Proportional Odds Model fitted satisfactorily to the data and it is possible to make use of the estimates of probabilities and odds ratios for the interpretation of results and concluding that the taste of the variety Sweet Grape was the one that most pleased the tasters regardless of sex.