Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.

A methodological exploration to determine transportation disadvantage variables: the partial least square approach

Determining the key variables of transportation disadvantage remains a great challenge as the variables are commonly selected using ad-hoc techniques. In order to identify the variables, this research develops a transportation disadvantage framework by manipulating the capability approach. Developed framework is statistically analysed using partial least square-based software to determine the framework fitness. The statistical analysis identifies mobility and socioeconomic variables that significantly influence transportation disadvantage. The research reveals the key socioeconomic variables for transportation disadvantage in the case of Brisbane, Australia as household structure, presence of dependent family member, vehicle ownership, and driving licence possession.

Determinants of WTP for Prosecco wine: A latent class regression with attitudinal responses

Purpose – Under investigation is Prosecco wine, a sparkling white wine from North-East Italy.
Information collection on consumer perceptions is particularly relevant when developing market
strategies for wine, especially so when local production and certification of origin play an important
role in the wine market of a given district, as in the case at hand. Investigating and characterizing the
structure of preference heterogeneity become crucial steps in every successful marketing strategy. The
purpose of this paper is to investigate the sources of systematic differences in consumer preferences.
Design/methodology/approach – The paper explores the effect of inclusion of answers to
attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this
specialty wine. These additional variables were included in the membership equations to investigate
whether they could be of help in the identification of latent classes. The individual specific WTPs from
the sampled respondents were then derived from the best fitting model and examined for consistency.
Findings – The use of answers to attitudinal question in the latent class regression model is found to
improve model fit, thereby helping in the identification of latent classes. The best performing model
obtained makes use of both attitudinal scores and socio-economic covariates identifying five latent
classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were
derived from this model.
Originality/value – The approach appears informative and promising: attitudes emerge as
important ancillary indicators of taste differences for specialty wines. This might be of interest per se
and of practical use in market segmentation. If future research shows that these variables can be of use
in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in
structural latent class hedonic models.

Preliminary epidemiological study of latent tuberculosis in Mexican agricultural workers in the Niagara region, Canada

It is well documented that the majority of Tuberculosis (TB) cases diagnosed in Canada are related to foreign-bom persons from TB high-burden countries. The Canadian seasonal agricultural workers program (SAWP) operating with Mexico allows migrant workers to enter the country with a temporary work permit for up to 8 months. Preiimnigration screening of these workers by both clinical examination and chest X-ray (CXR) reduces the risk of introducing cases of active pulmonary TB to Canada, but screening for latent TB (LTBI) is not routinely done. Studies carried out in industrialized nations with high immigration from TBendemic countries provide data of lifetime LTBI reactivation of around 10% but little is known about reactivation rates within TB-endemic countries where new infections (or reinfections) may be impossible to distinguish from reactivation. Migrant populations like the SAWP workers who spend considerable amounts of time in both Canada and TBendemic rural areas in Mexico are a unique population in terms of TB epidemiology. However, to our knowledge no studies have been undertaken to explore either the existence of LTBI among Mexican workers, the probability of reactivation or the workers' exposure to TB cases while back in their communities before returning the following season. Being aware of their LTBI status may help workers to exercise healthy behaviours to avoid TB reactivation and therefore continue to access the SAWP. In order to assess the prevalence of LTBI and associated risk factors among Mexican migrant workers a preliminary cross sectional study was designed to involve a convenience sample of the Niagara Region's Mexican workers in 2007. Research ethics clearance was granted by Brock University. Individual questionnaires were administered to collect socio-demographic and TB-related epidemiological data as well as TB knowledge and awareness levels. Cellular immunity to M tuberculosis was assessed by both an Interferon-y release assay (lGRA), QuantiFERON -TB Gold In-Tube (QFf™) and by the tuberculin skin test (TSn using Mantoux. A total of 82 Mexican workers (out of 125 invited) completed the study. Most participants were male (80%) and their age ranged from 22 to 65 years (mean 38.5). The prevalence of LTBI was 34% using TST and 18% using QFTTM. As previously reported, TST (using ~lOmm cut-off) showed a sensitivity of 93.3% and a specificity of 79.1 %. These findings at the moment cannot predict the probability of progression to active TB; only longitudinal cohort studies of this population can ascertain this outcome. However, based on recent publications, lORA positive individuals may have up to 14% probability of reactivation within the next two years. Although according to the SA WP guidelines, all workers undergo TB screening before entering or re-entering Canada, CXR examination requirements showed to be inconsistent for this population: whereas 100% of the workers coming to Canada for the first time reported having the procedure done, only 31 % of returning participants reported having had a CXR in the past year. None of the participants reported ever having a CXR compatible with TB which was consistent with the fact that none had ever been diagnosed with active pulmonary TB and with only 3.6% reporting close contact with a person with active TB in their lifetime. Although Mexico reports that 99% of popUlation is fully immunized against TB within the first year of age, only 85.3% of participants reported receiving BOC vaccine in childhood. Conversely, even when TST is not part of the routine TB screening in endemic countries, a suqDrisingly high 25.6% reported receiving a TST in the past. In regards to TB knowledge and awareness, 74% of the studied population had previous knowledge about (active) TB, 42% correctly identified active TB symptomatology, 4.8% identified the correct route of transmission, 4.8% knew about the existence of LTBI, 3.6% knew that latent TB could reactivate and 48% recognized TB as treatable and curable. Of all variables explored as potential risk factors for LTBI, age was the only one which showed statistical significance. Significant associations could not be proven for other known variables (such as sex, TB contact, history of TB) probably because of the small sample size and the homogeneity of the sample. Screening for LTBI by TST (high sensitivity) followed by confirmation with QFT''"'^ (high specificity) suggests to be a good strategy especially for immigrants from TB high-burden countries. After educational sessions, workers positive for LTBI gained greater knowledge about the signs and symptoms of TB reactivation as well as the risk factors commonly associated with reactivation. Additionally, they were more likely to attend their annual health check up and request a CXR exam to monitor for TB reactivation.

Modélisation des bi-grappes et sélection des variables pour des données de grande dimension : application aux données d’expression génétique

Les simulations ont été implémentées avec le programme Java.

Descripción del comportamiento basal y transoperatorio de los nivels de NIRS cerebral en pacientes con cardiopatias congenitas cianosantes sometidos a cirugia paliativa o correctiva y su correlación con las variables fisiologicas determinantes del flujo sanguineo cerebral

La lesión neurológica es un riesgo latente en pacientes sometidos a cirugía cardiaca, en cirugía para corrección de cardiopatías congénitas puede tener una incidencia tan alta como del 26%, por lo cual es necesario contar con herramientas cada vez más acertadas y que puedan ayudar a disminuir esta incidencia; la saturación regional cerebral medida por NIRS constituye una herramienta válida, que permite una evaluación continua y de forma no invasiva, que puede servir para este fin. El presente estudio pretende determinar una asociación entre los niveles de saturación regional de oxígeno cerebral en los pacientes con cardiopatías congénitas cianosantes y las variables fisiológicas determinantes del aporte de oxígeno, asumiendo una hipoxemia crónica para estos pacientes. Se realizó un estudio de correlación para estas variables, para lo cual se evaluaron de forma sistemática estas en pacientes sometidos a cirugía cardiaca en la Fundación Cardioinfantil Instituto de Cardiología, que cumplían con los criterios de inclusión, hasta completar una muestra de 31 pacientes, en los cuales no se realizó ninguna intervención, catalogándolo como riesgo menor que el mínimo, cumpliendo con los criterios de Helsinki.Se encontró una correlación significativa entre los valores de NIRS cerebral con los contenidos arteriales, capilares y venoso de oxígeno en el análisis bivariado, encontrándose para estos pacientes niveles más bajos de estos contenidos como también para el consumo de oxígeno, no se encontró asociación significativa con la saturación arterial ni venosa de oxígeno, parece existir una relación significativa entre los niveles más bajos de NIRS con el resultado neurológico, estos hallazgos sin embargo no fueron significativos en el análisis multivariado.

A Bayesian approach to estimate sensible and latent heat over vegetated land surface

Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods.

Latent heat loss of Holstein cows in a tropical environment: a prediction model

Nove vacas Holandesas lactantes com 526 ± 5 kg de peso corporal (cinco predominantemente pretas e quatro predominantemente brancas), criadas em região tropical e manejadas em pastagens, foram observadas com os objetivos de determinar simultaneamente as taxas de evaporação cutânea e respiratória em ambiente tropical e desenvolver modelos de predição. Para a medição da perda de calor latente pela superfície corporal, utilizou-se uma cápsula ventilada e, para a perda por respiração, utilizou-se uma máscara facial. Os resultados mostraram que as vacas que tinham maior peso corporal (classe 2 e 3) apresentaram maiores taxas evaporativas. Quando a temperatura do ar aumentou de 10 para 36ºC e a umidade relativa do ar caiu de 90 para 30%, a eliminação de calor por evaporação respiratória aumentou de aproximadamente 5 para 57 W m-2 e a evaporação na superfície corporal passou de 30 para 350 W m-2. Esses resultados confirmam que a eliminação de calor latente é o principal mecanismo de perda de energia térmica sob altas temperaturas (>30ºC); a evaporação cutânea é a maior via e corresponde a aproximadamente 85% da perda total de calor, enquanto o restante é eliminado pelo sistema respiratório. O modelo para predizer o fluxo de perda de calor latente baseado em variáveis fisiológicas e ambientais pode ser utilizado para estimar a contribuição da evaporação na termorregulação, enquanto o modelo baseado somente na temperatura do ar deve ser usado apenas para a simples caracterização do processo evaporativo.

Latent heat loss of dairy cows in an equatorial semi-arid environment

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Tuberculosis and latent tuberculosis in prison inmates

OBJECTIVE: To estimate the prevalences of tuberculosis and latent tuberculosis ill inmates. METHODS: Observational study was carried out with inmates of a prison and a jail in the State of Sao Paulo, Southeastern Brazil, between March and December of 2008. Questionnaires were used to collect sociodemographic and epidemiological data. Tuberculin skin testing was administered (PPD-RT23-2TU/0.1 mL), and the following laboratory tests were also performed: sputum smear examination, sputum culture, identification of strains isolated and drug susceptibility testing. The variables were compared using Pearson's chi-square (chi(2)) association test, Fisher's exact test and the proportion test. RESULTS: Of the 2,435 inmates interviewed, 2,237(91.9%) agreed to submit to tuberculin skin testing and of these, 73.0% had positive reactions. The prevalence of tuberculosis was 830.6 per 100,000 inmates. The coefficients of prevalence were 1,029.5/100,000 for inmates of the prison and 525.7/100,000 for inmates of the jail. The sociodemographic characteristics of the inmates in the two groups studied were similar; most of the inmates were young and single with little schooling. The epidemiological characteristics differed between the prison units, with the number of cases of previous tuberculosis and of previous contact with the disease greater in the prison and coughing, expectoration and smoking more common in the jail. Among the 20 Mycobacterium tuberculosis strains identified, 95.0% were sensitive to anti-tuberculosis drugs, and 5.0% were resistant to streptomycin. CONCLUSIONS: The prevalences of tuberculosis and latent tuberculosis were higher in the incarcerated population than in the general population, and they were also higher in the prison than in the jail.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Performance of six diagnostic tests to screen for Chagas disease in blood banks and prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening based on the analysis of epidemiological variables

OBJECTIVE: The frequent occurrence of inconclusive serology in blood banks and the absence of a gold standard test for Chagas'disease led us to examine the efficacy of the blood culture test and five commercial tests (ELISA, IIF, HAI, c-ELISA, rec-ELISA) used in screening blood donors for Chagas disease, as well as to investigate the prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening in respect to some epidemiological variables. METHODS: To obtain estimates of interest we considered a Bayesian latent class model with inclusion of covariates from the logit link. RESULTS: A better performance was observed with some categories of epidemiological variables. In addition, all pairs of tests (excluding the blood culture test) presented as good alternatives for both screening (sensitivity > 99.96% in parallel testing) and for confirmation (specificity > 99.93% in serial testing) of Chagas disease. The prevalence of 13.30% observed in the stratum of donors with inconclusive serology, means that probably most of these are non-reactive serology. In addition, depending on the level of specific epidemiological variables, the absence of infection can be predicted with a probability of 100% in this group from the pairs of tests using parallel testing. CONCLUSION: The epidemiological variables can lead to improved test results and thus assist in the clarification of inconclusive serology screening results. Moreover, all combinations of pairs using the five commercial tests are good alternatives to confirm results.

Relations among fluid intelligence, sensory discrimination and working memory in middle to late childhood – A latent variable approach

Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

Transition to a cyclable city: policies and variables affecting cycling commuting

The growing interest in achieving the objectives of cycling policies has increased the need to know the key variables that influence the use of the bicycle for daily mobility. This paper makes a contribution in this research line by examining a varying nature of variables – objective and psychological - and their influence on cycling commuting in the context of a “climber cycling city”: Vitoria-Gasteiz (Spain). Statistical differences of the variables were determined between cycling commuters and commuters by other modes. The objective variables analyzed allowed us to identify the cycling commuting profile in Vitoria-Gasteiz, but showed a small effect on cycling commuting. However, analyses on seven cycling psychological variables identified and defined, showed a higher influence, especially “Individual capacities” and “Non-commuting cycling habit”. Their results allowed recommending a wide et of policy initiatives. These policy recommendations were made considering that Vitoria-Gasteiz is a “city in transition” towards cycling: a high level of cycling share for the Spanish contex t and the safety issue not being the main barrier for cycling. However the psychological latent variable “Non-commuting cycling habit” indicates that normalization of the bicycle as a mode of transport needs more progress.