Modeling household interactions in daily in-home and out-of-home maintenance activity participation
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Discrete choice
In this paper, multilevel logistic regression models are developed for examining the hierarchical effects of contraceptive use and its selected determinants in Oman using the 2008 Oman National Reproductive Health Survey (ONRHS). Comparison between single level and multilevel logistic regression models has been made to examine the plausibility of multilevel effects of contraceptive use. From the multilevel logistic regression model analysis, it was found that there is real multilevel variation among contraceptive users in Oman. The results indicate that a multilevel logistic regression model is the best fit over ordinary multiple logistic regression models. Generally, this study revealed that women’s age, education, number of living children and region of residence are important factors that affect contraceptive use in Oman. The effect of regional variation for age of women, education of women and number of living children further implies that there exists considerable differences in modern contraceptive use among regions, and a model with a random coefficient or slope is more appropriate to explain the regional variation than a model with fixed coefficients or without random effects. The study suggests that researchers should use multilevel models rather than traditional regression methods when their data structure is hierarchal.
Multilevel modelling
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Hazard model
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Baseline (sea)
Parametric model
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The motivation behind this paper is to enhance the reliability of in-vehicle navigation systems by predicting the duration of incidents that cause congestion. The main objective of this paper is to develop a methodology for predicting incident duration using broadcast incident data and evaluate the performance of k-NN and hazard-based duration models for predicting incident duration; both of the models are presented in this paper. An incident dataset from the BBC for the Greater London area is used to evaluate the accuracy of both models so that the results give a direct comparison between the models. The strengths and weaknesses of the models are discussed in the paper based on this analysis. Results show that both k-NN and hazard based models have the potential to provide accurate incident duration prediction. While k-NN based models provided marginally more accurate prediction than hazard-based models, the hazard-based duration models can provide additional information such as delay probabilities that can be used by advanced routing and navigation algorithms. Results also show that traffic information incident feeds, such as the tpegML feed from the BBC or TMC information, can be used as a potential data source for incident duration prediction in vehicle navigation systems.
Predictive modelling
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We estimate the impact of unemployment duration on exits from unemployment, along with a set of individual and other explanatory variables. The analysis is based on EU-SILC longitudinal data for the period 2007–2010 and involves Spain and the Czech Republic as examples of the two EU countries with remarkably different labour market performance but similar in their totalitarian past, post-transition economies and recent EU entry. Survival functions estimates point uniformly to prolonged unemployment duration and increasing long-term unemployment. However, both these tendencies apply relatively more to the young unemployed. Estimations of hazard models indicate that shorter unemployment spells are more likely to be terminated by finding a job in comparison with spells lasting for more than one year. The hazard ratios are usually higher for prime age unemployed. Finally, we examine education, gender, household size, etc., as determinants of exits from unemployment, with uniform evidence found for university graduates only.
Youth Unemployment
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It is not enough to study the labour market only by analysing the static variables like rates of employment and unemployment. For the decision making on the labour market it is essential to see the movement of people into and out of jobs, the extent to which they can or cannot quickly find alternative employment and to which extent different groups of the labour force are more affected than others. Using the frailty models, as a specific area in survival analysis, we show that the durations of unemployment are sensitive to the educational level and gender. First, females are experiencing significantly longer durations of finding job than man. Second, better-educated individuals appear to find job more quickly than the less-educated. Finally, there is evidence of duration dependence in unemployment in Bosnia and Herzegovina. The re-employment hazard exhibits positive duration dependence in the first 59 months, and then declines approximately 60 months.
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This paper investigates the factors influencing duration of cross-border marriages among the Chinese spouses in Taiwan. The data used is from the 2008 Survey of Foreign and Mainland Chinese Spouses’ Living Conditions in Taiwan (SFMLC), which contains detailed information on individuals, family structure, health, social support, employment, and economic status. Duration models are used to estimate the hazard rates of marriage duration, especially for divorce or separation. Further, this paper examines the effect of unobserved heterogeneity on estimated individual hazard rates of marriage duration. The main results show that older Chinese spouses, people with more children, spouses with good health, and people with higher income have lower hazard rates of divorce or separation. In contrast, the Chinese spouses with high educational attainment, and spouses with jobs have higher hazard rates of divorce or separation. The empirical results also confirm that, after considering unobserved heterogeneity, most estimated coefficients on the marriage hazard regressors are larger in magnitude that the corresponding coefficients in the reference model.
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Abstract This study examines the rhythms in the shopping activity participation of individuals over a multiweek period by modeling the duration between successive shopping participations. A hazard-based duration model is used to model intershopping duration, and a latent segmentation method is applied to distinguish between erratic shoppers and regular shoppers. The paper applies the methodology to examine the regularity and frequency of shopping behavior of individuals using a continuous six-week travel survey collected in the cities of Halle and Karlsruhe in Germany in the fall of 1999. The empirical results underscore the need to adopt a flexible hazard model form for analyzing intershopping durations. The results also provide important insights into the determinants of the regularity and frequency of individuals’ shopping activity participation behavior.
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This paper investigates whether the hazard of dropping out for both male and female students changes over the duration of study. Using duration modelling techniques wend a certain degree of non-monotonic duration dependence for both males and females. However this pattern for female students aiming at high level qualifications is sensitive to attempts to control for unobserved heterogeneity. For these students the extended models show a flattened hazard function, suggesting that the hazard is basically constant over time. For males introducing controls for unobserved heterogeneity does not change the pattern of the duration dependence, suggesting that they might be at higher risk of dropping out during the first semester of their studies. In addition, we examine variations in drop out hazard patterns for students enrolled on courses which confer different qualification levels. We provide evidence of distinct hazard patterns between students pursuing 'high level' and 'low level' qualifications.
Dropout (neural networks)
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This paper postulates that the effect of unemployment benefits on the hazard rates changes considerably using a traditional duration model that uses only unemployment insurance (UI) data, or deals with unemployment assistance (UA) as a mere extension of UI, instead of an extra time duration model that accounts separately for transition rates to work of the unemployed who receive UI and UA. For UI recipients the hazard rate rises dramatically when UI benefits lapse approaches. On the contrary, for UA recipients the hazard rate remains flat or even has a slight fall nearby the UA lapse. Finally, there is a group of unemployed qualified for UA that quit UI due to the income fall that they will experience when they pass from UI to UA.
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