Home About us Contact
|
Home About us Contact | ||
|
|
||
Event History Model (event + history_model)
Selected AbstractsChurches in Dutch: Causes of Religious Disaffiliation in The Netherlands, 1937,1995JOURNAL FOR THE SCIENTIFIC STUDY OF RELIGION, Issue 4 2001Manfred Te Grotenhuis The Netherlands has become one of the most secular countries in the world. A vast majority of the Dutch people does not attend church regularly and more than half its population is not affiliated with any church at all. In this study we set out to test which individual and contextual characteristics affect religious disaffiliation. We deduced several hypotheses from theories on social integration and rationalization. To test these hypotheses we used retrospective data containing information on events that took place in the lives of our respondents since adolescence. These data were analysed using a discrete-time event history model. We found that the higher the level of rationalization in a certain year, the more likely people were to disaffiliate. This effect was particularly strong for young people. Moreover, by introducing rationalization in the model we found a number of spurious relationships that at first glance seemed to be causal. Not surprisingly, respondents were more likely to disaffiliate in cases where their partners were nonreligious. However, as respondents and their partners presumably are effected equally by rationalization, we cannot but conclude that the process of rationalization is mainly responsible for the process of religious disaffiliation that takes place in The Netherlands. [source] Welfare Reform and Teenage Pregnancy, Childbirth, and School DropoutJOURNAL OF MARRIAGE AND FAMILY, Issue 1 2004Lingxin Hao This study estimates the effect of welfare reform on adolescent behaviors using a difference-in-differences approach. After defining the prereform and reform cohorts and considering the life course development of adolescent behavior by following each cohort from age 14 to age 16, we compare the welfare-target and nontarget populations in the two cohorts. The difference-in-differences estimates are obtained using an event history model. Our analysis suggests that welfare reform has not reduced teenage fertility and school dropout. We find modest evidence that welfare reform is associated with higher risk of teenage births for girls in welfare families and higher risk of school dropout for girls in poor families. A combination of a difference-in-differences approach and a life course perspective can be a useful way to delineate the effect of societal-level change on family phenomena. [source] Multilevel models for longitudinal dataJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008Fiona Steele Summary., Repeated measures and repeated events data have a hierarchical structure which can be analysed by using multilevel models. A growth curve model is an example of a multilevel random-coefficients model, whereas a discrete time event history model for recurrent events can be fitted as a multilevel logistic regression model. The paper describes extensions to the basic growth curve model to handle auto-correlated residuals, multiple-indicator latent variables and correlated growth processes, and event history models for correlated event processes. The multilevel approach to the analysis of repeated measures data is contrasted with structural equation modelling. The methods are illustrated in analyses of children's growth, changes in social and political attitudes, and the interrelationship between partnership transitions and childbearing. [source] Analysing absence behaviour using event history modelsMANAGERIAL AND DECISION ECONOMICS, Issue 3 2004Tim Barmby This paper analyses the absence behaviour of a group of industrial workers. Part of their remuneration scheme comprises an experience rated sick-pay scheme (linking level of sickpay to past absence) which determines the cost of a day's absence for a worker, both contemporaneously and in terms of expected future cost. This cost is explicitly computed for each worker and we show that this cost is negatively related to absence. Using an event history model with a Markov structure for the absence histories the size of this effect is shown to depend on the state occupied. Copyright © 2004 John Wiley & Sons, Ltd. [source] | ||||||||||