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History Model (history + model)

Distribution by Scientific Domains
Humanities and Social Sciences33%

Kinds of History Model

  • event history model
    		•

    Selected Abstracts

    Churches in Dutch: Causes of Religious Disaffiliation in The Netherlands, 1937,1995

    JOURNAL FOR THE SCIENTIFIC STUDY OF RELIGION, Issue 4 2001
    Manfred 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 Dropout

    JOURNAL OF MARRIAGE AND FAMILY, Issue 1 2004
    Lingxin 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]

    A RAPID METHOD OF QUANTIFYING THE RESOLUTION LIMITS OF HEAT-FLOW ESTIMATES IN BASIN MODELS

    JOURNAL OF PETROLEUM GEOLOGY, Issue 2 2008
    A. Beha
    Deterministic forward models are commonly used to quantify the processes accompanying basin evolution. Here, we describe a workflow for the rapid calibration of palaeo heat-flow behaviour. The method determines the heat-flow history which best matches the observed data, such as vitrinite reflectance, which is used to indicate the thermal maturity of a sedimentary rock. A limiting factor in determining the heat-flow history is the ability of the algorithm used in the software for the maturity calculation to resolve information inherent in the measured data. Thermal maturation is controlled by the temperature gradient in the basin over time and is therefore greatly affected by maximum burial depth. Calibration, i.e. finding the thermal history model which best fits the observed data (e.g. vitrinite reflectance), can be a time-consuming exercise. To shorten this process, a simple pseudo-inverse model is used to convert the complex thermal behaviour obtained from a basin simulator into more simple behaviour, using a relatively simple equation. By comparing the calculated "simple" maturation trend with the observed data points using the suggested workflow, it becomes relatively straightforward to evaluate the range within which a best-fit model will be found. Reverse mapping from the simple model to the complex behaviour results in precise values for the heat-flow which can then be applied to the basin model. The goodness-of-fit between the modelled and observed data can be represented by the Mean Squared Residual (MSR) during the calibration process. This parameter shows the mean squared difference between all measured data and the respective predicted maturities. A minimum MSR value indicates the "best fit". Case studies are presented of two wells in the Horn Graben, Danish North Sea. In both wells calibrating the basin model using a constant heat-flow over time is not justified, and a more complex thermal history must be considered. The pseudo-inverse method was therefore applied iteratively to investigate more complex heat-flow histories. Neither in the observed maturity data nor in the recorded stratigraphy was there evidence for erosion which would have influenced the present-day thermal maturity pattern, and heat-flow and time were therefore the only variables investigated. The aim was to determine the simplest "best-fit" heat-flow history which could be resolved at the maximum resolution given by the measured maturity data. The conclusion was that basin models in which the predicted maturity of sedimentary rocks is calibrated solely against observed vitrinite reflectance data cannot provide information on the timing of anomalies in the heat-flow history. The pseudo inverse method, however, allowed the simplest heat-flow history that best fits the observed data to be found. [source]

    Multilevel models for longitudinal data

    JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008
    Fiona 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]

    Adaptation of the mayo primary biliary cirrhosis natural history model for application in liver transplant candidates

    LIVER TRANSPLANTATION, Issue 4 2000
    W. Ray Kim MD
    The Mayo natural history model has been used widely as a tool to estimate prognosis in patients with primary biliary cirrhosis (PBC), particularly liver transplant candidates. We present an abbreviated model in which a tabular method is used to approximate the risk score, which may be incorporated in the minimal listing criteria for liver transplant candidates. Data used in the development and validation of the original Mayo model were derived from 418 patients with well-characterized PBC. To construct an abbreviated risk score in a format similar to that of Child-Turcotte-Pugh score, 1 to 3 cut-off criteria were determined for each variable, namely age (0 point for <38, 1 for 38 to 62 and 2 for ,63 years), bilirubin (0 point for <1, 1 for 1 to 1.7, 2 for 1.7 to 6.4, and 3 for >6.4 mg/dL), albumin (0 point for >4.1, 1 for 2.8 to 4.1, and 2 for <2.8 g/dL), prothrombin time (1 point for normal and 2 for prolonged) and edema (0 point for absent and 1 for present). The intervals between these criteria were chosen in a way to enable a meaningful classification of patients according to their risk for death. This score is highly correlated with the original risk score (r = 0.93; P < .01). The Kaplan-Meier estimate at 1 year was 90.6% in patients with a score of 6. The abbreviated risk score is a convenient method to quickly estimate the risk score in patients with PBC. An abbreviated score of 6 may be consistent with the current minimal listing criteria in liver transplant candidates. [source]

    Analysing absence behaviour using event history models

    MANAGERIAL AND DECISION ECONOMICS, Issue 3 2004
    Tim 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]