For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.
Poker has gained tremendous popularity in recent years, increasing the risk for some individuals to develop pathological gambling.
Here, we investigated cognitive biases in a computerized two-player poker task against a fictive opponent, among 12 pathological
gambling poker players (PGP), 10 experienced poker players (ExP), and 11 inexperienced poker players (InP). Players were compared
on probability estimation and decision-making with the hypothesis that ExP would have significantly lower cognitive biases
than PGP and InP, and that the groups could be differentiated based on their cognitive bias styles. The results showed that
ExP had a significantly lower average error margin in probability estimation than PGP and InP, and that PGP played hands with
lower winning probability than ExP. Binomial logistic regression showed perfect differentiation (100%) between ExP and PGP,
and 90.5% classification accuracy between ExP and InP. Multinomial logistic regression showed an overall classification accuracy
of 23 out of 33 (69.7%) between the three groups. The classification accuracy of ExP was higher than that of PGP and InP due
to the similarities in probability estimation and decision-making between PGP and InP. These impairments in probability estimation
and decision-making of PGP may have implications for assessment and treatment of cognitive biases in pathological gambling
poker players. 相似文献
In this article in the journal Gruppe. Interaktion. Organisation (GIO) we discuss the impact of individual mindfulness trainings on organizations. Therefore, we combine research on high reliability organizations with aspects of the newer sociologist system theory. First we seek to define the construct of mindfulness and we distinguish between individual and collective mindfulness as two different qualities of mindfulness. Using an example from the banking sector we discuss the challenges developing mindfulness in organizations and what intervention strategies could work. We distinguish between the three system levels psyche, interaction and organization. Doing this it becomes clear that interventions have to consider the coupling of the three different levels: How interventions have to be designed to effect all three levels? 相似文献