Accuracy evaluation history

The accuracy of exposure assessment is determined by systematic and random errors in the assessment. For quantitative exposure assessments, important sources of error include measurement errors (i.e. from laboratory and field monitoring techniques), as well as variations in exposure over time and space. For qualitative exposure proxies (e.g. self-reported past exposures, occupational histories or expert evaluations), the most important sources of error are recall bias (systematic differences in exposure recall between cases and controls) and random error, expressed in terms of intra- and inter-rater agreement. Although systematic errors can result in serious misinterpretations of the data, especially due to scaling problems, random errors have received more attention in epidemiology because this type of error is pervasive, and its effect is usually to diminish estimates of association between exposure and disease. The magnitude of random errors can be considerable in epidemiological field studies. 

The accuracy of a Markov model for a given state space can be evaluated by comparing the timescale for trajectories to lose memory of their history with the lifetimes of... 

One of the methods developed for the seismic risk evaluation of structures is the SAC-FEMA method, which enables probability assessment in closed form (Cornell et al. 2002), and represents a part of a broader PEER probabilistic framework (Deierlein 2004). Within the framework of SAC-FEMA method, the relationship between the seismic intensity measure and the engineering demand parameter is usually determined by Incremental Dynamic Analysis (IDA) developed by Vamvatsikos Cornell (2002). IDA is a powerful tool for estimation of seismic demand and capacity for multiple levels of intensity. However, it requires a large number of inelastic time-history analyses (and corresponding detailed data on ground motion time-histories and hysteretic behavior of structural elements) and is thus very time-consuming. Often it is possible to create summarized IDA curves with less input data, with less effort, but with still acceptable accuracy. One possible approach is to determine seismic demand for multiple levels... 

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