YPQ110A 3ASD573001A5 system module PLC system module

YPQ110A 3ASD573001A5 system module PLC system module

Technical data of product parameters

As discussed earlier, since cross-sectional studies are based on the comparison of roadway units with a
common feature to roadway units that do not have that feature, they are more prone to confounding
(Hauer, 2005; Elvik, 2011a). There are issues with before-after studies as well (e.g., bias due to
regression to the mean), but there is more consensus among the research community about differentYPQ110A 3ASD573001A5
ways to address the issues associated with before-after studies. Such a consensus does not yet exist to
address the issues associated with cross-sectional studies. However, as discussed earlier in this
document, there are some treatments for which before-after studies would simply not be feasible. One
example is the safety of median width. Agencies rarely expand or realign a roadway section just for the
sake of changing the median width. In such cases, cross-sectional studies would be appropriate for
developing a CMF. Following is some discussion about the different factors that may be considered inYPQ110A 3ASD573001A5
selecting an appropriate study design (part of this discussion is based on information from Sections 3.8
and 4.0, as well as Figure 5 from Gross et al., 2010).
To conduct a before-after study, information is needed on a sufficient number of sites where a
sufficiently similar treatment has been installed or can be installed. If there is possibility of bias due to
RTM, then a reference group can be used to develop SPFs to apply the empirical Bayes method, or a
sufficiently long before period should be considered to minimize the possible bias due to RTM for
applying a time series or intervention analysis method. A comparison or reference group is necessary toYPQ110A 3ASD573001A5
account for temporal effects. If spatial correlation is a factor or if prior knowledge of CMF estimates
need to be included in the evaluation, then a full Bayes approach would be a better approach compared
to the empirical Bayes method. The full Bayes approach is also more flexible and can be applied even if
the sample of reference sites is limited, or if the functional form of the SPF is complex (e.g., needs to
include additive and multiplicative terms).

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