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The challenges of developing and delivering a computer-based simulation of the patient management environment were signi cant, but this was only part of the effort required to produce a useful assessment tool In order for the system to be useful for licensure evaluation, it had to be possible to quantify examinee responses as an indication of pro ciency: it was not only necessary to collect meaningful examinee responses; it was necessary to score them During much of the period in which Primum was being developed, effort was also underway to create scoring procedures The evolution of these procedures was associated with dramatic changes; four conceptually different systems were developed Each of these scoring procedures required that the simulation system be able to capture examinee responses and compare them to a key The procedures differed in which information was used to calculate the scores and how that information was aggregated The simplest and earliest procedures were based on the scoring approaches that had been applied to PMPs administered on paper Although there were many variations on this theme, the basic approach is that examinees are given points for selecting keyed actions that were identi ed as bene cial for management and points are lost for ordered actions that are non-indicated and may be dangerous to the patient The main problem with this approach was that test-wise examinees could sometimes achieve adequate scores by ordering non-intrusive procedures and avoiding potentially risky procedures Adequate scores did not necessarily re ect adequate management A second scoring procedure that was examined applied the Rasch model to the response patterns based on the key (Julian and Wright, 1988) More than any of the others, this approach is purely data driven It provided an implicit weighting for items based on the likelihood that examinees of a given pro ciency level would order those actions Both of these approaches were limited by the fact that the resulting scores may not show a strong correspondence to the judgments that expert clinicians would make if they eviewed the associated examinee performances The nal two scoring approaches that were studied share in common the fact that they are both explicit efforts to model that expert judgment Again, both approaches begin with items that could be quanti ed based on a kind of key Content experts reviewed case material and identi ed actions that would be bene cial for the given case presentation This de nition of bene cial was process rather than outcomes based in that bene cial items were those that would be appropriate for patients with a given presentation For example, diagnostic tests that would rule out reasonable differential diagnoses may be considered as bene cial as those that would identify the speci c problem that would ultimately prove to be the correct answer In addition to identifying those actions that would be considered bene cial, content experts categorized the non-indicated actions based on their level of potential risk to the patient (or level of invasiveness) These latter two procedures differed in terms of how the scored actions were combined to create an aggregate score The rst of these procedures used linear regression For this.

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Mathematical/Statistical Features and Characteristics in Visual Studio .NET Make Code 128 ode Set B in Visual Studio .NET Mathematical/Statistical Features and Characteristics. In Visual Studio .NET Using Barcode recognizer for .Data, which is used to investigate data characteristics of attack and normal use activities in Part III, is collected from a computer running the Windows XP Professional with Service ack 2 The performance objects [1] on the Windows XP Professional are used to collect data under eleven attack conditions and two normal use conditions This chapter describes the Windows performance objects data, attack and normal use conditions, the computer setup for the data collection, and the procedure of running eleven attacks and two normal use activities.Related: 

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su to root 2 Run the rpm -ivh e2fsprogs-versionsrcrpm command to extract the source into a /usr/src/redhat/SOURCES/ directory The source RPM drops a e2fsprogs-versiontargz file that needs to be extracted using the tar xvzf e2fsprogs-versiontargz command This creates a subdirectory called e2fsprogs-version 3 Change to the new subdirectory 4 Run mkdir build to create a new subdirectory and then change to that directory 5 Run /configure script to configure the source tree 6 Run the make utility to create the binaries 7 Run the make check command to nsure that everything is built correctly 8 Run the make install command to install the binaries After you have installed the e2fsprogs utilities you can start using them as discussed in the following sections. 417 In Visual Studio .NET Using Barcode printer for .Related: