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12.3.3.2 Internet Control Message Protocol (ICMP). ICMP is used as an adjunct to IP when there is an error in datagram processing. ICMP uses the basic support of IP as if it were a higher-level protocol; however, ICMP is actually an integral part of IP and is implemented by every IP module. ICMP messages are sent in several situations: for example, when a datagram cannot reach its destination, when a gateway (router) does not have the buffering capacity to forward a datagram, and when the gateway (router) can direct the host to send traf c on a shorter route. ICMP messages typically report errors in the processing of datagrams. To avoid the possibility of in nite regress of messages about messages, and so on, no ICMP messages are sent about ICMP messages. There are eight distinct ICMP messages:

Each of these procedures calls the LogEvent procedure and passes an argument that consists of the event name and the object. The LogEvent procedure follows:

There are usually no restrictions on the number or power of CPUs in the server hardware supporting the software nor on the number of users accessing the software Usually, the only restriction is that the software application must be confined to the organization s internal use In some cases, the price of the software may include an additional cost for a developer license These licenses are based on the number of developer seats required for the developers to create dashboards for regular business users..

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Be patient; this can take a while. Many elements conspire to slow things down, such as the time of day (how many other users are currently active and sharing the same resources); optimum hardware capabilities; and the size of the data set you must acquire. Again, this must occur only once on the network (with the MBE).

Fluid V-P Figure 21.1 Change in estimated mean Adjusted Fluid V-P (VisualizationPerformance) scores over twenty years for Hypertensive (H) and Normotensive (N) cohorts participating in the Maine-Syracuse Longitudinal Study of Cognitive Function. Change scores are adjusted for age, education, occupation, gender, and treatment with antihypertensive medication. Adapted for this chapter from tabled data presented in Elias, M. F., Robbins, M. A., Elias, P. K., and Streeten, D. H. P. (1998). A longitudinal study of blood pressure in relation to performance on the Wechsler Adult Intelligence Scale. Health Psychology, 17, 486 493, with permission of the authors.

1 2 3 4 5

. . . . . .

(5.41)

Totals $6,510 $310 Unfavorable Cost variance $6,200 $200 Sales Unfavorable volume variance $6,000

$ 940,000 370,400 $1,310,400 $9,055,000

Figure 18-10 shows a chart that is interactive. The chart plots data stored in columns A and B, and buttons on the chart allow the user to change the chart so it shows more or fewer months of data. Using the ChartSeries class makes this type of coding relatively easy.

text version ofAmos, an example of which is included in Graham (in press). It is also straightforward in LISREL and other text-based FIML procedures. Latent-Variable Regression With Amos or With LISREL/EQS and Multiple Imputation A latent-variable example is beyond the scope of this chapter. However, we would like to make a few points in this regard. First, the extension to latent-variable analysis is trivial in Amos (assuming prior knowledge of SEM). One simply performs the analysis with individual variables as indicators of latent variables rather than with the composite indices. Amos handles the rest. The model for including additional variables is the same as previously described. With LISREL 8.50 (Mx, and the FIML aspect of Mplus), latent-variable models with incomplete data are a trivial extension of latent variable models with complete data. With LISREL, one simply adds the statement MI = 9 (assuming the missing value indicator is 9) to the Data Parameters statement. As previously mentioned, the addition of missingdata relevant variables to the model is straightforward. For using multiple imputation with EQS 5.x (Bentler, 1986) and Mplus (Muth n, 2001), the situation is a little more complicated, but no more so than the analysis with SPSS previously described in this chapter. Utility programs have been written to use these two programs with NORM (Schafer, 1997). The two utilities, NORMEQS and NORMplus, make use of a single EQS 5.x or Mplus 2 input le to read and analyze the multiple imputed data sets, combine the results, and provide MI inference. These utilities, along with user guides, can be obtained free at our web site.

1. 2. 3.

Example 1.8: Determine the a priori and a posteriori entropies for the channel of Example 1.7. The a priori entropy is equal to H (X ) = 4 log2 5 5 4 + 1 log2 (5) = 0.7219 bits 5

w=a 1=2 exp4 36:6

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