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The complete and incomplete cases are then sorted into subgroups based on these propensity scores Finally, missing data are replaced by values taken from a randomly chosen donor in the same imputation class This procedure is repeated a number of times to generate multiple imputations The advantage of the nonparametric approach is that it does not require an explicit data model; the implicit model for the missing data is provided by the observed data In addition, it will always generate imputed values that actually exist in the observed data Multiple imputation may be somewhat laborious, but it is a powerful approach The power of multiple imputation, especially in longitudinal research, is based on the notion that the imputation model need not be the same as the analysis model.

In Huygens picture, a wave is not a single ripple, but is built up of a lot of tiny wavelets, moving outwards in all directions from each point on the front of the original wave. Generally the ones going off in odd directions would cancel each other out as one goes left, the other goes right, and the result is no movement. But heading in the direction of the wave, there is no cancellation and the motion continues along.

The following code excerpt shows how to send a simple JMS message using the point to point model of JMS:

The most important imperative for the imputation model is that it should be at least as complex as the analysis model to be used Thus, if it is anticipated that nonlinear curves will be fitted to a longitudinal dataset, nonlinear terms must also be used when the incomplete data are imputed When interactions are tested, interaction terms should be included in the imputation model In nonparametric imputation, where existing values are imputed from a donor case, this happens implicitly, but there is no rule against the imputation model being more complex than the analysis model As we stated before, in longitudinal research there is a potential richness of auxiliary variables, both initially measured and time-varying variables.

Not only can missing data at time point t (yt) be imputed using the information from previous measurement occasions (yt 1, yt 2), but also later observations (yt + 1) can in due course be used in the imputation process In multiple imputation, the preferred strategy would be to use as many variables as possible Collins, Schafer and Kam (2001) investigated whether a liberal use of available auxiliary variables improves the results They conclude that a liberal strategy is clearly superior to a restrictive strategy Using many auxiliary variables for imputation not only decreases the chance of overlooking an important cause of missingness, but also increases the accuracy of the imputed values If it is necessary to select a smaller number of auxiliary variables, Collins et al recommend looking for auxiliary variables that predict the incomplete variables well, and/or auxiliary variables that correlate with the missingness mechanism..

14:2-11

Activation in an entity bean must also perform extra tasks. Where ejbCreate() is used to insert new data into the database and then make the bean immediately active, the ejbActivate() method is called by the server when it wishes to bring a pooled bean back into use. When this method is called, you cannot assume that the bean represents exactly the same data it represented the last time it was active. During the activation process, you should make sure to load the new data. How do you know which data to reload You must consult the EntityContext to find the current primary key and reload data based on it. The code for doing this looks remarkably like the code in the ejbLoad() method that you wrote just a little while ago:

For most of your downloading needs, the best place to start is Sun's Java site. Keep in mind that because most of the APIs are pluggable with driver implementations, once you have downloaded drivers to use with the J2EE reference implementation, these drivers will be usable with any commercial environment that you may purchase at a later date. Implementations of the reference environment for Solaris, Linux, and Win32 are available from Sun at http://java.sun.com/j2ee/download.html. If you also need a copy of the J2SE environment, head to http://java.sun.com/j2se/1.3/ for the latest copy of v1.3. (1.4 is in beta at the time of writing). Tip The reference implementation does not contain any native code. If you are confident playing with shell scripts, it will not be very difficult to grab the installation bundle and copy it onto any other UNIX based platform, including Apple's Mac OS X. If you don't have either the JDK or J2EE reference implementation downloaded, then we suggest looking at obtaining a CD copy, which is also available from http://java.sun.com/j2se/1.3/. When you combine the two development kits and the documentation you are looking at around 150 MB of downloads. That's a lot of download time if you are only on a 56K modem!