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Tools form the basis of deploying our application. These tools provide the underlying infrastructure, doing things like loading JDBC drivers, managing our EJBs, and deploying the EJBs to the server. In total, the reference implementation contains 12 tools most of which you won't use under normal circumstances. We are going to cover the four most commonly used tools the server, a tool to package and deploy EJB, the included database, and also a tool to reset the other tools when you make a mistake. As the reference implementation is very simple, all these tools are run from a command line so fire up a new shell or DOS prompt and let's get going! Tip All the tools are run by batch files. You can find these in the bin directory underneath the installation directory. If you have set up the PATH correctly (as we demonstrated in the previous section), you will have access to all these tools with no further effort.

created a gender role attitude score by coding the responses to each of the six items, in such a way that a higher score indicates a more liberal gender role attitude, and then summing them. The score ranges from 6 to 30, with a mean in 1991 of 21.2 and a standard deviation of 3.7. One advantage of graphical chain models is their ability to handle response variables of different types: continuous, binary and multicategory. When the response is continuous, as is the case for the attitude score, we use linear regression models. When the response is binary, as is the case for whether or not the respondent becomes a parent, or multicategory, as is the case for the respondent s change in labour force status, we use binary and multinomial logistic regression models, respectively. Furthermore, sample weights, clustered samples and item nonresponse can be handled using the standard techniques developed for the component models. A disadvantage in the GCM approach considered here is that it does not use the information in the repeated measures or model the reciprocal relationship simultaneously. Hence, it is not easy to assess the overall goodness of fit of the model to the data. Also, it is difficult to explicitly adjust for measurement error without introducing a separate stage of latent variable modelling.

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String cmd = "SELECT * FROM Product WHERE category = "; PreparedStatement stmt = conn.prepareStatement(cmd); ... stmt.setString(1, "book"); ResultSet rs = stmt.executeQuery();

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interviewer or the centralized tracking team while the case is in tracking status) and the sum of these two (total calls). Positive outliers were truncated at three standard deviations above the mean. The HRS has a large disparity in effort according to whether or not tracking was required, similar to that found in the PSID. Households not requiring tracking in 2004 needed an average of 5.23 field calls, compared to 9.40 for households needing tracking. In addition, households needing tracking required an additional 7.36 tracking calls, yielding an overall differential of 11.53 total calls (16.76 for tracking households vs. 5.23 for nontracking households).7 This differential is reduced only slightly when examined in a multivariate context, and tracking status remains a significant (P 5 0.001) predictor of overall effort. Thus, as with the PSID, tracking in the HRS adds significant costs to data collection. Also presented in Table 11.7 are means for number of calls by participation in the 2003 supplements. In addition to being a strong predictor of need for tracking, this indicator is also highly predictive of effort, controlling for tracking status. Such factors can be effectively used to identify households or respondents who are likely to be difficult to track. Those cases can then be targeted for centralized tracking prior to or at the start of the field period, reducing effort on the part of interviewers during the field period.

The technology viewpoint describes what kinds of technologies will be used in the connection of provisioning and providing of services. The spectrum of different technologies available for service

Summary

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Table 2.1 A plan of the layout of tables of dietary standards (e.g. RNIs or RDAs). Nutrient 1 Age group (examples) 0 3 months 10 12 months 1 3 years 7 10 years 11 14 years (female) 19 50 years (male) 19 50 years (female) 50+ years (female) Pregnant Lactating

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