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However, a clearer separation of crosscutting concerns would be of bene t to meta-level architectures This provides the incentive to utilize AOP within re ective middleware projects A major impediment to the use of AOP techniques within re ective systems has been the implementation techniques used by the initial incarnations of AOP [33] Traditionally, when an aspect is inserted into an object, the compiler weaves the aspect into the objects code; this results in the absorption of the aspect into the object s runtime code The lack of preservation of the aspect as an identi able runtime entity is a hindrance to the dynamic adaptive capabilities of systems created with aspects Workarounds to this problem exist in the form of dynamic system recompilation at runtime; however, this is not an ideal solution and a number of issues, such as the transference of the system state, pose problems.

However, it should also be acknowledged that longitudinal surveys have their own problems, in particular panel attrition and possible panel conditioning Like cross-sectional surveys, longitudinal surveys suffer from unit nonresponse at the first round They also suffer from sample attrition at later rounds The overall response rates for the original panel of youth in the YMCLS dropped from 428 % in the first round, to 381 % in the second round and to 312 % in the third round For the NSPY, the overall youth response rates across the four rounds were 648 %, 567 %, 548 %, and 522 % For GEAR UP, the overall youth response rates in the first two rounds were 868 % and 796 %.

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Attrition raises the concern that the increasing loss of cases over waves of the panel may threaten the representativeness of the sample at later points This concern is shared with other longitudinal surveys and was addressed through attrition nonresponse weighting adjustments in the surveys reported here A special and more challenging aspect of attrition arises in evaluation studies where cases may drop out of the study as a direct result of their reaction to the treatment The concern about panel conditioning is that panel members in a longitudinal survey become atypical as a result of participating in the survey (see Cantor, 2008; Sturgis et al, 7 of this volume) This concern is potentially more serious in intervention evaluation studies For example, panel members may become sensitized to the existence of the intervention through their participation in the study, resulting in changes in true exposure.

Measurement biases in self-reported exposure may also be subject to conditioning Section 173 provides evidence of this type of panel conditioning in the YMCLS The measurement bias in self-reported exposure can sometimes be affected by the way in which exposure is captured For example, with an ongoing media campaign the exposure measurement could be anchored to time-specific advertising content In passing, it should be noted that trends in outcomes over time are sometimes used to evaluate ongoing interventions like VERB and the National Youth Anti-Drug Media Campaign Longitudinal surveys can provide trend data, but so can a series of repeated cross-sectional surveys For the analysis of trends, a series of repeated surveys has the considerable advantage of avoiding problems of attrition and panel conditioning.

Alternative implementations of AOP have emerged that do not have this limitation These approaches propose a method of middleware construction using composition [34] to preserve aspect as runtime entities, this method of creation facilitates the application of AOP for the construction of re ective middleware platforms Another approach involving Java bytecode manipulation libraries such as Javassist [35] provide a promising method of implementing AOP frameworks (ie AspectJ 12+, AspectWerkz and JBossAOP) with dynamic runtime aspect weaving One of the founding works on AOP highlighted the process of performance optimization that bloated a 768-line program to 35,213 lines Rewriting the program with the use of AOP techniques reduced the code back to 1039 lines while retaining most of the performance bene ts.

An interrupted time series design can provide strong evidence on abrupt intervention effects provided that there is a series of measurements both before and after the intervention (Shadish et al, 2002) Without such a time series, there are many other factors that could explain a trend..

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