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in the town of Lebanon, Pennsylvania It is produced entirely from beef and is a moist, heavily smoked, fermented, ready-to-eat sausage with an M : P of 35 : 1 that is often not processed above 489 C (Chikthimmah et al 2001) The starter culture involving L plantarum, P acidilactici, and micrococci was speci cally developed to obtain a very low pH (44 47), and it ferments the meat batter at 35 38 C (Smith and Palumbo 1973) In traditional processes, black pepper is added as seasoning, and the coarse ground meat is pre-salted and aged for several days under refrigeration Sweet bologna is produced with 10% to 12% of sugar instead of the 2% to 4% in Lebanon bologna Snack sticks are shelf-stable semidry sausages that include hot seasonings and edible collagen casings.

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FUTURE DIRECTIONS The area of program and policy development has, to some extent, been a fertile area for those trying to advance statistical analysis (eg, Rubin, 1974) and research design (eg, Shadish et al, 2002) The potential exists for signi cant future developments Among the areas where future developments are needed are the following four First, the theory and techniques of values inquiry is a fertile ground for additional work Values inquiry is a relatively recent offshoot of stakeholder approaches Additional experience is needed both to re ne the speci c methods of values inquiry and to gain experience about how well the general values inquiry approach works in practice Second, conceptual and methodological developments are needed to help us specify what constitutes a given program or type of program (Lipsey, 2001).

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Typically, we de ne programs in terms of either (a) a common funding stream (eg, all local sites funded through Head Start are called Head Start ) or (b) claims that program staff are following some named program (eg, regardless of the funding source, drug prevention offerings in schools are called DARE, for Drug Abuse Resistance Training, if police of cers are involved).

7, we can rewrite transactions T1 and T2 as follows:.

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But how much deviation should be allowed, and on which dimensions of service delivery, among the activities of local sites while still justifying use of the same program name For example, should a local school s drug prevention activities be called DARE if someone other than a police of cer serves as the program staff How far can a police of cer vary from the DARE curriculum and still have it constitute an instance of DARE In essence, the fundamental question is, How do we decide that two speci c cases are instances of the same category A related question is, In a world of hierarchically embedded categories, how do we decide which level of categorization is more important For example, should we be concerned about whether a local school s activity is an instance of DARE or of the more inclusive category, resistance skills training approaches to drug use prevention Further work on how to de ne the program could have bene cial effects outside of evaluation because similar questions about how to de ne constructs abound in the social and behavioral sciences.

Third, there is need for the development of better methods for rigorous estimates of the effects of everyday programs (Lipsey, 2001) As Lipsey noted, it appears that, at least in some policy areas, most of the rigorous causal evaluations are directed at demonstration projects interventions specially set up in order to test their effects rather than at everyday, ongoing programs Demonstration programs can facilitate the use of random assignment, for example, in a way that is rarely.

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possible ways to proceed One choice is to examine the distribution of solutions and assume that the solution reached most often is the best one, and that one can be selected as the nal model A second approach is to select the solution with the best t, which corresponds to the highest likelihood A third way to proceed is to simplify the model being t, which will reduce the number of parameters being estimated This often is enough to ensure that just one solution is reached Any combination of these approaches can be used together in deciding upon a nal solution Fortunately, for many latent class analyses only one solution will be identi ed Missing Data As has been reviewed extensively in the missing data literature (eg Collins, Schafer, & Kam, 2001; Schafer, 1997), there are three major classi cations of missing data.

where a 2 f0; 1; . . . ; Ag and A is the maximum batch size for PDU arrival (i.e., 1 A 1). The complementary cumulative probability mass function for this arrival process is given by Fa lj

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