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If you develop applications that need to work in all versions of Excel, be aware of some potentially serious compatibility issues that arise when you use API calls. For example, if you develop an application using Excel 97 or later that uses API calls, the application will not run with Excel 5 even if you save the workbook in the Excel 5 format because Excel 5 is a 16-bit application. Excel 97 and later versions are 32-bit applications. Excel 2002 is a 32-bit application (and uses 32-bit API calls) and Excel 5 is a 16-bit application. Refer to 26 for additional information and tips on how to circumvent this problem.

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Brown, 2000) While avoiding the risk of pregnancy, such extra-intercourse sexual activity still presents the risk of sexually transmitted disease Sexually Transmitted Disease The increased number of teenagers becoming sexually active at younger ages prompts concern regarding sexually transmitted disease (STD) not only because there is a longer time for potential exposure but also because of the cumulative effect on number of sexual partners For example, of women who were sexually active by age 15, 25% reported 10 or more lifetime sexual partners, in contrast to 6% of those who delayed sexual activity until age 20 (see Cates & Berman, 1999) Also, teenagers may be more vulnerable to infection if they are exposed, both because they are less likely to use protection consistently and because their immune and reproductive systems are less well-developed than those of adults (eg, cervical.

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Declare variables Dim x As Integer Dim y As Integer Dim z As Integer Start the routine x = 100 Assign 100 to x y = 200 Assign 200 to y Add x and y and store in z z = x + y Show the result MsgBox z End Sub

11.5.4.2 Average BER. Given the average PEP according to Eq. (11.27), the corresponding BER for the th error vector, starting in the ith position, is given by Pi; a PEPi; 11:28

While true score theory acknowledges measurement error, in most approaches it does not generally allow for different levels of measurement error for different levels of ability (but see Feldt & Brennan, 1989, and Lee, Brennan, & Kolen, 2000, for exceptions). Assumptions Applying the true and error score model of CTT requires assuming that errors are random and therefore uncorrelated with each other and uncorrelated with true scores. If such errors are a combination of several factors, then a normal distribution of errors can be expected, with a mean of zero and a

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[It] would appear that there are signi cant differences in means among the cultures in terms of emotional distance, geographical distance, meetings, and telephone communications. This would support the argument that cultures vary in terms of signi cant differences in emotional distance to members of the nuclear and extended family, in terms of how close or far they live from these members, how often they meet these members, and how often they telephone them. [20]

The master control center, which stores the data and monitors the on-board instrumentation;

SUGGESTIONS FOR FURTHER STUDY This chapter has been intended as an introduction to a topic with many complex facets. To become more familiar with logistic regression, the reader may want to consult many of the sources that have been cited throughout the chapter. Two volumes that are especially informative are those by Hosmer and Lemeshow (1989) and Long (1997). One major use of logistic regression not covered in this chapter is in survival analysis. This technique is used whenever one is examining the unfolding of events in time. For example, one may be investigating the factors that predict the onset of sexual intercourse among at-risk youth or the timing of entrance into or egress from marital unions. In these analyses, the response variable can be cast in two equivalent forms. First, it can be the length of time people survive in a given state (celibacy, singlehood, marriage) until the occurrence of the event of interest (sexual intercourse, marriage, divorce). Or it can be the hazard of event occurrence. The latter is approximately the instantaneous probability of event occurrence at time t, given that no event has occurred prior to t, for a group of cases at risk for the event. Logistic regression is a convenient statistical tool for estimating survival or hazard models. For those wishing to learn about this use of the technique, Allison (1982, 1995) and Singer and Willett (1993) are especially good source materials.

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