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of the target variable income is shown in Figure 4.4. The darker bands indicate the proportion of high incomes. Clearly, this proportion increases until about age 52, after which it begins to drop again. This behavior is nonlinear and should not be naively modeled as linear in the logistic regression. Suppose, for example, that we went ahead and performed a logistic regression of income on the singleton predictor age. The results are shown in Table 4.19. Table 4.19 shows that the predictor age is signi cant, with an estimated odds ratio of 1.04. Recall that the interpretation of this odds ratio is as follows: that the odds of having high income for someone of age x + 1 is 1.04 times higher than for someone of age x. Now consider this interpretation in light of Figure 4.4. The odds ratio of 1.04 is clearly inappropriate for the subset of subjects older than 50 or so. This is because the logistic regression assumes linearity, whereas the actual relationship is quadratic (nonlinear.) There are a couple of approaches we could take to alleviate this problem. First, we could use indicator variables as we did earlier. Here, we use an indicator variable age 33 65, where all records falling in this range are coded as 1 and all other records are coded as 0. This coding was used because the higher incomes were found to fall within this range in the histogram. The resulting logistic regression is shown in Table 4.20. The odds ratio is 5.01, indicating that persons between 33 and



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Proof: This follows directly from the weak law of large numbers. 1 P1 (X1 , X2 , . . . , Xn ) 1 log = log n P2 (X1 , X2 , . . . , Xn ) n

Voltage (E):





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making this distinction. However, in differentiating schizophrenia from affective disorder, item information should be maximized around point B. If a scale is intended to be useful in making a variety of such distinctions, one would prefer a scale to be composed of items that contain information relevant to discriminations across the entire relevant range or the full depth of the construct. In other words, a scale should be composed of items sampling information across the full spectrum of the concept if it is to be able to make a variety of different diagnostic distinctions. As an example, the item response model was used as a conceptual guide in selecting items for the nal version of the PAI (Morey, 1991a), in an attempt to select items that provided information across the full spectrum of the concept in question. Through an examination of the item characteristic curves of potential items, the nal items were selected to provide information across the full range of construct severity. The nature of the severity continuum varied across the constructs on the test; for example, for the Suicidal Ideation scale, this continuum involved the imminence of the suicidal threat. Thus, items on this scale varied from vague and illarticulated thoughts about suicide to immediate plans for self-harm, allowing the examiner to capture information, not only about the presence of suicidal thinking, but about its intensity. Discriminant Validity A test is said to have discriminant validity if it provides a measure of a construct that is speci c to that construct; in other words, the measurement is free from the in uence of other constructs. Although discriminant validity has long been recognized as an important facet of construct validity, it has not traditionally played a major role in the construction of

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7.3.2.2.1 Multifrequency Signaling. Multifrequency (MF) signaling has been in wide use around the world for interregister signaling. It is an in-band method using ve or six tone frequencies, two tones at a time. It works well over metallic pair, FDM, and TDM systems. MF systems are robust and dif cult to cheat. Three typical MF systems are reviewed in the following:

If the maximum rate of symbols per second, s, allowed in the channel is known, then the capacity of the channel per time unit is equal to C = sCs bps (42)

gures. Anticipated deployments are given in the rst columns relating to the three constellations. The early TRANSIT satellites, like Parus and Tsikada, are not included in the tables. Note also that the Satellite Based Augmentation Systems (SBAS) are not included, although some such satellites do enable ranging as well. In Table 6.8, the number of signals for each constellation is the total number of transmitted signals, irrespective of the fact they are civil, military, or reserved. In parentheses are the names of the newly added codes. Care must be taken when analyzing this table. For instance, there were three signals at the early stage of GPS, only one being civil. But civilian receivers using phase measurements on L1 and L2 were available. Table 6.8 has counted only one signal in this case.

3 B 11.11

Condensed Balance Sheet Dec. 31, 0003 Assets Liabilities Stockholders Equity: Capital stock Retained earnings $205,000 $182,000 $20,000 3,000

1 10 1 9

Wireless ATM MAC protocol relative characteristics PRMA/DA DSA++ FDD variable medium medium high high MASCARA TDD variable high high medium high DTDMA TDD fixed high medium high medium

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