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1.00, with both endpoints of the con dence interval also reported as 1.00. Do we conclude from this that capnet is not signi cant If so, how do we resolve the apparent contradiction with the strongly signi cant z-test p-value of approximately zero Actually, of course, there is no contradiction. The problem lies in the fact that the odds ratio results are reported only to two decimal places. More detailed 95% con dence intervals are provided here: CI(ORcapnet ) = exp[b1 z SE(b1 )] = exp [0.0002561 (1.96)(0.0000079)] = (e0.0002406 , e0.0002716 ) = (1.000241, 1.000272) Thus, the 95% con dence interval for the capnet variable does not include the null value of e0 = 1, indicating that this variable is in fact signi cant. Why is such precision needed Because capnet is measured in dollars. One additional dollar in capital gains, for example, would presumably not increase the probability of a high income very dramatically hence, the tiny but signi cant odds ratio. However, nearly 87% of the records have zero capnet (neither capital gains nor capital losses). What effect would this have on the linearity assumption Table 4.14 provides the income-level counts for a possible categorization of the capnet variable. Note that high income is associated with either capnet loss or capnet gain $3000, while low income is associated with capnet none or capnet gain < $3000. Such relationships are incompatible with the assumption of linearity. We would therefore like to rerun the logistic regression analysis, this time using the capnet categorization shown in Table 4.14.

Gustard, A, Bullock, A, and Dixon, JM, 1992, Low Flow Estimation in the United Kingdom IH Report no 108 Institute of Hydrology, Wallingford, UK Guti rrez-Santolalla, F, Guti rrez-Elorza, M, Mar n, C, Maldonado, C, and Younger, PL, 2005, Subsidence hazard avoidance based on geomorphological mapping in the Ebro River valley mantled evaportie karst terrain (NE Spain) Environmental Geology, 48: 370 383 Gutjahr, AL and Gelhar, LW, 1981, Stochastic-models of subsurface ow in nite versus nite domains and stationarity Water Resources Research, 17: 337 350 Haines, TS and Lloyd JW, 1985, Controls on silica in groundwater environments in the United Kingdom Journal of Hydrology, 81: 277 295..

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It also appears that the environment does not have an effect that is independent of preexisting genetic factors Reviews by Reiss, Neiderhiser, Hetherington, and Plomin (2000) and Caspi and Bem (1990) document personalityenvironment interaction and the way the individuals select and create their own environment Genetic factors in uence the environmental variables that are the focus of attention and the situations that the individual selects For example, some kinds of life events are not independent of the individual; rather, their occurrence is in uenced by such traits as Neuroticism and Extraversion (eg, Poulton & Andrews, 1992; Magnus, Diener, Fujita, & Pavot, 1993) Saudino, Pedersen, Lichtenstein, and McClearn (1997) showed that all genetic variance on controllable, desirable, and undesirable life events in women was common to the genetic in uences underlying EPQ Neuroticism and Extraversion, NEO-FFI Openness to Experience (Costa & McCrae, 1985).

[28] Warwick K.: Wiring in Humans: Advantages and problems as humans become part of the machine network via implants . Presentation in SWAMI Final Conference in Brussels, 21 22 March, 2006. Summary of the presentation in Friedewald M. and Wright D.: Safeguards in a World of Ambient Intelligence (SWAMI) , Deliverable D5, Report on the Final Conference, Brussels, 21 22 March 2006. [29] Wilhemsson T.: Kertomus parisuhteesta ja sopimuksesta . Oikeus, Vol. 1, 1999, pp. 66 74. [30] Wilhelmsson T. and J askinen N.: Avoimet yhti t ja kommandiittiyhti t. Kauppakaari Lakimiesliiton kustannus, a o o 2001.

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22 S Mitra and J Rabek Power ef cient clustering for clock synchronization in dynamic multihop networks, unpublished See at http://theorylcsmitedu/mitras/courses/ 6829/project/ nal_reportps, 2003 23 S Ganeriwal, R Kumar, and M B Srivastava Timing-sync protocol for sensor networks In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys), pages 138 149, November 2003 24 J van Greunen and J Rabaey Lightweight time synchronization for sensor networks In Proceedings of the 2nd ACM International Workshop on Wireless Sensor Networks and Applications (WSNA), pages 11 19, San Diego, California, September 2003 25 P Blum, L Meier, and L Thiele Improved interval-based clock synchronization in sensor networks In Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks (IPSN), pages 349 358, Berkeley, California, April 2004 26 Q Li and D Rus Global clock synchronization in sensor networks.