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There are a number of other revenue and cost analysis techniques and tools available apart from those already mentioned. Some of the more common ones are discussed briefly in the next section. Caution must be exercised in their use.
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In other words, every time the user moves the cell cursor, the Worksheet_SelectionChange procedure is executed. This procedure calls the UpdateChart procedure, which follows:
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also varies, with some dependency measures more interpersonal (e.g., Social Self-Con dence) than others (e.g., Emotional Reliance).
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Shumaker (Eds.), Advanced structural equation modeling: New developments and techniques (pp. 269 296). Mahwah, NJ: Erlbaum. Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238 246. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley. Boomsma, A. (1982). Robustness of LISREL against small sample sizes in factor analysis models. In K. G. J reskog & H. Wold (Eds.), Systems under indirect observation: Pt. 1. Causality, structure, prediction (pp. 149 173). Amsterdam: North-Holland. Boomsma, A. (2000). Reporting analyses of covariance structures. Structural Equation Modeling, 7, 461 483. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136 162). Newbury Park, CA: Sage. Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications and programming. Mahwah, NJ: Erlbaum. Byrne, B. M. (2003). Testing for equivalent self-concept measurement across culture: Issues, caveats, and application. In H. W. Marsh, R. G. Craven, & D. M. McInerney (Eds.), International advances in self research (Vol. 1, pp. 291 314). Greenwich, CT: Information Age. Byrne, B. M., Shavelson, R. J., & Muth n, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456 466. Calsyn, R. J., & Kenny, D. A. (1977). Self-concept of ability and perceived evaluation of others: Cause or effect of academic achievement Journal of Educational Psychology, 69, 136 145. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81 105. Cheung, G. W., & Rensvold, R. B. (2001). The effects of model parsimony and sampling error on the fit of structural equation models. Organizational Research Methods, 4, 236 264. Collins, L. M., Schafer, J. L., & Kam, C.-M. (2001). A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods, 6, 330 351. Cudeck, R., & Browne, M. W. (1983). Cross-validation of covariance structures. Multivariate Behavioral Research, 18, 147 167. Ding, L., Velicer, W. F., & Harlow, L. L. (1995). The effects of estimation methods, number of indicators per factor and improper solutions on structural equation modeling fit indices. Structural Equation Modeling, 2, 119 144. Duda, J. L. (1993). Goals: A social-cognitive approach to the study of achievement motivation in sport. In R. N. Single, M.
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DDBEs require secure communications, both between users and the DDBE and among the Sub-DBEs themselves. Secure communication typically demands privacy, authentication, and integrity. This means that we must protect against both passive eavesdroppers who can monitor messages passed over the network and active attackers who can not only monitor messages but can also inject new or modi ed messages into the network. In general, whenever we need to implement some security capability, we should use an existing, well-hardened protocol. This protocol should, in turn, use one or more of the existing, well-hardened cryptographic building blocks. We should use building blocks that were written by an experienced vendor or a trusted opensource project. Security algorithms, protocols, and implementations are extremely hard to design, implement, and deploy, and history is littered with well-intentioned, failed attempts. We will look at two well-known, well-hardened technologies for achieving end-to-end secure communications: SSL/TLS and Virtual Private Networks (VPNs).
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adolescent athletes who perceive their parents as providing an ego-involving climate are themselves higher in ego goal orientation. In addition, White (1998) found that a parentinitiated ego-involving climate was associated with higher competitive trait anxiety in the athletes, whereas a parentinitiated task-involving climate was associated with lower levels of competitive trait anxiety in athletes. The results of this research establish at least an initial link between the type of climate parents create for their children and the children s own attitudes, values, beliefs, and psychosocial responses. Other researchers (e.g., Harwood & Swain, 2001) have also found links between parents and their children in regard to their achievement goals as well as the motivational climate parents create for and with their young athletes. Parents Gender Beliefs and Values Eccles s (2005; Eccles et al., 1998; Fredricks & Eccles, 2004) expectancy-value model clearly includes the notion that parents belief and value systems as well as their behavior toward and with their children will vary as a function of the child s gender. Consistent with this idea, a number of research studies have shown that parents tend to (a) value sport and physical activity more for their sons than for their daughters; ( b) provide more encouragement for their sons participation than for their daughters ; and (c) perceive their sons to have higher sport competence than do their daughters (e.g., Brustad, 1993; Eccles, Jacobs, & Harold, 1990; Fredricks & Eccles, 2005; Jacobs & Eccles, 1992). Furthermore, Fredricks and Eccles have recently found that parents of sons bought more athletic equipment, were more apt to encourage them to participate in sport, and spent more time on sport activities than did parents of daughters. A similar gender difference was found by Welk, Wood, and Morss (2003) in their study on physical activity levels in children from grades 3 through 6. Specifically, boys in this study perceived that their parents provided more facilitation for their physical activity (e.g., provision of equipment, access, or opportunities to be active) than did girls. Furthermore, M. R. Weiss and Hayashi (1995) found that young male gymnasts perceived higher frequencies of positive and supportive behaviors from their father (e.g., attendance at meets, interest shown, encouragement, and provision of instruction during meets) than did female gymnasts. In interviewing adolescents, Coakley and White (1992) found that girls perceived that their parents placed constraints on them that limited their participation in
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