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In applied research, such as with motivation theories, typically many variables are theoretically implied predictors of an outcome and several interactions are assumed (e.g., Watt, 2004). However, estimation problems that might arise when several interaction and/or quadratic effects are analyzed simultaneously have not been investigated because simulation studies on interaction effects in the structural equation modeling framework have mainly focused on small models that contain single interaction effects. In this article, we show that traditional approaches can provide estimates with low accuracy when complex models are estimated. We introduce an adaptive Bayesian lasso approach with spike-and-slab priors that overcomes this problem. Using a complex model in a simulation study, we show that the parameter estimates of the proposed approach are more accurate in situations with high multicollinearity or low reliability compared with a standard Bayesian lasso approach and typical frequentist approaches (i.e., unconstrained product indicator approach and latent moderated structures approach). 相似文献
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Ellen Brandt 《Higher Education》2002,44(3-4):393-411
In the 1990s, universities received morediversified demands for continuing education.Market demands may contribute to createinnovative courses and introducing newperspectives. A critical question is, however,if universities should respond to all marketdemands, or base continuing education onresearch-oriented teaching and learning. Casestudies of Norwegian universities show thesecond understanding to be universal there.Strategic plans are quite general, so differentstrategies for continuing education areinferred from course offers and interviews. Sixstrategies are presented and discussed:Research news for professionals; Same contentwith flexible delivery; Adapted specialisation;Interdisciplinary Master's degrees;Interdisciplinary courses for new markets;Tailor-made on commission. 相似文献