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Covariance structure analysis of nonnormal data is important because in practice all data are nonnormal. When applying covariance structure analysis to nonnormal data, it is generally assumed that the asymptotic covariance matrix Γ for the nonredundant terms in the sample covariance matrix S is...
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One of the common features of innovative SMEs identified from our previous surveys and in-depth interviews is innovation capability accumulated inside the firm, which enables them to create new products which meet customer needs and to cooperate with the other firms. The factors that SMEs...
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The noncentral chi-square approximation of the distribution of the likelihood ratio (LR) test statistic is a critical part of the methodology in structural equations modeling (SEM). Recently, it was argued by some authors that in certain situations normal distributions may give a better...
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