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The structural model with relationships between structure, process, and outcome reasonably represented quality systems at hospital departments.
A model with relationships between the structure, process, and outcome of quality systems was developed from the results of an interview study[ 4].
To verify the estimated coefficients of the fitted model for N = 42, we deleted the direct effects of the exogenous variables on the endogenous variables, resulting in an estimated ASE model with relationships between the endogenous variables only.
The model with relationships between structure, process, and outcome was found to be a reasonable representation of quality systems at hospital departments (p = 0.095, indicating no significant differences between the model and the data set).
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Bivariate sire models with relationships among sires were used to estimate parameters.
Note that model (2) with relationships as presented here is the most obvious generalisation of the Wei and van der Werf model in Eq. (1) from two to three breeds since base individuals are assumed unrelated.
The best example is to consider social networking models, or other models with relationship elements that are either not easily expressed in a traditional table structure or where a table and relationship based structure does not scale.
Unlike traditional linear regression, non-linear regression can estimate a model with arbitrary relationships between dependent and independent variables (SPSS 2012).
A multi-fluid Eularian CFD model with closure relationships according to the kinetic theory of granular flow has been applied to study the motions of particles in the gas bubbling fluidized bed with the binary mixtures.
To elucidate the importance of these possible relations, we constructed a model with bidirectional relationships for these variables.
Gengler et al. [ 9] suggested that missing genotypes could be modelled using the usual mixed model methodology with relationship matrix A. We now combine that idea with the genomic relationship matrix on the form (1).
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