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Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains cycles.
For the mechanical models, the factor with the greatest influence is the definition and modelling of matrix cracking.
In our models the factor loading for the slope growth factor on T2 was freely estimated.
In such models, the factor loading reflects the strength of the association between the observed item and the latent construct.
It was found that in the importance-weighted models the factor structure was stronger, due to improved distributional characteristics of the individual items.
However, if the factor prone position is omitted from the models, the factor level of the tumor above the left atrium became more important and vice versa.
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According to the definitions and categories of factors in the two models, the factors were compared.
Before comparing the models, the factor-analytic study results from the present study (using residents and caregivers combined) were compared with five previous findings.
To establish sensitive and reliable models, the factors influencing profiling should be recognised.
The multivariate analysis is a probit model, which models the factors associated with roll-out of CBHI to the districts.
Taguchi quality-loss functions are adapted to model the factor mean and variance effects.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com