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While the first - order factor dimensional models had mostly similar fit indices (AIC values: 481.7 -510.4), the original three - factor model had a slightly better fit.
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The dimensional models have been criticized in the past by the lack of differentiation of neighborhood emotions in the valence and arousal dimensions such as anger and fear [36].
Various dimensional models have been proposed in order to distinguish common and distinct features of depression and anxiety and to further investigate the components of the broad internalizing factor.
An emphasis on dimensional models has been developed within the NIMH Research Domains Criteria (RDoC) project [ 10, 11], particlarly for diagnosis, permitting continuous variables of function, ranging from behavior down to neurobiology.
A one dimensional model has been used for the analysis for both the regions.
A one dimensional model has been developed and presented to calculate the seasonal energy yield of solar air collectors.
A two dimensional model has been set up of the movements of coarse particles during pneumatic transport in a pipe.
A semi-empirical (dimensional) model has been developed to predict the performance of an inline dynamic mixer within a specific application to ensure effective process design and operation.
Dimensional modeling has been adopted as the predominant method for designing data warehouses and data marts in practice and, as such, represents an important contribution to the discipline of data modeling and database design.
Steady state one dimensional model has been developed to identify the operation parameters and to describe the propane and oxygen conversions, gas process and coolant temperatures, as well as other parameters affecting the reactor performance such as pressure.
The higher-dimensional models have been accordingly analyzed in [13, 14].
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