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The Arc Geographical Information System (ArcGIS) has seen much use in spatial analytics and modeling in different perspectives and is one of the most advanced and reliable geospatial analytical tools available [35 37].
The objective of this paper is to stress the important differences between IRT and CTT for latent variable modeling in different situations and show why IRT measurement models should be used in longitudinal research.
Cellular automata (CA) models are extensively applied in urban growth modeling in different forms (i.e., pixel or patch).
Statistical modeling in different datasets has found that a separation between neurocognition and social cognition fit the data best (Allen et al. 2007; Bell et al. 2009).
Similar modeling in different human methylomes (Xie et al., 2013) revealed that these regulatory principles apply similarly in other somatic cell types and organism.
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These complicated situations are modeled in different scenarios.
In the literature, for many fiber systems, the fiber-fiber interactions are modeled in different ways.
To assure the perceptual quality of the signal after DST, the DST parameters can be modeled in different ways.
Epistasis can be modeled in different ways (Cordell 2002).
Inhomogeneous surfaces can be modeled in different ways.
In addition, different degrees of dependency between liability of dropping out and the study variables were modeled in different populations.
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