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Modelling latent variables at individual level using multivariate analysis (such as regression) in transport policy research has long been recognised as a robust way to gain insights into understanding relationships between multi-dimensional issues.
Recent methods developed for team sports suggest including context information like Game Context Features [24] and contextual trajectory information [25], improving tracking by modelling latent behaviour from team-level context dynamics [26] or by improving the detection step [27, 28].
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In this paper, we propose a machine learning approach to model latent, heterogeneous consumer tastes from social Web reviews.
First, PLS can be used to model latent constructs as either formative (superordinate constructs) or reflective indicators (unmeasured latent constructs) [12, 72].
Compared with previous attempts to model latent pavement condition index utilizing SEM method, more pavement condition measurements and influencing factors were included.
Standard methods of quantitative genetic analysis were used to model latent genetic and environmental factors influencing sibling covariance for MZ and DZ twins.
Another refinement is proposed by the CLASCAL model (Latent Class Approach) (Winsberg and De Soete [32]).
Repeated-measure analyses encompass univariate models (with or without sphericity adjustment), multivariate models, mixed models, analysis of covariance, multilevel models, latent growth models, and hybrids of these models.
To this end, Bos et al. (2012a, b) model latent profiles of student achievement in reading, mathematics, and science for 4th-grade students in Germany.
One can fit factor models, latent class models, structural equation models, mixture models, latent growth curve models, and others within the MLM framework.
In multivariate regression models, latent class was strongly associated with emotional distress.
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