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Multilevel Mixture Factor Models
Multivariate Behavioral Research, 2012Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure.
Varriale R., Vermunt J. K.
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Multilevel Materials for Multilevel Learners
2014The presence of learner diversity is inevitable in any language classroom. Not only do our learners differ in their ages, interests, learning styles, goals, and motivation, but their levels of proficiency may also vary. In everyday teaching, practitioners are constantly faced with the problems of finding the right materials for all their learners.
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Multilevel Models for Multilevel Network Dependencies
2015We explain how a type of multilevel model called a Multiple Membership Multiple Classification (MMMC) model can be used to investigate multilevel network dependencies for a nodal dependent variable at the lowest level of such a structure. In particular, the MMMC model allows us to estimate the relative share of variation in the dependent variable ...
Tranmer, Mark, Lazega, Emmanuel
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Multilevel Functional Clustering Analysis
Biometrics, 2012Summary In this article, we investigate clustering methods for multilevel functional data, which consist of repeated random functions observed for a large number of units (e.g., genes) at multiple subunits (e.g., bacteria types). To describe the within‐ and between variability induced by the hierarchical structure in the data, we take a multilevel ...
Serban, Nicoleta, Jiang, Huijing
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International Journal of Injury Control and Safety Promotion, 2012
Many of the commonly used methods in statistics assume that the data come from a random sample taken from a population of interest.
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Many of the commonly used methods in statistics assume that the data come from a random sample taken from a population of interest.
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Multilevel Gaussian graphical model for multilevel networks
Journal of Statistical Planning and Inference, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cheng, Lulu, Shan, Liang, Kim, Inyoung
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2013
The representation of many real-world scenarios in conceptual models benefits from the use of multilevel abstraction hierarchies. Product models, for example, are typically grouped into product categories which, in turn, constitute the company’s range of products.
Christoph Schütz +2 more
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The representation of many real-world scenarios in conceptual models benefits from the use of multilevel abstraction hierarchies. Product models, for example, are typically grouped into product categories which, in turn, constitute the company’s range of products.
Christoph Schütz +2 more
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Cascaded multilevel inverter using sub-multilevel cells
Electric Power Systems Research, 2013Abstract The multilevel inverters have been in the center of focus of many researcher in recent years. This is partly because of some advantages such as improved output power quality. The multilevel inverters can generate a near sinusoidal output voltage. The quality of output voltage depends on the number of voltage levels of inverter.
Ebrahim Babaei +3 more
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IEEE Transactions on Computers, 1987
In this correspondence we present a design technique for implementation of systems of Boolean functions in the form of multilevel AND-OR networks. We show that for a given system of Boolean functions, the transition from the additional two-level AND-OR implementation to multilevel AND-OR implementations results in considerable savings in gate counts ...
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In this correspondence we present a design technique for implementation of systems of Boolean functions in the form of multilevel AND-OR networks. We show that for a given system of Boolean functions, the transition from the additional two-level AND-OR implementation to multilevel AND-OR implementations results in considerable savings in gate counts ...
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Neighborhoods and violent crime: a multilevel study of collective efficacy.
Science, 1997R. Sampson, S. Raudenbush, F. Earls
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