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Introduction - Multilevel Analysis
Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 1996The authors of this article, who are also the guest editors for this issue on multilevel analysis, give an overview and brief history of multilevel analysis and present the following four research articles. Multilevel Analysis - Overview. Methods. History.
van den Eeden, P., Hox, J.J.C.M.
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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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British Journal of Mathematical and Statistical Psychology, 2006
A general framework for the exploratory component analysis of multilevel data (MLCA) is proposed. In this framework, a separate component model is specified for each group of objects at a certain level. The similarities between the groups of objects at a given level can be expressed by imposing constraints on component models of the groups using the ...
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A general framework for the exploratory component analysis of multilevel data (MLCA) is proposed. In this framework, a separate component model is specified for each group of objects at a certain level. The similarities between the groups of objects at a given level can be expressed by imposing constraints on component models of the groups using the ...
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Sociological Methods & Research, 1994
This special issue of SMR is about the analysis of data collected at different levels of observation, such as groups and individuals within these groups, and about the methodological problems that are present when natural experimentation and observations nested within existing social groups are the object of study.
JOOP J. HOX, ITA G. G. KREFT
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This special issue of SMR is about the analysis of data collected at different levels of observation, such as groups and individuals within these groups, and about the methodological problems that are present when natural experimentation and observations nested within existing social groups are the object of study.
JOOP J. HOX, ITA G. G. KREFT
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ACM Transactions on Embedded Computing Systems, 2015
Phase analysis, which classifies the set of execution intervals with similar execution behavior and resource requirements, has been widely used in a variety of systems, including dynamic cache reconfiguration, prefetching, race detection, and sampling simulation.
Weihua Zhang +3 more
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Phase analysis, which classifies the set of execution intervals with similar execution behavior and resource requirements, has been widely used in a variety of systems, including dynamic cache reconfiguration, prefetching, race detection, and sampling simulation.
Weihua Zhang +3 more
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Multilevel structural analysis
Social Networks, 1993Abstract Multilevel structural analysis links the macrostructures of large populations in successive steps to the network structures in face-to-face groups. Macrostructure is conceptualized as a multidimensional space of positions among which people are distributed.
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Sampling Considerations for Multilevel Crossing Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1982This paper examines the amplitude fluctuations of band-limited functions with bounded zeroth absolute moments, and the problems associated with estimating the level crossing profiles of these functions. Level crossings have received increased attention as features for pattern recognition because of their capability to provide information related to ...
Woods, Richard E., Gonzalez, Rafael C.
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Multilevel analysis with messy data
Statistical Methods in Medical Research, 2001This paper reviews applications of the method of multiple imputation to dealing with multilevel data that have several kinds of imperfections. These are classified into two broad categories: missing values and imprecise measurement (corrupted recording). The role of the model describing the data imperfections is emphasized.
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2006
This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel
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This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel
openaire +1 more source